Tootfinder

Robust Partitioning and Operation for Maximal Uncertain-Load Delivery in Distribution Grids
Hannah Moring, Harsha Nagarajan, Kshitij Girigoudar, David M. Fobes, Johanna L. Mathieu
https://arxiv.org/abs/2404.03137

Robust Partitioning and Operation for Maximal Uncertain-Load Delivery in Distribution Grids
To mitigate the vulnerability of distribution grids to severe weather events, some electric utilities use preemptive de-energization as the primary line of defense, causing significant power outages. In such instances, networked microgrids could improve resiliency and maximize load delivery, though the modeling of three-phase unbalanced network physics and computational complexity pose challenges. These challenges are further exacerbated by an increased penetration of uncertain loads. In this p…

Eight-Partitioning Points in 3D, and Efficiently Too
Boris Aronov, Abdul Basit, Gianluca Tasinato, Indu Ramesh, Uli Wagner
https://arxiv.org/abs/2403.02627

Eight-Partitioning Points in 3D, and Efficiently Too
An \emph{eight-partition} of a finite set of points (respectively, of a continuous mass distribution) in $\mathbb{R}^3$ consists of three planes that divide the space into $8$ octants, such that each open octant contains at most $1/8$ of the points (respectively, of the mass). In 1966, Hadwiger showed that any mass distribution in $\mathbb{R}^3$ admits an eight-partition; moreover, one can prescribe the normal direction of one of the three planes. The analogous result for finite point sets foll…

WindGP: Efficient Graph Partitioning on Heterogenous Machines
Li Zeng, Haohan Huang, Binfan Zheng, Kang Yang, Shengcheng Shao, Jinhua Zhou, Jun Xie, Rongqian Zhao, Xin Chen
https://arxiv.org/abs/2403.00331

WindGP: Efficient Graph Partitioning on Heterogenous Machines
Graph Partitioning is widely used in many real-world applications such as fraud detection and social network analysis, in order to enable the distributed graph computing on large graphs. However, existing works fail to balance the computation cost and communication cost on machines with different power (including computing capability, network bandwidth and memory size), as they only consider replication factor and neglect the difference of machines in realistic data centers. In this paper, we p…

This https://arxiv.org/abs/2312.14889 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_sta…

On Rate-Optimal Partitioning Classification from Observable and from Privatised Data
In this paper we revisit the classical method of partitioning classification and study its convergence rate under relaxed conditions, both for observable (non-privatised) and for privatised data. Let the feature vector $X$ take values in $\mathbb{R}^d$ and denote its label by $Y$. Previous results on the partitioning classifier worked with the strong density assumption, which is restrictive, as we demonstrate through simple examples. We assume that the distribution of $X$ is a mixture of an abs…

Extended Donnan model for ion partitioning in charged nanopores
R. Wang, M. Elimelech, P. M. Biesheuvel
https://arxiv.org/abs/2403.02796 https://

Extended Donnan model for ion partitioning in charged nanopores
Membranes consist of pores and the walls of these pores are often charged. In contact with an aqueous solution, the pores fill with water and ions migrate from solution into the pores until chemical equilibrium is reached. The distribution of ions between outside and pore solution is governed by a balance of chemical potential, and the resulting model is called a Donnan theory, or Donnan equation. Including a partitioning coefficient that does not depend on salt concentration results in an exte…

This https://arxiv.org/abs/2404.01022 has been replaced.
link: https://scholar.google.com/scholar?q=a

On the Complexity of Minimizing Energy Consumption of Partitioning DAG Tasks
We study a graph partition problem where we are given a directed acyclic graph (DAG) whose vertices and arcs can be respectively regarded as tasks and dependencies among tasks. The objective of the problem is to minimize the total energy consumed for completing these tasks by assigning the tasks to k heterogeneous machines. We first show that the problem is NP-hard. Then, we present polynomial-time algorithms for two special cases where there are only two machines and where the input DAG is a d…

Graph Partitioning With Limited Moves
Majid Behbahani, Mina Dalirrooyfard, Elaheh Fata, Yuriy Nevmyvaka
https://arxiv.org/abs/2402.15485 https://

Graph Partitioning With Limited Moves
In many real world networks, there already exists a (not necessarily optimal) $k$-partitioning of the network. Oftentimes, one aims to find a $k$-partitioning with a smaller cut value for such networks by moving only a few nodes across partitions. The number of nodes that can be moved across partitions is often a constraint forced by budgetary limitations. Motivated by such real-world applications, we introduce and study the $r$-move $k$-partitioning~problem, a natural variant of the Multiway c…

Play like a Vertex: A Stackelberg Game Approach for Streaming Graph Partitioning
Zezhong Ding, Yongan Xiang, Shangyou Wang, Xike Xie, S. Kevin Zhou
https://arxiv.org/abs/2402.18304

Play like a Vertex: A Stackelberg Game Approach for Streaming Graph Partitioning
In the realm of distributed systems tasked with managing and processing large-scale graph-structured data, optimizing graph partitioning stands as a pivotal challenge. The primary goal is to minimize communication overhead and runtime cost. However, alongside the computational complexity associated with optimal graph partitioning, a critical factor to consider is memory overhead. Real-world graphs often reach colossal sizes, making it impractical and economically unviable to load the entire gra…

This https://arxiv.org/abs/2302.12115 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csNI_…

Dynamic realization of miscellaneous profile services in elastic optical networks using spectrum partitioning
Optical backbone networks are required to be highly dynamic in supporting requests with flexible bandwidth granularities to cope with the demands of new broadband wireless and fixed access networks. To provide this flexibility, services are offered by taking requested bandwidth profile into consideration, instead of assigning a fixed amount of bandwidth to each request. New techniques are developed for the resource management of the elastic optical networks to realize services with a specified …

On the Optimality of CVOD-based Column Selection
Maria Emelianenko, Guy B. Oldaker IV
https://arxiv.org/abs/2403.00121 https://arxiv.…

On the Optimality of CVOD-based Column Selection
While there exists a rich array of matrix column subset selection problem (CSSP) algorithms for use with interpolative and CUR-type decompositions, their use can often become prohibitive as the size of the input matrix increases. In an effort to address these issues, the authors in \cite{emelianenko2024adaptive} developed a general framework that pairs a column-partitioning routine with a column-selection algorithm. Two of the four algorithms presented in that work paired the Centroidal Voronoi…

This https://arxiv.org/abs/2310.08213 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csDB_…

A Universal Scheme for Dynamic Partitioned Shortest Path Index
Shortest path (SP) computation is the fundamental operation in various networks such as urban networks, logistic networks, communication networks, social networks, etc. With the development of technology and societal expansions, those networks tend to be massive. This, in turn, causes deteriorated performance of SP computation, and graph partitioning is commonly leveraged to scale up the SP algorithms. However, the partitioned shortest path (PSP) index has never been systematically investigated…

Graph Partitioning With Limited Moves
Majid Behbahani, Mina Dalirrooyfard, Elaheh Fata, Yuriy Nevmyvaka
https://arxiv.org/abs/2402.15485 https://

Graph Partitioning With Limited Moves
In many real world networks, there already exists a (not necessarily optimal) $k$-partitioning of the network. Oftentimes, one aims to find a $k$-partitioning with a smaller cut value for such networks by moving only a few nodes across partitions. The number of nodes that can be moved across partitions is often a constraint forced by budgetary limitations. Motivated by such real-world applications, we introduce and study the $r$-move $k$-partitioning~problem, a natural variant of the Multiway c…

Partitioning the projective plane to two incidence-rich parts
Zolt\'an L\'or\'ant Nagy
https://arxiv.org/abs/2403.13734 https://

Partitioning the projective plane to two incidence-rich parts
An internal or friendly partition of a vertex set $V(G)$ of a graph $G$ is a partition to two nonempty sets $A\cup B$ such that every vertex has at least as many neighbours in its own class as in the other one. Motivated by Diwan's existence proof on internal partitions of graphs with high girth, we give constructive proofs for the existence of internal partitions in the incidence graph of projective planes and discuss its geometric properties. In addition, we determine exactly the maximum poss…

This https://arxiv.org/abs/2401.01657 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csRO_…

Distributed Pose-graph Optimization with Multi-level Partitioning for Collaborative SLAM
The back-end module of Distributed Collaborative Simultaneous Localization and Mapping (DCSLAM) requires solving a nonlinear Pose Graph Optimization (PGO) under a distributed setting, also known as SE(d)-synchronization. Most existing distributed graph optimization algorithms employ a simple sequential partitioning scheme, which may result in unbalanced subgraph dimensions due to the different geographic locations of each robot, and hence imposes extra communication load. Moreover, the performa…

This https://arxiv.org/abs/2404.15080 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csIT_…

Flexible Field Sizes in Secure Distributed Matrix Multiplication via Efficient Interference Cancellation
In this paper, we propose a new secure distributed matrix multiplication (SDMM) scheme using the inner product partitioning. We construct a scheme with a minimal number of workers and no redundancy, and another scheme with redundancy against stragglers. Unlike previous constructions in the literature, we do not utilize algebraic methods such as locally repairable codes or algebraic geometry codes. Our construction, which is based on generalized Reed-Solomon codes, improves the flexibility of th…

This https://arxiv.org/abs/2312.15084 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csCV_…

Automated forest inventory: analysis of high-density airborne LiDAR point clouds with 3D deep learning
Detailed forest inventories are critical for sustainable and flexible management of forest resources, to conserve various ecosystem services. Modern airborne laser scanners deliver high-density point clouds with great potential for fine-scale forest inventory and analysis, but automatically partitioning those point clouds into meaningful entities like individual trees or tree components remains a challenge. The present study aims to fill this gap and introduces a deep learning framework, termed…

CarbonCP: Carbon-Aware DNN Partitioning with Conformal Prediction for Sustainable Edge Intelligence
Hongyu Ke, Wanxin Jin, Haoxin Wang
https://arxiv.org/abs/2404.16970

CarbonCP: Carbon-Aware DNN Partitioning with Conformal Prediction for Sustainable Edge Intelligence
This paper presents a solution to address carbon emission mitigation for end-to-end edge computing systems, including the computing at battery-powered edge devices and servers, as well as the communications between them. We design and implement, CarbonCP, a context-adaptive, carbon-aware, and uncertainty-aware AI inference framework built upon conformal prediction theory, which balances operational carbon emissions, end-to-end latency, and battery consumption of edge devices through DNN partiti…

Improving Multi-Instance GPU Efficiency via Sub-Entry Sharing TLB Design
Bingyao Li, Yueqi Wang, Tianyu Wang, Lieven Eeckhout, Jun Yang, Aamer Jaleel, Xulong Tang
https://arxiv.org/abs/2404.18361

Improving Multi-Instance GPU Efficiency via Sub-Entry Sharing TLB Design
NVIDIA's Multi-Instance GPU (MIG) technology enables partitioning GPU computing power and memory into separate hardware instances, providing complete isolation including compute resources, caches, and memory. However, prior work identifies that MIG does not extend to partitioning the last-level TLB (i.e., L3 TLB), which remains shared among all instances. To enhance TLB reach, NVIDIA GPUs reorganized the TLB structure with 16 sub-entries in each L3 TLB entry that have a one-to-one mapping to th…

This https://arxiv.org/abs/2403.07068 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_qu…

Multiset tomography: Optimizing quantum measurements by partitioning multisets of observables
Quantum tomography approaches typically consider a set of observables which we wish to measure, design a measurement scheme which measures each of the observables and then repeats the measurements as many times as necessary. We show that instead of considering only the simple set of observables, one should consider a multiset of the observables taking into account the required repetitions, to minimize the number of measurements. This leads to a graph theoretic multicolouring problem. We show th…

Unveiling Linguistic Regions in Large Language Models
Zhihao Zhang, Jun Zhao, Qi Zhang, Tao Gui, Xuanjing Huang
https://arxiv.org/abs/2402.14700 https://…

Unveiling Linguistic Regions in Large Language Models
Large Language Models (LLMs) have demonstrated considerable cross-lingual alignment and generalization ability. Current research primarily focuses on improving LLMs' cross-lingual generalization capabilities. However, there is still a lack of research on the intrinsic mechanisms of how LLMs achieve cross-lingual alignment. From the perspective of region partitioning, this paper conducts several investigations on the linguistic competence of LLMs. We discover a core region in LLMs that correspon…

Balanced Partitioning for Optimizing Big Graph Computation: Complexities and Approximation Algorithms
Baoling Ning, Jianzhong Li
https://arxiv.org/abs/2404.05949

Balanced Partitioning for Optimizing Big Graph Computation: Complexities and Approximation Algorithms
Graph partitioning is a key fundamental problem in the area of big graph computation. Previous works do not consider the practical requirements when optimizing the big data analysis in real applications. In this paper, motivated by optimizing the big data computing applications, two typical problems of graph partitioning are studied. The first problem is to optimize the performance of specific workloads by graph partitioning, which lacks of algorithms with performance guarantees. The second pro…

This https://arxiv.org/abs/2305.14461 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csDS_…

Engineering Rank/Select Data Structures for Large-Alphabet Strings
Large-alphabet strings are common in scenarios such as information retrieval and natural-language processing. The efficient storage and processing of such strings usually introduces several challenges that are not witnessed in small-alphabets strings. This paper studies the efficient implementation of one of the most effective approaches for dealing with large-alphabet strings, namely the \emph{alphabet-partitioning} approach. The main contribution is a compressed data structure that supports t…

Deep Clustering Evaluation: How to Validate Internal Clustering Validation Measures
Zeya Wang, Chenglong Ye
https://arxiv.org/abs/2403.14830 https://

Deep Clustering Evaluation: How to Validate Internal Clustering Validation Measures
Deep clustering, a method for partitioning complex, high-dimensional data using deep neural networks, presents unique evaluation challenges. Traditional clustering validation measures, designed for low-dimensional spaces, are problematic for deep clustering, which involves projecting data into lower-dimensional embeddings before partitioning. Two key issues are identified: 1) the curse of dimensionality when applying these measures to raw data, and 2) the unreliable comparison of clustering res…

This https://arxiv.org/abs/2311.04536 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csDC_…

Uniform Partitioning of a Bounded Region using Opaque ASYNC Luminous Mobile Robots
We are given $N$ autonomous mobile robots inside a bounded region. The robots are opaque which means that three collinear robots are unable to see each other as one of the robots acts as an obstruction for the other two. They operate in classical \emph{Look-Compute-Move} (LCM) activation cycles. Moreover, the robots are oblivious except for a persistent light (which is why they are called \emph{Luminous robots}) that can determine a color from a fixed color set. Obliviousness does not allow the…

Towards Cohesion-Fairness Harmony: Contrastive Regularization in Individual Fair Graph Clustering
Siamak Ghodsi, Seyed Amjad Seyedi, Eirini Ntoutsi
https://arxiv.org/abs/2402.10756

Towards Cohesion-Fairness Harmony: Contrastive Regularization in Individual Fair Graph Clustering
Conventional fair graph clustering methods face two primary challenges: i) They prioritize balanced clusters at the expense of cluster cohesion by imposing rigid constraints, ii) Existing methods of both individual and group-level fairness in graph partitioning mostly rely on eigen decompositions and thus, generally lack interpretability. To address these issues, we propose iFairNMTF, an individual Fairness Nonnegative Matrix Tri-Factorization model with contrastive fairness regularization that…

Attention-aware Semantic Communications for Collaborative Inference
Jiwoong Im, Nayoung Kwon, Taewoo Park, Jiheon Woo, Jaeho Lee, Yongjune Kim
https://arxiv.org/abs/2404.07217

Attention-aware Semantic Communications for Collaborative Inference
We propose a communication-efficient collaborative inference framework in the domain of edge inference, focusing on the efficient use of vision transformer (ViTs) models. The partitioning strategy of conventional collaborative inference fails to reduce communication cost because of the inherent architecture of ViTs maintaining consistent layer dimensions across the entire transformer encoder. Therefore, instead of employing the partitioning strategy, our framework utilizes a lightweight ViT mod…

1/4 "Barbarians" by Jacek Markusiewicz impresses me like no other recent work of #GenerativeArt has.
The images of majestic mountain slopes and neatly arranged fields – with occasional buildings strewn in between them – at first feel strangely detached and bland, thanks to a distant, aerial point of view and bleached, bright colours. Yet the way the landscapes are unexpectedl…

superblockify: A Python Package for Automated Generation, Visualization, and Analysis of Potential Superblocks in Cities
Carlson Moses B\"uth, Anastassia Vybornova, Michael Szell
https://arxiv.org/abs/2404.15062

superblockify: A Python Package for Automated Generation, Visualization, and Analysis of Potential Superblocks in Cities
superblockify is a Python package for partitioning an urban street network into Superblock-like neighborhoods and for visualizing and analyzing the partition results. A Superblock is a set of adjacent urban blocks where vehicular through traffic is prevented or pacified, giving priority to people walking and cycling. The Superblock blueprints and descriptive statistics generated by superblockify can be used by urban planners as a first step in a data-driven planning pipeline, or by urban data s…

Self-healing Nodes with Adaptive Data-Sharding
Ayush Thakur, Sanskar Chauhan, Ilisha Tomar, Vaibhavi Paul, Deepak Gupta
https://arxiv.org/abs/2405.00004 ht…

Self-healing Nodes with Adaptive Data-Sharding
Data sharding, a technique for partitioning and distributing data among multiple servers or nodes, offers enhancements in the scalability, performance, and fault tolerance of extensive distributed systems. Nonetheless, this strategy introduces novel challenges, including load balancing among shards, management of node failures and data loss, and adaptation to evolving data and workload patterns. This paper proposes an innovative approach to tackle these challenges by empowering self-healing nod…

The Fundamental Parameters of Astrophysical Plasma Turbulence and its Dissipation: Nonrelativistic Limit
Gregory G. Howes
https://arxiv.org/abs/2402.12829 …

The Fundamental Parameters of Astrophysical Plasma Turbulence and its Dissipation: Nonrelativistic Limit
A specific set of dimensionless plasma and turbulence parameters is introduced to characterize the nature of turbulence and its dissipation in weakly collisional space and astrophysical plasmas. Key considerations are discussed for the development of predictive models of the turbulent plasma heating that characterize the partitioning of dissipated turbulent energy between the ion and electron species and between the perpendicular and parallel degrees of freedom for each species. Identifying the…

Distributed Simulation of Large Multi-body Systems
Manas Kale, Paul G. Kry
https://arxiv.org/abs/2403.17261 https://arxiv.org/pdf/240…

Distributed Simulation of Large Multi-body Systems
We present a technique designed for parallelizing large rigid body simulations, capable of exploiting multiple CPU cores within a computer and across a network. Our approach can be applied to simulate both unilateral and bilateral constraints, requiring straightforward modifications to the underlying physics engine. Starting from an approximate partitioning, we identify interface bodies and add them to overlapping sets such that they are simulated by multiple workers. At each timestep, we blend…

Deep Clustering Evaluation: How to Validate Internal Clustering Validation Measures
Zeya Wang, Chenglong Ye
https://arxiv.org/abs/2403.14830 https://

Deep Clustering Evaluation: How to Validate Internal Clustering Validation Measures
Deep clustering, a method for partitioning complex, high-dimensional data using deep neural networks, presents unique evaluation challenges. Traditional clustering validation measures, designed for low-dimensional spaces, are problematic for deep clustering, which involves projecting data into lower-dimensional embeddings before partitioning. Two key issues are identified: 1) the curse of dimensionality when applying these measures to raw data, and 2) the unreliable comparison of clustering res…

Memory-Efficient and Secure DNN Inference on TrustZone-enabled Consumer IoT Devices
Xueshuo Xie, Haoxu Wang, Zhaolong Jian, Tao Li, Wei Wang, Zhiwei Xu, Guiling Wang
https://arxiv.org/abs/2403.12568

Memory-Efficient and Secure DNN Inference on TrustZone-enabled Consumer IoT Devices
Edge intelligence enables resource-demanding Deep Neural Network (DNN) inference without transferring original data, addressing concerns about data privacy in consumer Internet of Things (IoT) devices. For privacy-sensitive applications, deploying models in hardware-isolated trusted execution environments (TEEs) becomes essential. However, the limited secure memory in TEEs poses challenges for deploying DNN inference, and alternative techniques like model partitioning and offloading introduce p…

A Transition System Abstraction Framework for Neural Network Dynamical System Models
Yejiang Yang, Zihao Mo, Hoang-Dung Tran, Weiming Xiang
https://arxiv.org/abs/2402.11739

A Transition System Abstraction Framework for Neural Network Dynamical System Models
This paper proposes a transition system abstraction framework for neural network dynamical system models to enhance the model interpretability, with applications to complex dynamical systems such as human behavior learning and verification. To begin with, the localized working zone will be segmented into multiple localized partitions under the data-driven Maximum Entropy (ME) partitioning method. Then, the transition matrix will be obtained based on the set-valued reachability analysis of neura…

Multiset tomography: Optimizing quantum measurements by partitioning multisets of observables
Otto Veltheim, Esko Keski-Vakkuri
https://arxiv.org/abs/2403.07068

Multiset tomography: Optimizing quantum measurements by partitioning multisets of observables
Quantum tomography approaches typically consider a set of observables which we wish to measure, design a measurement scheme which measures each of the observables and then repeats the measurements as many times as necessary. We show that instead of considering only the simple set of observables, one should consider a multiset of the observables taking into account the required repetitions, to minimize the number of measurements. This leads to a graph theoretic multicolouring problem. We show th…

New Invariants for Partitioning a Graph into 2-connected Subgraphs
Michitaka Furuya, Masaki Kashima, Katsuhiro Ota
https://arxiv.org/abs/2403.08465 https:/…

New Invariants for Partitioning a Graph into 2-connected Subgraphs
A vertex partition in which every part induces a 2-connected subgraph is called a 2-proper partition. This concept was introduced by Ferrara et al. in 2013, and Borozan et al. gave the best possible minimum degree condition for the existence of a 2-proper partition in 2016. Later, in 2022, Chen et al. extended the result by showing a minimum degree sum condition for the existence of 2-proper partition. In this paper, we introduce two new invariants of graph, denoted by $σ^*(G)$ and $α^*(G)$. …

Buffered Streaming Edge Partitioning
Adil Chhabra, Marcelo Fonseca Faraj, Christian Schulz, Daniel Seemaier
https://arxiv.org/abs/2402.11980 https://

Buffered Streaming Edge Partitioning
Addressing the challenges of processing massive graphs, which are prevalent in diverse fields such as social, biological, and technical networks, we introduce HeiStreamE and FreightE, two innovative (buffered) streaming algorithms designed for efficient edge partitioning of large-scale graphs. HeiStreamE utilizes an adapted Split-and-Connect graph model and a Fennel-based multilevel partitioning scheme, while FreightE partitions a hypergraph representation of the input graph. Besides ensuring s…

This https://arxiv.org/abs/2402.08397 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csCV_…

A Neural-network Enhanced Video Coding Framework beyond ECM
In this paper, a hybrid video compression framework is proposed that serves as a demonstrative showcase of deep learning-based approaches extending beyond the confines of traditional coding methodologies. The proposed hybrid framework is founded upon the Enhanced Compression Model (ECM), which is a further enhancement of the Versatile Video Coding (VVC) standard. We have augmented the latest ECM reference software with well-designed coding techniques, including block partitioning, deep learning…

Hardness of Packing, Covering and Partitioning Simple Polygons with Unit Squares
Jack Stade, Mikkel Abrahamsen
https://arxiv.org/abs/2404.09835 https://

Hardness of Packing, Covering and Partitioning Simple Polygons with Unit Squares
We show that packing axis-aligned unit squares into a simple polygon $P$ is NP-hard, even when $P$ is an orthogonal and orthogonally convex polygon with half-integer coordinates. It has been known since the early 80s that packing unit squares into a polygon with holes is NP-hard~[Fowler, Paterson, Tanimoto, Inf. Process. Lett., 1981], but the version without holes was conjectured to be polynomial-time solvable more than two decades ago~[Baur and Fekete, Algorithmica, 2001]. Our reduction reli…

This https://arxiv.org/abs/2303.02130 has been replaced.
initial toot: https://mastoxiv.page/@arX…

Towards Entanglement Entropy of Random Large-N Theories
A large class of strongly correlated quantum systems can be described in certain large-N limits by quadratic in field actions along with self-consistency equations that determine the two-point functions. We use the replica approach and the notion of shifted Matsubara frequency to compute von Neumann and Rényi entanglement entropies for generic bi-partitioning of such systems. We argue that the von Neumann entropy can be computed from equilibrium spectral functions w/o partitioning, while the R…

Flexible Field Sizes in Secure Distributed Matrix Multiplication via Efficient Interference Cancellation
Okko Makkonen
https://arxiv.org/abs/2404.15080 htt…

Flexible Field Sizes in Secure Distributed Matrix Multiplication via Efficient Interference Cancellation
In this paper, we propose a new secure distributed matrix multiplication (SDMM) scheme using the inner product partitioning. We construct a scheme with a minimal number of workers and no redundancy, and another scheme with redundancy against stragglers. Unlike previous constructions in the literature, we do not utilize algebraic methods such as locally repairable codes or algebraic geometry codes. Our construction, which is based on generalized Reed-Solomon codes, improves the flexibility of th…

BOND: Bootstrapping From-Scratch Name Disambiguation with Multi-task Promoting
Yuqing Cheng, Bo Chen, Fanjin Zhang, Jie Tang
https://arxiv.org/abs/2404.08322

BOND: Bootstrapping From-Scratch Name Disambiguation with Multi-task Promoting
From-scratch name disambiguation is an essential task for establishing a reliable foundation for academic platforms. It involves partitioning documents authored by identically named individuals into groups representing distinct real-life experts. Canonically, the process is divided into two decoupled tasks: locally estimating the pairwise similarities between documents followed by globally grouping these documents into appropriate clusters. However, such a decoupled approach often inhibits opti…

This https://arxiv.org/abs/2310.01496 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_…

The Cosmic Baryon Partition between the IGM and CGM in the SIMBA Simulations
We use the Simba suite of cosmological hydrodynamical simulations to investigate the importance of various stellar and AGN feedback mechanisms in partitioning the cosmic baryons between the intergalactic (IGM) and circumgalactic (CGM) media in the $z\leq 1$ Universe. We identify the AGN jets as the most prominent mechanism for the redistribution of baryons between the IGM and CGM. In contrast to the full feedback models, deactivating AGN jets results in $\approx20$ per cent drop in fraction of …

This https://arxiv.org/abs/2310.06096 has been replaced.
initial toot: https://mastoxiv.page/@ar…

Diagnosing tracer transport in convective penetration of a stably stratified layer
We use large-eddy simulations to study the penetration of a buoyant plume carrying a passive tracer into a stably stratified layer with constant buoyancy frequency. Using a buoyancy-tracer volume distribution, we develop a method for objectively partitioning buoyancy-tracer space into three regions, each of which corresponds to a coherent region in physical space. Specifically, we identify a source region where undiluted plume fluid enters the stratified layer, a transport region where much of …

AdaOper: Energy-efficient and Responsive Concurrent DNN Inference on Mobile Devices
Zheng Lin, Bin Guo, Sicong Liu, Wentao Zhou, Yasan Ding, Yu Zhang, Zhiwen Yu
https://arxiv.org/abs/2404.19209

AdaOper: Energy-efficient and Responsive Concurrent DNN Inference on Mobile Devices
Deep neural network (DNN) has driven extensive applications in mobile technology. However, for long-running mobile apps like voice assistants or video applications on smartphones, energy efficiency is critical for battery-powered devices. The rise of heterogeneous processors in mobile devices today has introduced new challenges for optimizing energy efficiency. Our key insight is that partitioning computations across different processors for parallelism and speedup doesn't necessarily correlate…

Semidefinite programming on population clustering: a local analysis
Shuheng Zhou
https://arxiv.org/abs/2403.12048 https://arxiv.org/p…

Semidefinite programming on population clustering: a local analysis
In this paper, we consider the problem of partitioning a small data sample of size $n$ drawn from a mixture of $2$ sub-gaussian distributions. In particular, we design and analyze two computational efficient algorithms to partition data into two groups approximately according to their population of origin given a small sample in a recent paper (Zhou 2023a). Our work is motivated by the application of clustering individuals according to their population of origin using markers, when the divergen…

The Fundamental Parameters of Astrophysical Plasma Turbulence and its Dissipation: Nonrelativistic Limit
Gregory G. Howes
https://arxiv.org/abs/2402.12829 …

The Fundamental Parameters of Astrophysical Plasma Turbulence and its Dissipation: Nonrelativistic Limit
A specific set of dimensionless plasma and turbulence parameters is introduced to characterize the nature of turbulence and its dissipation in weakly collisional space and astrophysical plasmas. Key considerations are discussed for the development of predictive models of the turbulent plasma heating that characterize the partitioning of dissipated turbulent energy between the ion and electron species and between the perpendicular and parallel degrees of freedom for each species. Identifying the…

This https://arxiv.org/abs/2105.03782 has been replaced.
link: https://scholar.google.com/scholar?q=a

Construction of Sparse Suffix Trees and LCE Indexes in Optimal Time and Space
The notions of synchronizing and partitioning sets are recently introduced variants of locally consistent parsings with great potential in problem-solving. In this paper we propose a deterministic algorithm that constructs for a given readonly string of length $n$ over the alphabet $\{0,1,\ldots,n^{\mathcal{O}(1)}\}$ a variant of $τ$-partitioning set with size $\mathcal{O}(b)$ and $τ= \frac{n}{b}$ using $\mathcal{O}(b)$ space and $\mathcal{O}(\frac{1}εn)$ time provided $b \ge n^ε$, for $ε>…

Strict Partitioning for Sporadic Rigid Gang Tasks
Binqi Sun, Tomasz Kloda, Marco Caccamo
https://arxiv.org/abs/2403.10726 https://arx…

Strict Partitioning for Sporadic Rigid Gang Tasks
The rigid gang task model is based on the idea of executing multiple threads simultaneously on a fixed number of processors to increase efficiency and performance. Although there is extensive literature on global rigid gang scheduling, partitioned approaches have several practical advantages (e.g., task isolation and reduced scheduling overheads). In this paper, we propose a new partitioned scheduling strategy for rigid gang tasks, named strict partitioning. The method creates disjoint partitio…

Neural Network-Based Piecewise Survival Models
Olov Holmer, Erik Frisk, Mattias Krysander
https://arxiv.org/abs/2403.18664 https://ar…

Neural Network-Based Piecewise Survival Models
In this paper, a family of neural network-based survival models is presented. The models are specified based on piecewise definitions of the hazard function and the density function on a partitioning of the time; both constant and linear piecewise definitions are presented, resulting in a family of four models. The models can be seen as an extension of the commonly used discrete-time and piecewise exponential models and thereby add flexibility to this set of standard models. Using a simulated d…

This https://arxiv.org/abs/2304.10268 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csCR_…

BackCache: Mitigating Contention-Based Cache Timing Attacks by Hiding Cache Line Evictions
Caches are used to reduce the speed differential between the CPU and memory to improve the performance of modern processors. However, attackers can use contention-based cache timing attacks to steal sensitive information from victim processes through carefully designed cache eviction sets. And L1 data cache attacks are widely exploited and pose a significant privacy and confidentiality threat. Existing hardware-based countermeasures mainly focus on cache partitioning, randomization, and cache l…

This https://arxiv.org/abs/2312.07808 has been replaced.
initial toot: https://mastoxiv.page/@…

A simplified Parisi Ansatz II: REM universality
In a previous work [A simplified Parisi Ansatz, Franchini, S., Commun. Theor. Phys., 73, 055601 (2021)] we introduced a simple method to compute the Random Overlap Structure of Aizenmann, Simm and Stars and the full-RSB Parisi formula for the Sherrington-Kirckpatrick Model without using replica theory. The method consists in partitioning the system into smaller sub-systems that we call layers, and iterate the Bayes rule. A central ansatz in our derivation was that these layers could be approxim…

Large-Scale RIS Enabled Air-Ground Channels: Near-Field Modeling and Analysis
Hao Jiang, Wangqi Shi, Zaichen Zhang, Cunhua Pan, Qingqing Wu, Feng Shu, Ruiqi Liu, Jiangzhou Wang
https://arxiv.org/abs/2403.12781

Large-Scale RIS Enabled Air-Ground Channels: Near-Field Modeling and Analysis
Existing works mainly rely on the far-field planar-wave-based channel model to assess the performance of reconfigurable intelligent surface (RIS)-enabled wireless communication systems. However, when the transmitter and receiver are in near-field ranges, this will result in relatively low computing accuracy. To tackle this challenge, we initially develop an analytical framework for sub-array partitioning. This framework divides the large-scale RIS array into multiple sub-arrays, effectively red…

Multirate Time-Integration based on Dynamic ODE Partitioning through Adaptively Refined Meshes for Compressible Fluid Dynamics
Daniel Doehring, Michael Schlottke-Lakemper, Gregor J. Gassner, Manuel Torrilhon
https://arxiv.org/abs/2403.05144

Multirate Time-Integration based on Dynamic ODE Partitioning through Adaptively Refined Meshes for Compressible Fluid Dynamics
In this paper, we apply the Paired-Explicit Runge-Kutta (P-ERK) schemes by Vermeire et. al. (2019, 2022) to dynamically partitioned systems arising from adaptive mesh refinement. The P-ERK schemes enable multirate time-integration with no changes in the spatial discretization methodology, making them readily implementable in existing codes that employ a method-of-lines approach. We show that speedup compared to a range of state of the art Runge-Kutta methods can be realized, despite additiona…

Simultaneous Conformal Prediction of Missing Outcomes with Propensity Score $\epsilon$-Discretization
Yonghoon Lee, Edgar Dobriban, Eric Tchetgen Tchetgen
https://arxiv.org/abs/2403.04613

Simultaneous Conformal Prediction of Missing Outcomes with Propensity Score $ε$-Discretization
We study the problem of simultaneous predictive inference on multiple outcomes missing at random. We consider a suite of possible simultaneous coverage properties, conditionally on the missingness pattern and on the -- possibly discretized/binned -- feature values. For data with discrete feature distributions, we develop a procedure which attains feature- and missingness-conditional coverage; and further improve it via pooling its results after partitioning the unobserved outcomes. To handle ge…

Bond Dipole Theory of Band Offset
Zeyu Jiang, Damien West, Shengbai Zhang
https://arxiv.org/abs/2403.05509 https://arxiv.org/pdf/2403…

Bond Dipole Theory of Band Offset
Understanding the band offset between materials is pivotal for electronic device functionality. While traditional theories attribute this offset solely to intrinsic properties of constituent materials, interfacial chemistry introduces complexities, including charge transfer dipoles. We address this challenge by defining a reference system based on Wigner-Seitz atoms, which is a charge partitioning that tessellates space while retaining bulk crystal symmetry. The interfacial dipole is then expre…

$L^p$ estimates of the maximal Schr\"odinger operator in $\mathbb R^n$
Xiumin Du, Jianhui Li
https://arxiv.org/abs/2404.10958 https://

$L^p$ estimates of the maximal Schrödinger operator in $\mathbb R^n$
We obtain $L^p$ estimates of the maximal Schrödinger operator in $\mathbb R^n$ using polynomial partitioning, bilinear refined Strichartz estimates, and weighted restriction estimates.

Efficient pore space characterization based on the curvature of the distance map
Ilan Ben-Noah, Juan J. Hidalgo, Marco Dentz
https://arxiv.org/abs/2403.12591

Efficient pore space characterization based on the curvature of the distance map
Media classification and the construction of pore network models from binary images of porous media hinges on accurately characterizing the pore space. We present an efficient method for (i) locating critical points, that is, pore body and throat centers, and (ii) partitioning of the pore space using information on the curvature of the distance map (DM) of the binary image. Specifically, we use the local maxima and minima of the determinant map of the Hessian matrix of the DM to locate the cent…

Wireless Distributed Matrix-Vector Multiplication using Over-the-Air Computation and Analog Coding
Jinho Choi
https://arxiv.org/abs/2402.11390 https://

Wireless Distributed Matrix-Vector Multiplication using Over-the-Air Computation and Analog Coding
In this paper, we propose an over-the-air (OTA)-based approach for distributed matrix-vector multiplications in the context of distributed machine learning (DML). Thanks to OTA computation, the column-wise partitioning of a large matrix enables efficient workload distribution among workers (i.e., local computing nodes) based on their computing capabilities. In addition, without requiring additional bandwidth, it allows the system to remain scalable even as the number of workers increases to mit…

This https://arxiv.org/abs/2310.01496 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_…

The Cosmic Baryon Partition between the IGM and CGM in the SIMBA Simulations
We use the Simba suite of cosmological hydrodynamical simulations to investigate the importance of various stellar and AGN feedback mechanisms in partitioning the cosmic baryons between the intergalactic (IGM) and circumgalactic (CGM) media in the $z\leq 1$ Universe. We identify the AGN jets as the most prominent mechanism for the redistribution of baryons between the IGM and CGM. In contrast to the full feedback models, deactivating AGN jets results in $\approx20$ per cent drop in fraction of …

This https://arxiv.org/abs/2310.17816 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_sta…

Local Discovery by Partitioning: Polynomial-Time Causal Discovery Around Exposure-Outcome Pairs
Causal discovery is crucial for causal inference in observational studies: it can enable the identification of valid adjustment sets (VAS) for unbiased effect estimation. However, global causal discovery is notoriously hard in the nonparametric setting, with exponential time and sample complexity in the worst case. To address this, we propose local discovery by partitioning (LDP), a novel nonparametric local discovery algorithm that is tailored for downstream inference tasks while avoiding the …

This https://arxiv.org/abs/2404.09835 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csCG_…

Hardness of Packing, Covering and Partitioning Simple Polygons with Unit Squares
We show that packing axis-aligned unit squares into a simple polygon $P$ is NP-hard, even when $P$ is an orthogonal and orthogonally convex polygon with half-integer coordinates. It has been known since the early 80s that packing unit squares into a polygon with holes is NP-hard~[Fowler, Paterson, Tanimoto, Inf. Process. Lett., 1981], but the version without holes was conjectured to be polynomial-time solvable more than two decades ago~[Baur and Fekete, Algorithmica, 2001]. Our reduction reli…

Chromatic number in $1.9999^n$ time? Fast deterministic set partitioning under the asymptotic rank conjecture
Andreas Bj\"orklund, Radu Curticapean, Thore Husfeldt, Petteri Kaski, Kevin Pratt
https://arxiv.org/abs/2404.04987

Chromatic number in $1.9999^n$ time? Fast deterministic set partitioning under the asymptotic rank conjecture
In this paper we further explore the recently discovered connection by Björklund and Kaski [STOC 2024] and Pratt [STOC 2024] between the asymptotic rank conjecture of Strassen [Progr. Math. 1994] and the three-way partitioning problem. We show that under the asymptotic rank conjecture, the chromatic number of an $n$-vertex graph can be computed deterministically in $O(1.99982^n)$ time, thus giving a conditional answer to a question of Zamir [ICALP 2021], and questioning the optimality of the $…

Building An Efficient Grid On GPU
Vasco Costa, Jo\~ao M. Pereira, Joaquim Jorge
https://arxiv.org/abs/2403.10647 https://arxiv.org/pd…

Building An Efficient Grid On GPU
Grid space partitioning is a technique to speed up queries to graphics databases. We present a parallel grid construction algorithm which can efficiently construct a structured grid on GPU hardware. Our approach is substantially faster than existing uniform grid construction algorithms, especially on non-homogeneous scenes. Indeed, it can populate a grid in real-time (at rates over 25 Hz), for architectural scenes with 10 million triangles.

Iterative distributed moving horizon estimation of linear systems with penalties on both system disturbances and noise
Xiaojie Li, Song Bo, Yan Qin, Xunyuan Yin
https://arxiv.org/abs/2404.06706

Iterative distributed moving horizon estimation of linear systems with penalties on both system disturbances and noise
In this paper, partition-based distributed state estimation of general linear systems is considered. A distributed moving horizon state estimation scheme is developed via decomposing the entire system model into subsystem models and partitioning the global objective function of centralized moving horizon estimation (MHE) into local objective functions. The subsystem estimators of the distributed scheme that are required to be executed iteratively within each sampling period are designed based o…

This https://arxiv.org/abs/2402.12829 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_…

The Fundamental Parameters of Astrophysical Plasma Turbulence and its Dissipation: Nonrelativistic Limit
A specific set of dimensionless plasma and turbulence parameters is introduced to characterize the nature of turbulence and its dissipation in weakly collisional space and astrophysical plasmas. Key considerations are discussed for the development of predictive models of the turbulent plasma heating that characterize the partitioning of dissipated turbulent energy between the ion and electron species and between the perpendicular and parallel degrees of freedom for each species. Identifying the…

PICO: Accelerating All k-Core Paradigms on GPU
Chen Zhao, Ting Yu, Zhigao Zheng, Song Jin, Jiawei Jiang, Bo Du, Dacheng Tao
https://arxiv.org/abs/2402.15253

PICO: Accelerating All k-Core Paradigms on GPU
Core decomposition is a well-established graph mining problem with various applications that involves partitioning the graph into hierarchical subgraphs. Solutions to this problem have been developed using both bottom-up and top-down approaches from the perspective of vertex convergence dependency. However, existing algorithms have not effectively harnessed GPU performance to expedite core decomposition, despite the growing need for enhanced performance. Moreover, approaching performance limita…

Accelerating Regular Path Queries over Graph Database with Processing-in-Memory
Ruoyan Ma, Shengan Zheng, Guifeng Wang, Jin Pu, Yifan Hua, Wentao Wang, Linpeng Huang
https://arxiv.org/abs/2403.10051

Accelerating Regular Path Queries over Graph Database with Processing-in-Memory
Regular path queries (RPQs) in graph databases are bottlenecked by the memory wall. Emerging processing-in-memory (PIM) technologies offer a promising solution to dispatch and execute path matching tasks in parallel within PIM modules. We present Moctopus, a PIM-based data management system for graph databases that supports efficient batch RPQs and graph updates. Moctopus employs a PIM-friendly dynamic graph partitioning algorithm, which tackles graph skewness and preserves graph locality with …

Chromatic number in $1.9999^n$ time? Fast deterministic set partitioning under the asymptotic rank conjecture
Andreas Bj\"orklund, Radu Curticapean, Thore Husfeldt, Petteri Kaski, Kevin Pratt
https://arxiv.org/abs/2404.04987

Chromatic number in $1.9999^n$ time? Fast deterministic set partitioning under the asymptotic rank conjecture
In this paper we further explore the recently discovered connection by Björklund and Kaski [STOC 2024] and Pratt [STOC 2024] between the asymptotic rank conjecture of Strassen [Progr. Math. 1994] and the three-way partitioning problem. We show that under the asymptotic rank conjecture, the chromatic number of an $n$-vertex graph can be computed deterministically in $O(1.99982^n)$ time, thus giving a conditional answer to a question of Zamir [ICALP 2021], and questioning the optimality of the $…

This https://arxiv.org/abs/2207.12653 has been replaced.
link: https://scholar.google.com/scholar?q=a

Incremental Measurement of Structural Entropy for Dynamic Graphs
Structural entropy is a metric that measures the amount of information embedded in graph structure data under a strategy of hierarchical abstracting. To measure the structural entropy of a dynamic graph, we need to decode the optimal encoding tree corresponding to the best community partitioning for each snapshot. However, the current methods do not support dynamic encoding tree updating and incremental structural entropy computation. To address this issue, we propose Incre-2dSE, a novel increm…

Exploiting CPU Clock Modulation for Covert Communication Channel
Shariful Alam, Jidong Xiao, Nasir U. Eisty
https://arxiv.org/abs/2404.05823 https://

Exploiting CPU Clock Modulation for Covert Communication Channel
Covert channel attacks represent a significant threat to system security, leveraging shared resources to clandestinely transmit information from highly secure systems, thereby violating the system's security policies. These attacks exploit shared resources as communication channels, necessitating resource partitioning and isolation techniques as countermeasures. However, mitigating attacks exploiting modern processors' hardware features to leak information is challenging because successful atta…

This https://arxiv.org/abs/2404.09835 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csCG_…

Hardness of Packing, Covering and Partitioning Simple Polygons with Unit Squares
We show that packing axis-aligned unit squares into a simple polygon $P$ is NP-hard, even when $P$ is an orthogonal and orthogonally convex polygon with half-integer coordinates. It has been known since the early 80s that packing unit squares into a polygon with holes is NP-hard~[Fowler, Paterson, Tanimoto, Inf. Process. Lett., 1981], but the version without holes was conjectured to be polynomial-time solvable more than two decades ago~[Baur and Fekete, Algorithmica, 2001]. Our reduction reli…

Building An Efficient Grid On GPU
Vasco Costa, Jo\~ao M. Pereira, Joaquim Jorge
https://arxiv.org/abs/2403.10647 https://arxiv.org/pd…

Building An Efficient Grid On GPU
Grid space partitioning is a technique to speed up queries to graphics databases. We present a parallel grid construction algorithm which can efficiently construct a structured grid on GPU hardware. Our approach is substantially faster than existing uniform grid construction algorithms, especially on non-homogeneous scenes. Indeed, it can populate a grid in real-time (at rates over 25 Hz), for architectural scenes with 10 million triangles.

This https://arxiv.org/abs/2404.10756 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_mat…

A High-Order Conservative Cut Finite Element Method for Problems in Time-Dependent Domains
A mass-conservative high-order unfitted finite element method for convection-diffusion equations in evolving domains is proposed. The space-time method presented in [P. Hansbo, M. G. Larson, S. Zahedi, Comput. Methods Appl. Mech. Engrg. 307 (2016)] is extended to naturally achieve mass conservation by utilizing Reynold's transport theorem. Furthermore, by partitioning the time-dependent domain into macroelements, a more efficient stabilization procedure for the cut finite element method in time…

This https://arxiv.org/abs/2403.08209 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csDS_…

Height-bounded Lempel-Ziv encodings
We introduce height-bounded LZ encodings (LZHB), a new family of compressed representations that are variants of Lempel-Ziv parsings with a focus on bounding the worst-case access time to arbitrary positions in the text directly via the compressed representation. An LZ-like encoding is a partitioning of the string into phrases of length $1$ which can be encoded literally, or phrases of length at least $2$ which have a previous occurrence in the string and can be encoded by its position and leng…

Flip Graphs of Pseudo-Triangulations With Face Degree at Most 4
Maarten L\"offler, Tamara Mchedlidze, David Orden, Josef Tkadlec, Jules Wulms
https://arxiv.org/abs/2402.12357

Flip Graphs of Pseudo-Triangulations With Face Degree at Most 4
A pseudo-triangle is a simple polygon with exactly three convex vertices, and all other vertices (if any) are distributed on three concave chains. A pseudo-triangulation~$\mathcal{T}$ of a point set~$P$ in~$\mathbb{R}^2$ is a partitioning of the convex hull of~$P$ into pseudo-triangles, such that the union of the vertices of the pseudo-triangles is exactly~$P$. We call a size-4 pseudo-triangle a dart. For a fixed $k\geq 1$, we study $k$-dart pseudo-triangulations ($k$-DPTs), that is, pseudo-tri…

This https://arxiv.org/abs/2403.08209 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csDS_…

Height-bounded Lempel-Ziv encodings
We introduce height-bounded LZ encodings (LZHB), a new family of compressed representations that are variants of Lempel-Ziv parsings with a focus on bounding the worst-case access time to arbitrary positions in the text directly via the compressed representation. An LZ-like encoding is a partitioning of the string into phrases of length $1$ which can be encoded literally, or phrases of length at least $2$ which have a previous occurrence in the string and can be encoded by its position and leng…

A divide-and-conquer approach for sparse recovery of high dimensional signals
Aron Bevelander, Kim Batselier, Nitin Jonathan Myers
https://arxiv.org/abs/2403.04688

A divide-and-conquer approach for sparse recovery of high dimensional signals
Compressed sensing (CS) techniques demand significant storage and computational resources, when recovering high-dimensional sparse signals. Block CS (BCS), a special class of CS, addresses both the storage and complexity issues by partitioning the sparse recovery problem into several sub-problems. In this paper, we derive a Welch bound-based guarantee on the reconstruction error with BCS. Our guarantee reveals that the reconstruction quality with BCS monotonically reduces with an increasing num…

This https://arxiv.org/abs/2403.00331 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csDC_…

WindGP: Efficient Graph Partitioning on Heterogenous Machines
Graph Partitioning is widely used in many real-world applications such as fraud detection and social network analysis, in order to enable the distributed graph computing on large graphs. However, existing works fail to balance the computation cost and communication cost on machines with different power (including computing capability, network bandwidth and memory size), as they only consider replication factor and neglect the difference of machines in realistic data centers. In this paper, we p…

This https://arxiv.org/abs/2403.02627 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csCG_…

Eight-Partitioning Points in 3D, and Efficiently Too
An \emph{eight-partition} of a finite set of points (respectively, of a continuous mass distribution) in $\mathbb{R}^3$ consists of three planes that divide the space into $8$ octants, such that each open octant contains at most $1/8$ of the points (respectively, of the mass). In 1966, Hadwiger showed that any mass distribution in $\mathbb{R}^3$ admits an eight-partition; moreover, one can prescribe the normal direction of one of the three planes. The analogous result for finite point sets foll…

This https://arxiv.org/abs/2310.15669 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_mat…

Robust Methods for Multiscale Coarse Approximations of Diffusion Models in Perforated Domains
For the Poisson equation posed in a domain containing a large number of polygonal perforations, we propose a low-dimensional coarse approximation space based on a coarse polygonal partitioning of the domain. Similarly to other multiscale numerical methods, this coarse space is spanned by locally discrete harmonic basis functions. Along the subdomain boundaries, the basis functions are piecewise polynomial. The main contribution of this article is an error estimate regarding the H1-projection ov…

Semialgebraic Range Stabbing, Ray Shooting, and Intersection Counting in the Plane
Timothy M. Chan, Pingan Cheng, Da Wei Zheng
https://arxiv.org/abs/2403.12303

Semialgebraic Range Stabbing, Ray Shooting, and Intersection Counting in the Plane
Polynomial partitioning techniques have recently led to improved geometric data structures for a variety of fundamental problems related to semialgebraic range searching and intersection searching in 3D and higher dimensions (e.g., see [Agarwal, Aronov, Ezra, and Zahl, SoCG 2019; Ezra and Sharir, SoCG 2021; Agarwal, Aronov, Ezra, Katz, and Sharir, SoCG 2022]). They have also led to improved algorithms for offline versions of semialgebraic range searching in 2D, via lens-cutting [Sharir and Zahl…

This https://arxiv.org/abs/2310.15669 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_mat…

Robust Methods for Multiscale Coarse Approximations of Diffusion Models in Perforated Domains
For the Poisson equation posed in a domain containing a large number of polygonal perforations, we propose a low-dimensional coarse approximation space based on a coarse polygonal partitioning of the domain. Similarly to other multiscale numerical methods, this coarse space is spanned by locally discrete harmonic basis functions. Along the subdomain boundaries, the basis functions are piecewise polynomial. The main contribution of this article is an error estimate regarding the H1-projection ov…

A High-Order Conservative Cut Finite Element Method for Problems in Time-Dependent Domains
Sebastian Myrb\"ack, Sara Zahedi
https://arxiv.org/abs/2404.10756

A High-Order Conservative Cut Finite Element Method for Problems in Time-Dependent Domains
A mass-conservative high-order unfitted finite element method for convection-diffusion equations in evolving domains is proposed. The space-time method presented in [P. Hansbo, M. G. Larson, S. Zahedi, Comput. Methods Appl. Mech. Engrg. 307 (2016)] is extended to naturally achieve mass conservation by utilizing Reynold's transport theorem. Furthermore, by partitioning the time-dependent domain into macroelements, a more efficient stabilization procedure for the cut finite element method in time…

A High-Order Conservative Cut Finite Element Method for Problems in Time-Dependent Domains
Sebastian Myrb\"ack, Sara Zahedi
https://arxiv.org/abs/2404.10756

A High-Order Conservative Cut Finite Element Method for Problems in Time-Dependent Domains
A mass-conservative high-order unfitted finite element method for convection-diffusion equations in evolving domains is proposed. The space-time method presented in [P. Hansbo, M. G. Larson, S. Zahedi, Comput. Methods Appl. Mech. Engrg. 307 (2016)] is extended to naturally achieve mass conservation by utilizing Reynold's transport theorem. Furthermore, by partitioning the time-dependent domain into macroelements, a more efficient stabilization procedure for the cut finite element method in time…

This https://arxiv.org/abs/2311.15639 has been replaced.
link: https://scholar.google.com/scholar?q=a

On Approximating Cutwidth and Pathwidth
We study graph ordering problems with a min-max objective. A classical problem of this type is cutwidth, where given a graph we want to order its vertices such that the number of edges crossing any point is minimized. We give a $ \log^{1+o(1)}(n)$ approximation for the problem, substantially improving upon the previous poly-logarithmic guarantees based on the standard recursive balanced partitioning approach of Leighton and Rao (FOCS'88). Our key idea is a new metric decomposition procedure tha…

This https://arxiv.org/abs/2210.01954 has been replaced.
link: https://scholar.google.com/scholar?q=a

Ruler Rolling
At CCCG '21 O'Rourke proposed a variant of Hopcroft, Josephs and Whitesides' (1985) NP-complete problem {\sc Ruler Folding}, which he called {\sc Ruler Wrapping} and for which all folds must be 180 degrees in the same direction. Gagie, Saeidi and Sapucaia (2023) noted that if the last straight section of the ruler must be longest, then {\sc Ruler Wrapping} is equivalent to partitioning a string of positive integers into substrings whose sums are increasing such that the last substring sums to a…

This https://arxiv.org/abs/2403.00121 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_mat…

On the Optimality of CVOD-based Column Selection
While there exists a rich array of matrix column subset selection problem (CSSP) algorithms for use with interpolative and CUR-type decompositions, their use can often become prohibitive as the size of the input matrix increases. In an effort to address these issues, the authors in \cite{emelianenko2024adaptive} developed a general framework that pairs a column-partitioning routine with a column-selection algorithm. Two of the four algorithms presented in that work paired the Centroidal Voronoi…