Tootfinder

Singapore-based SingleInterface, which helps offline businesses manage and grow their online presence, raised $30M, its first external raise since 2015 founding (Jagmeet Singh/TechCrunch)
https://techcrunch.com/2024/04/03/singleinterface-funding-digital…

SaaS startup SingleInterface raises $30M to help more businesses get online | TechCrunch
SingleInterface, a SaaS startup offering tools to offline businesses to get online, has raised $30 million in its maiden fundraising round.

Efficient Interaction-Based Offline Runtime Verification of Distributed Systems with Lifeline Removal
Erwan Mahe, Boutheina Bannour, Christophe Gaston, Pascale Le Gall
https://arxiv.org/abs/2403.03057

Efficient Interaction-Based Offline Runtime Verification of Distributed Systems with Lifeline Removal
Runtime Verification (RV) refers to a family of techniques in which system executions are observed and confronted to formal specifications, with the aim of identifying faults. In Offline RV, observation is done in a first step and verification in a second, on a static artifact collected during observation. In this paper, we define an approach to offline RV of Distributed Systems (DS) against interactions. Interactions are formal models describing communications within a DS. DS are composed of s…

baseball: Baseball steroid use (2008)
Two networks representing steroid use among baseball players. First, a bipartite network of players and their steroid providers (of illegal performance-enhancing substances). Second, a one-mode projection of players, which are linked if they have a common supplier.
This network has 72 nodes and 1089 edges.
Tags: Social, Offline, Weighted, Projection

This https://arxiv.org/abs/2309.06174 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_mat…

Relating Electric Vehicle Charging to Speed Scaling with Job-Specific Speed Limits
Due to the ongoing electrification of transport in combination with limited power grid capacities, efficient ways to schedule the charging of electric vehicles (EVs) are needed for the operation of, for example, large parking lots. Common approaches such as model predictive control repeatedly solve a corresponding offline problem. In this work, we first present and analyze the Flow-based Offline Charging Scheduler (FOCS), an offline algorithm to derive an optimal EV charging schedule for a flee…

Offline, The Podcast
Great Australian Pods Podcast Directory: #GreatAusPods

Offline | Great Australian Pods Podcast Directory
Podcast: Offline, The Podcast Host: Alison Rice Category: Religion & Spirituality Sub-Category: Self-Improvement & Advice, Spirituality First Episode: 2018 Hosted by one of Australia’s most in-demand…

baseball: Baseball steroid use (2008)
Two networks representing steroid use among baseball players. First, a bipartite network of players and their steroid providers (of illegal performance-enhancing substances). Second, a one-mode projection of players, which are linked if they have a common supplier.
This network has 72 nodes and 1089 edges.
Tags: Social, Offline, Weighted, Projection

This https://arxiv.org/abs/2310.03239 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csRO_…

Roadmaps with Gaps over Controllers: Achieving Efficiency in Planning under Dynamics
This paper aims to improve the computational efficiency of motion planning for mobile robots with non-trivial dynamics through the use of learned controllers. It adopts a decoupled strategy, where a system-specific controller is first trained offline in an empty environment to deal with the robot's dynamics. For a target environment, the proposed approach constructs offline a data structure, a "Roadmap with Gaps," to approximately learn how to solve planning queries in this environment using th…

This https://arxiv.org/abs/2307.08669 has been replaced.
link: https://scholar.google.com/scholar?q=a

Leveraging Recommender Systems to Reduce Content Gaps on Peer Production Platforms
Peer production platforms like Wikipedia commonly suffer from content gaps. Prior research suggests recommender systems can help solve this problem, by guiding editors towards underrepresented topics. However, it remains unclear whether this approach would result in less relevant recommendations, leading to reduced overall engagement with recommended items. To answer this question, we first conducted offline analyses (Study 1) on SuggestBot, a task-routing recommender system for Wikipedia, then…

Conjectural Online Learning with First-order Beliefs in Asymmetric Information Stochastic Games
Tao Li, Kim Hammar, Rolf Stadler, Quanyan Zhu
https://arxiv.org/abs/2402.18781

Conjectural Online Learning with First-order Beliefs in Asymmetric Information Stochastic Games
Stochastic games arise in many complex socio-technical systems, such as cyber-physical systems and IT infrastructures, where information asymmetry presents challenges for decision-making entities (players). Existing computational methods for asymmetric information stochastic games (AISG) are primarily offline, targeting special classes of AISGs to avoid belief hierarchies, and lack online adaptability to deviations from equilibrium. To address this limitation, we propose a conjectural online le…

Nonlinear identification algorithm for online and offline study of pulmonary mechanical ventilation
Diego A. Riva, Carolina A. Evangelista, Paul F. Puleston, Luis Corsiglia, Nahuel Dargains
https://arxiv.org/abs/2402.18709

Nonlinear identification algorithm for online and offline study of pulmonary mechanical ventilation
This work presents an algorithm for determining the parameters of a nonlinear dynamic model of the respiratory system in patients undergoing assisted ventilation. Using the pressure and flow signals measured at the mouth, the model's quadratic pressure-volume characteristic is fit to this data in each respiratory cycle by appropriate estimates of the model parameters. Parameter changes during ventilation can thus also be detected. The algorithm is first refined and assessed using data derived f…

Continual Offline Reinforcement Learning via Diffusion-based Dual Generative Replay
Jinmei Liu, Wenbin Li, Xiangyu Yue, Shilin Zhang, Chunlin Chen, Zhi Wang
https://arxiv.org/abs/2404.10662

Continual Offline Reinforcement Learning via Diffusion-based Dual Generative Replay
We study continual offline reinforcement learning, a practical paradigm that facilitates forward transfer and mitigates catastrophic forgetting to tackle sequential offline tasks. We propose a dual generative replay framework that retains previous knowledge by concurrent replay of generated pseudo-data. First, we decouple the continual learning policy into a diffusion-based generative behavior model and a multi-head action evaluation model, allowing the policy to inherit distributional expressi…

This https://arxiv.org/abs/2310.03239 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csRO_…

Roadmaps with Gaps over Controllers: Achieving Efficiency in Planning under Dynamics
This paper aims to improve the computational efficiency of motion planning for mobile robots with non-trivial dynamics through the use of learned controllers. It adopts a decoupled strategy, where a system-specific controller is first trained offline in an empty environment to deal with the robot's dynamics. For a target environment, the proposed approach constructs offline a data structure, a "Roadmap with Gaps," to approximately learn how to solve planning queries in this environment using th…

Normal people: using one #map app.
Me: using up to five apps:
1. MapFactor Navigator — with offline maps based on #OpenStreetMap.
#Android

Offline tagging of radon-induced backgrounds in XENON1T and applicability to other liquid xenon detectors
E. Aprile, J. Aalbers, K. Abe, S. Ahmed Maouloud, L. Althueser, B. Andrieu, E. Angelino, J. R. Angevaare, D. Ant\'on Martin, F. Arneodo, L. Baudis, A. L. Baxter, M. Bazyk, L. Bellagamba, R. Biondi, A. Bismark, E. J. Brookes, A. Brown, G. Bruno, R. Budnik, T. K. Bui, J. M. R. Cardoso, A. P. Cimental Chavez, A. P. Colijn, J. Conrad, J. J. Cuenca-Garc\'ia, V. D'Andrea, L. …

Offline tagging of radon-induced backgrounds in XENON1T and applicability to other liquid xenon detectors
This paper details the first application of a software tagging algorithm to reduce radon-induced backgrounds in liquid noble element time projection chambers, such as XENON1T and XENONnT. The convection velocity field in XENON1T was mapped out using $^{222}\text{Rn}$ and $^{218}\text{Po}$ events, and the root-mean-square convection speed was measured to be $0.30 \pm 0.01$ cm/s. Given this velocity field, $^{214}\text{Pb}$ background events can be tagged when they are followed by $^{214}\text{Bi…

This https://arxiv.org/abs/2306.03111 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_qbi…

Bootstrapped Training of Score-Conditioned Generator for Offline Design of Biological Sequences
We study the problem of optimizing biological sequences, e.g., proteins, DNA, and RNA, to maximize a black-box score function that is only evaluated in an offline dataset. We propose a novel solution, bootstrapped training of score-conditioned generator (BootGen) algorithm. Our algorithm repeats a two-stage process. In the first stage, our algorithm trains the biological sequence generator with rank-based weights to enhance the accuracy of sequence generation based on high scores. The subsequen…

Offline tagging of radon-induced backgrounds in XENON1T and applicability to other liquid xenon detectors
E. Aprile, J. Aalbers, K. Abe, S. Ahmed Maouloud, L. Althueser, B. Andrieu, E. Angelino, J. R. Angevaare, D. Ant\'on Martin, F. Arneodo, L. Baudis, A. L. Baxter, M. Bazyk, L. Bellagamba, R. Biondi, A. Bismark, E. J. Brookes, A. Brown, G. Bruno, R. Budnik, T. K. Bui, J. M. R. Cardoso, A. P. Cimental Chavez, A. P. Colijn, J. Conrad, J. J. Cuenca-Garc\'ia, V. D'Andrea, L. …

Offline tagging of radon-induced backgrounds in XENON1T and applicability to other liquid xenon detectors
This paper details the first application of a software tagging algorithm to reduce radon-induced backgrounds in liquid noble element time projection chambers, such as XENON1T and XENONnT. The convection velocity field in XENON1T was mapped out using $^{222}\text{Rn}$ and $^{218}\text{Po}$ events, and the root-mean-square convection speed was measured to be $0.30 \pm 0.01$ cm/s. Given this velocity field, $^{214}\text{Pb}$ background events can be tagged when they are followed by $^{214}\text{Bi…

A New Hotplug Coded Caching Scheme Using PDAs
Mallikharjuna Chinnapadamala, Charul Rajput, B. Sundar Rajan
https://arxiv.org/abs/2404.06433 https://…

A New Hotplug Coded Caching Scheme Using PDAs
In the original coded caching model introduced by Maddah-Ali and Niesen in 2014, the server starts broadcasting only after it receives demands from all the users. So, all the users must be active during the delivery phase. In this work, we consider a coded caching model called hotplug coded caching in which some of the users are offline during the delivery phase. This model was first introduced by Ma and Tuninetti (``On Coded Caching Systems with Offline Users," 2022 IEEE International Symposiu…

This https://arxiv.org/abs/2306.03111 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_qbi…

Bootstrapped Training of Score-Conditioned Generator for Offline Design of Biological Sequences
We study the problem of optimizing biological sequences, e.g., proteins, DNA, and RNA, to maximize a black-box score function that is only evaluated in an offline dataset. We propose a novel solution, bootstrapped training of score-conditioned generator (BootGen) algorithm. Our algorithm repeats a two-stage process. In the first stage, our algorithm trains the biological sequence generator with rank-based weights to enhance the accuracy of sequence generation based on high scores. The subsequen…

baseball: Baseball steroid use (2008)
Two networks representing steroid use among baseball players. First, a bipartite network of players and their steroid providers (of illegal performance-enhancing substances). Second, a one-mode projection of players, which are linked if they have a common supplier.
This network has 72 nodes and 1089 edges.
Tags: Social, Offline, Weighted, Projection

DITTO: Demonstration Imitation by Trajectory Transformation
Nick Heppert, Max Argus, Tim Welschehold, Thomas Brox, Abhinav Valada
https://arxiv.org/abs/2403.15203

DITTO: Demonstration Imitation by Trajectory Transformation
Teaching robots new skills quickly and conveniently is crucial for the broader adoption of robotic systems. In this work, we address the problem of one-shot imitation from a single human demonstration, given by an RGB-D video recording through a two-stage process. In the first stage which is offline, we extract the trajectory of the demonstration. This entails segmenting manipulated objects and determining their relative motion in relation to secondary objects such as containers. Subsequently, …

This https://arxiv.org/abs/2401.14871 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_mat…

Data-Enabled Policy Optimization for Direct Adaptive Learning of the LQR
Direct data-driven design methods for the linear quadratic regulator (LQR) mainly use offline or episodic data batches, and their online adaptation has been acknowledged as an open problem. In this paper, we propose a direct adaptive method to learn the LQR from online closed-loop data. First, we propose a new policy parameterization based on the sample covariance to formulate a direct data-driven LQR problem, which is shown to be equivalent to the certainty-equivalence LQR with optimal non-asy…

baseball: Baseball steroid use (2008)
Two networks representing steroid use among baseball players. First, a bipartite network of players and their steroid providers (of illegal performance-enhancing substances). Second, a one-mode projection of players, which are linked if they have a common supplier.
This network has 72 nodes and 1089 edges.
Tags: Social, Offline, Weighted, Projection

baseball: Baseball steroid use (2008)
Two networks representing steroid use among baseball players. First, a bipartite network of players and their steroid providers (of illegal performance-enhancing substances). Second, a one-mode projection of players, which are linked if they have a common supplier.
This network has 72 nodes and 1089 edges.
Tags: Social, Offline, Weighted, Projection

CATSE: A Context-Aware Framework for Causal Target Sound Extraction
Shrishail Baligar, Mikolaj Kegler, Bryce Irvin, Marko Stamenovic, Shawn Newsam
https://arxiv.org/abs/2403.14246

CATSE: A Context-Aware Framework for Causal Target Sound Extraction
Target Sound Extraction (TSE) focuses on the problem of separating sources of interest, indicated by a user's cue, from the input mixture. Most existing solutions operate in an offline fashion and are not suited to the low-latency causal processing constraints imposed by applications in live-streamed content such as augmented hearing. We introduce a family of context-aware low-latency causal TSE models suitable for real-time processing. First, we explore the utility of context by providing the …

This https://arxiv.org/abs/2402.18781 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csGT_…

Conjectural Online Learning with First-order Beliefs in Asymmetric Information Stochastic Games
Stochastic games arise in many complex socio-technical systems, such as cyber-physical systems and IT infrastructures, where information asymmetry presents challenges for decision-making entities (players). Existing computational methods for asymmetric information stochastic games (AISG) are primarily offline, targeting special classes of AISGs to avoid belief hierarchies, and lack online adaptability to deviations from equilibrium. To address this limitation, we propose a conjectural online le…

This https://arxiv.org/abs/2307.08669 has been replaced.
link: https://scholar.google.com/scholar?q=a

Leveraging Recommender Systems to Reduce Content Gaps on Peer Production Platforms
Peer production platforms like Wikipedia commonly suffer from content gaps. Prior research suggests recommender systems can help solve this problem, by guiding editors towards underrepresented topics. However, it remains unclear whether this approach would result in less relevant recommendations, leading to reduced overall engagement with recommended items. To answer this question, we first conducted offline analyses (Study 1) on SuggestBot, a task-routing recommender system for Wikipedia, then…

baseball: Baseball steroid use (2008)
Two networks representing steroid use among baseball players. First, a bipartite network of players and their steroid providers (of illegal performance-enhancing substances). Second, a one-mode projection of players, which are linked if they have a common supplier.
This network has 72 nodes and 1089 edges.
Tags: Social, Offline, Weighted, Projection

baseball: Baseball steroid use (2008)
Two networks representing steroid use among baseball players. First, a bipartite network of players and their steroid providers (of illegal performance-enhancing substances). Second, a one-mode projection of players, which are linked if they have a common supplier.
This network has 72 nodes and 1089 edges.
Tags: Social, Offline, Weighted, Projection