Tootfinder

Spent my nervous energy preparing for the #nyc #heatwave making myself a wool coozie for my tall cans.
Check on your friends, family, and neighbors.
Designate a cool room in your home — no need to cool the whole house with a/c. Draw your shades/blinds.
Take it easy outside. Have a non electric plan for cooling down (cool shower/pool/ spray cap in a park or hydrant— fans — cool drink).
https://finder.nyc.gov/coolingcenters/

On polluted bootstrap percolation in Cartesian grids
Bo\v{s}tjan Bre\v{s}ar, Jaka Hed\v{z}et, Michael A. Henning
https://arxiv.org/abs/2506.18345 https://

On polluted bootstrap percolation in Cartesian grids
Given a graph $G$ and assuming that some vertices of $G$ are infected, the $r$-neighbor bootstrap percolation rule makes an uninfected vertex $v$ infected if $v$ has at least $r$ infected neighbors. The $r$-percolation number, $m(G, r)$, of $G$ is the minimum cardinality of a set of initially infected vertices in $G$ such that after continuously performing the $r$-neighbor bootstrap percolation rule each vertex of $G$ eventually becomes infected. In this paper, we continue the study of polluted…

Throughput in inhomogeneous planar drainage networks
Partha Pratim Ghosh, Benedikt Jahnel, Yannic Steenbeck
https://arxiv.org/abs/2506.18132 https://

Throughput in inhomogeneous planar drainage networks
We consider navigation schemes on planar diluted lattices and semi lattices with one discrete and one continuous component. More precisely, nodes that survive inhomogeneous Bernoulli site percolation, or are placed as inhomogeneous Poisson points on shifted copies of $\mathbb{Z}$, forward their individually generated traffic to their respective closest neighbors to the left in the next layer. The resulting drainage network is a tree and we study the amount of traffic that goes through an increa…

Take action in your community to help save Medicaid.
If you’re in a swing district or state, use our simple Neighbor2Neighbor tool to get a list of like-minded neighbors,
knock on their doors and talk to them about stopping the monstrous GOP megabill:
https://indivisiblepr…

#Facebook front office grabbed great publicity from its bold #billion dollar public #pledge to help solve the #BayArea

Here’s where the money Meta spent on its $1 billion pledge for affordable housing has gone
Executives at Facebook’s parent company in 2022 stopped committing funding to the initiative, slowing progress.

Our Revolution here.
It's crunch time in Congress
- Trump's budget, Iran, & oligarch money in politics.
Join the Virtual Lobby Training this Sun 6/22
at 7pm ET (4pm PT).
Our Revolution's DC team is facilitating virtual lobby visits with Capitol Hill offices
and we need your help.
Join and get trained up to speak directly with DC offices via Zoom.
RSVP now
👉

Our Revolution Virtual Lobby Training
Our Revolution Virtual Lobby Training Your elected officials in Congress need to hear from you to build support for progressive policies and make democracy work for the many! Come learn about Our Revolution’s virtual lobby model, how you can get involved, and opportunities to join your neighbors to meet with your Senators and Representatives. Event Details: Date: Sunday, June 22, 2025 Time: 7pm ET (4pm PT) Location: Virtual Training - Zoom Link

Oldies but Goldies: The Potential of Character N-grams for Romanian Texts
Dana Lupsa, Sanda-Maria Avram
https://arxiv.org/abs/2506.15650 https://

Oldies but Goldies: The Potential of Character N-grams for Romanian Texts
This study addresses the problem of authorship attribution for Romanian texts using the ROST corpus, a standard benchmark in the field. We systematically evaluate six machine learning techniques: Support Vector Machine (SVM), Logistic Regression (LR), k-Nearest Neighbors (k-NN), Decision Trees (DT), Random Forests (RF), and Artificial Neural Networks (ANN), employing character n-gram features for classification. Among these, the ANN model achieved the highest performance, including perfect clas…

After some neighbors say they want to be able to drive cars in cycletrack, DC govt replaces it with painted lanes & says basis for action was aesthetics of flexposts.
If the problem is really that flexposts don't look nice, why not replace them with decorative bollards?
https://wapo.st/4dXmJY1

D.C. is removing bike lane barriers for the first time, calling them ugly
The move comes as political leaders across the country begin reversing and undoing bike lane plans.

Inward and Outward Spillover Effects of One Unit's Treatment on Network Neighbors under Partial Interference
Fei Fang, Edoardo M Airoldi, Laura Forastiere
https://arxiv.org/abs/2506.06615

Inward and Outward Spillover Effects of One Unit's Treatment on Network Neighbors under Partial Interference
In settings where interference is present, direct effects are commonly defined as the average effect of a unit's treatment on their own outcome while fixing the treatment status or probability among interfering units, and spillover effects measure the average effect of a change in the latter while the individual's treatment status is kept fixed. Here, we define the average causal effect of a unit's treatment status on the outcome of their network neighbors, while fixing the treatment probabilit…

So uh, no 6 or 7 on my block for a bit.

Repeat it like a broken record, tell your friends and neighbors who are not Extremely Online and are not getting these firsthand reports:
The only people who were violent were ICE and the police.
The only people who were violent were ICE and the police.
The only people who were violent were ICE and the police.

„The protesters throwing rocks at heavily armed security forces or attempting to damage the vehicles used to kidnap their immigrant neighbors did not introduce violence. They are instead acting in militant community defense.“
From: @…

I have my share of issues with Parkrose Permaculture, but she has a lot of things I do strongly agree with. I can't stress enough that you never dehumanize your enemies. You can respond appropriately to violence. You can defend yourself from them by any means necessary. But you do not dehumanize them. You always limit your response to the minimum necessary to defend yourself.
There are a number of former Nazi skins who became antifascists after realizing they were wrong. Those folks tend to be some of the most dedicated because they feel a debt, and some of the most knowledgeable because they were there. Coming out of these types of cults, police included, is hard and takes time. A lot of us don't have the ability to work with them. But some do.
By repeatedly humanizing your opponent, you can break some of them. The #Seattle Police Department was not defunded but saw a massive reduction in numbers because their morale was destroyed. Some people will never change. Some people are broken and feel like they need the power. But if you change one person's mind, even give them something to think about, it's a crack. If even one cop quits, that's one less trained gun pointed at you in the future.
The 18 year old marines and federalized national guard troops out there are literally kids. A lot of them came from poor communities. They are being used in a way they haven't been trained to do, doing things they (should) have been told are not legal. They joined to get out of poverty, to go to college, or to "defend the American people" (regardless of how misguided that is). Few, if any, of them joined to abuse people. They will be especially open to persuasion.
Remind those troops that they are carrying out illegal orders, that they are being called on to violate their oath to protect the constitution, that they are suppressing the free speech of the fellow Americans they swore to defend. Remind them that the people they could be illegally arresting now are just like their parents, their neighbors, their families, the friends who didn't join. Remind them that this is the first step. They will be called on to kill Americans if they let this keep going.
Remind them ICE sleeps in hotels while they sleep on the ground. Remind them that their drunk and incompetent leadership thinks of them as disposable tools. Remind them that some of these people are out protesting *for them* against cuts to the VA and other services. Remind them that the people they're defending refuse to make college free so they can recruit from poor schools. Remind them that they will always be welcome when they're ready to join the side of freedom and justice.
When you dehumanize your enemies, you unify them. When you humanize your enemies, you can divide them. There is no weapon available to us right now so powerful as compassion.
https://youtu.be/YtWOYUDMsBw

That's a first: I ordered & paid shorts from Nike, delivered by DPD as “will be deposited without ringing.” OK, there is a box at our mailbox and the parcel should fit. I get the notification “parcel delivered.” An hour later partner looks for it—nothing. Not in our box, not in one of the neighbors, not in the hallway, nothing. DPD sends a picture with our box and the parcel. So at least it was there once. But where is it now? Never before someone stole sth from this box. So the driv…

#UpliftMoment
This morning I learned the Soup Kitchen in my #nyc neighborhood was $50k in the hole bc of fed grant cancellations
By midday I learned the entire neighborhood was throwing a fundraising party to feed mouthes uptown
This evening 100s of neighbors danced to Caribbean music & raised ❤️❤️&💰💰
#NeighborsHelpingNeighbors

Approximations for Fault-Tolerant Total and Partial Positive Influence Domination
Ioannis Lamprou, Ioannis Sigalas, Ioannis Vaxevanakis, Vassilis Zissimopoulos
https://arxiv.org/abs/2506.12828

Approximations for Fault-Tolerant Total and Partial Positive Influence Domination
In $\textit{total domination}$, given a graph $G=(V,E)$, we seek a minimum-size set of nodes $S\subseteq V$, such that every node in $V$ has at least one neighbor in $S$. We define a $\textit{fault-tolerant}$ version of total domination, where we require any node in $V \setminus S$ to have at least $m$ neighbors in $S$. Let $Δ$ denote the maximum degree in $G$. We prove a first $1 + \ln(Δ+ m - 1)$ approximation for fault-tolerant total domination. We also consider fault-tolerant variants of t…

High Probability Convergence of Distributed Clipped Stochastic Gradient Descent with Heavy-tailed Noise
Yuchen Yang, Kaihong Lu, Long Wang
https://arxiv.org/abs/2506.11647

High Probability Convergence of Distributed Clipped Stochastic Gradient Descent with Heavy-tailed Noise
In this paper, the problem of distributed optimization is studied via a network of agents. Each agent only has access to a noisy gradient of its own objective function, and can communicate with its neighbors via a network. To handle this problem, a distributed clipped stochastic gradient descent algorithm is proposed, and the high probability convergence of the algorithm is studied. Existing works on distributed algorithms involving stochastic gradients only consider the light-tailed noises. Di…

This is so out of touch. ICE is ambushing and kidnapping our neighbors and we're going to "cover the entire city with drones"? The SFBOS should reject this "gift"
https://missionlocal.org/2025/06/were-

‘We’re going to be covering the entire city with drones’: Billionaire’s donation to SFPD accepted
San Francisco police commission accepts tech billionaire's gift, to provide cops with drones, cameras and a massive new office

My neighbors stood up to ICE. What they did next shows why California politics makes no sense (Sara Libby/San Francisco Chronicle)
https://www.sfchronicle.com/opinion/article/ice-immigration-san-diego-20358933.php
http://www.memeorandum.com/250605/p76#a250605p76

Have been watching Your Friends and Neighbors on #AppleTVPlus . No masterpiece, and somehow fairly annoying, but still somehow I want to watch all of it. I often find myself fast-forwarding through boring bits, though.

Dynamic Evolution of Cooperation Based on Adaptive Reputation Threshold and Game Transition
Hongyu Yue, Xiaojin Xiong, Minyu Feng, Attila Szolnoki
https://arxiv.org/abs/2506.13319

Dynamic Evolution of Cooperation Based on Adaptive Reputation Threshold and Game Transition
In real-world social systems, individual interactions are frequently shaped by reputation, which not only influences partner selection but also affects the nature and benefits of the interactions themselves. We propose a heterogeneous game transition model that incorporates a reputation-based dynamic threshold mechanism to investigate how reputation regulates game evolution. In our framework, individuals determine the type of game they engage in according to their own and their neighbors' reput…

After some neighbors say they want to be able to drive cars in cycletrack, DC govt replaces it with painted lanes & says basis for action was aesthetics of flexposts.
If the problem is really that flexposts don't look nice, why not replace them with decorative bollards?
https://wapo.st/4dXmJY1

I wish my neighbors would have sex more loudly.

If an "undercover" officer is seen and known to the press then I would not hesitate to publish their face image and identity - in part because they have failed actually be "undercover".
That said, the fact that agents can't be identified as actual Federal agents, much less identified down to the individual actor when they do ill, is simply unacceptable.
TSA at least has numbers on their "name" badges, so one can make a complaint about a person …

The ICE agents disappearing your neighbors would like a little privacy, please
After taking four people into custody at SF’s immigration court, ICE wanted The Standard to conceal agents’ faces.

What Really is a Member? Discrediting Membership Inference via Poisoning
Neal Mangaokar, Ashish Hooda, Zhuohang Li, Bradley A. Malin, Kassem Fawaz, Somesh Jha, Atul Prakash, Amrita Roy Chowdhury
https://arxiv.org/abs/2506.06003

What Really is a Member? Discrediting Membership Inference via Poisoning
Membership inference tests aim to determine whether a particular data point was included in a language model's training set. However, recent works have shown that such tests often fail under the strict definition of membership based on exact matching, and have suggested relaxing this definition to include semantic neighbors as members as well. In this work, we show that membership inference tests are still unreliable under this relaxation - it is possible to poison the training dataset in a way…

WOW! Looked at the local nextdoor site and noticed someone was asking where the local No Kings protest was going to be held at. It appears almost all my neighbors are trumpist as almost every reply was hate filled. With one telling the lady if he had his way he would march her to the shoreline and give her a choice. Swim to Mexico or a bullet to the back of the head. Reported it of course but I know who it is.
Can't wait for the next time he walks his dog and it craps on my yard an…

Adaptive Tetrahedral Grids for Volumetric Path-Tracing
Anis Benyoub, Jonathan Dupuy
https://arxiv.org/abs/2506.11510 https://arxiv.or…

Adaptive Tetrahedral Grids for Volumetric Path-Tracing
We advertise the use of tetrahedral grids constructed via the longest edge bisection algorithm for rendering volumetric data with path tracing. The key benefits of such grids is two-fold. First, they provide a highly adaptive space-partitioning representation that limits the memory footprint of volumetric assets. Second, each (tetrahedral) cell has exactly 4 neighbors within the volume (one per face of each tetrahedron) or less at boundaries. We leverage these properties to devise optimized alg…

I do not understand why folks aren’t mildly freaking out on the extended forecasts for #NYC
Seriously #HeatWave
To have five days (!!!5 days !!!) of over 100degF
Check on your neighbors.
Prepare now for no or low power. Get your spritzer and battery powered electric fans.
We will get through this together. But it will be easier with a little bit of planning.
Where is your NYC cooling center??
https://finder.nyc.gov/coolingcenters/

Extending the Affirmative Action Problem: mixing numbers and integrated colorings of graphs
Charles Burnette, Broden Caton, Olivia Coward, Julian Davis, Austin Teter
https://arxiv.org/abs/2506.07192

Extending the Affirmative Action Problem: mixing numbers and integrated colorings of graphs
Consider a graph whose vertices are colored in one of two colors, say black or white. A white vertex is called integrated if it has at least as many black neighbors as white neighbors, and similarly for a black vertex. The coloring as a whole is integrated if every vertex is integrated. A classic exercise in graph theory, known as the Affirmative Action Problem, is to prove that every finite simple graph admits an integrated coloring. The solution can be neatly summarized with the one-liner: "m…

This https://arxiv.org/abs/2506.03437 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csIR_…

Quake: Adaptive Indexing for Vector Search
Vector search, the task of finding the k-nearest neighbors of high-dimensional vectors, underpins many machine learning applications, including recommendation systems and information retrieval. However, existing approximate nearest neighbor (ANN) methods perform poorly under dynamic, skewed workloads where data distributions evolve. We introduce Quake, an adaptive indexing system that maintains low latency and high recall in such environments. Quake employs a hierarchical partitioning scheme th…

Rep. Emily Randall of Washington's 6th congressional district via FB (link to SeaTimes in 2/2):
"The American people are being told one thing, but my eyes saw another: the people inside this facility are our neighbors, people who we would see in the community, parents, and siblings. We spoke with a legal permanent resident who is being detained on a 20 year old crime for which he served his time." 1/2

Temperature-Noise Interplay in a Coupled Model of Opinion Dynamics
Anna Chmiel, Julian Sienkiewicz
https://arxiv.org/abs/2506.07680 https://

Temperature-Noise Interplay in a Coupled Model of Opinion Dynamics
We consider a coupled system mimicking opinion formation under the influence of a group of $q$ neighbors ($q$-lobby) that consists of an Ising part governed by temperature-like parameter $T$ and a voter dynamics parameterized by noise probability $p$ (independence of choice). Using rigorous analytical calculations backed by extensive Monte Carlo simulations, we examine the interplay between these two quantities. Based on the theory of phase transitions, we derive the relation between $T$ and $p…

Training-Free Query Optimization via LLM-Based Plan Similarity
Nikita Vasilenko, Alexander Demin, Vladimir Boorlakov
https://arxiv.org/abs/2506.05853 https…

Training-Free Query Optimization via LLM-Based Plan Similarity
Large language model (LLM) embeddings offer a promising new avenue for database query optimization. In this paper, we explore how pre-trained execution plan embeddings can guide SQL query execution without the need for additional model training. We introduce LLM-PM (LLM-based Plan Mapping), a framework that embeds the default execution plan of a query, finds its k nearest neighbors among previously executed plans, and recommends database hintsets based on neighborhood voting. A lightweight cons…

A Neuronal Model at the Edge of Criticality: An Ising-Inspired Approach to Brain Dynamics
Sajedeh Sarmastani, Maliheh Ghodrat, Yousef Jamali
https://arxiv.org/abs/2506.07027

A Neuronal Model at the Edge of Criticality: An Ising-Inspired Approach to Brain Dynamics
We present a neuronal network model inspired by the Ising model, where each neuron is a binary spin ($s_i = \pm1$) interacting with its neighbors on a 2D lattice. Updates are asynchronous and follow Metropolis dynamics, with a temperature-like parameter $T$ introducing stochasticity. To incorporate physiological realism, each neuron includes fixed on/off durations, mimicking the refractory period found in real neurons. These counters prevent immediate reactivation, adding biologically grounde…

https://social.cwts.nl/@LudoWaltman/114552901400267842
Always publish an open preprint first, and then, if needed, submit to a journal. If the preprint is open anyway, it probably doesn't matter whether your chosen journal is open access (of any flavour) or subscription-…

Ludo Waltman (@LudoWaltman@social.cwts.nl)
Attached: 1 image How does the adoption of preprinting differ between European countries? Preprint adoption is significantly higher in Western and Northern European countries than in their Southern and Eastern European neighbors. Switzerland has the highest preprint adoption in Europe.

#nyc isn’t ready for temperatures above 100 degrees. #hot #heatwave
Prepare yourself for a 50 degree F swing in one weeks time.
Do your vulnerable neighbors have access to a/c?
😥
NYC Folks - do you have a non electric way to cool yourself? (Water sprayers outside , shade?)

Foreboding only intensified Monday,
when Trump applauded the idea of arresting California Gov. Gavin Newsom (D),
followed by the mobilization of hundreds of active-duty Marines to augment the Guard members already in Los Angeles.

In a city that has increasingly found itself in the crosshairs of the federal government, turmoil can feel personal.
Local leaders accuse the Trump administration of ginning up a crisis for political gain,
and Angelenos from across …

‘He’s waging a war on us’: As Trump escalates, Angelenos defend their city
Across this vast metropolis, residents denounce what they consider an attack on the very fabric of their city — on their neighbors, co-workers, family members.

Ordering-disordering dynamics of the voter model under random external bias
Roni Muslim, Jihye Kim, Noriko Oikawa, Rinto Anugraha NQZ, Zulkaida Akbar
https://arxiv.org/abs/2506.05669

Ordering-disordering dynamics of the voter model under random external bias
We investigate a variant of the two-state voter model in which agents update their states under a random external field (which points upward with probability $s$ and downward with probability $1-s$) with probability $p$ or adopt the unanimous opinion of $q$ randomly selected neighbors with probability $ 1-p$. Using mean-field analysis and Monte Carlo simulations, we identify an ordering-disorder transition at $p_c$ when $s=1/2$. Notably, in the regime of $p>p_c$, we estimate the time for system…

Sensor Fusion Methods for Gaussian Mixture Models
Ishan Paranjape, Islam Hussein, Jeremy Murray-Krezan, Sean Phillips, Suman Chakravorty
https://arxiv.org/abs/2506.00383

Sensor Fusion Methods for Gaussian Mixture Models
Consensus is a popular technique for distributed state estimation. This formulation allows networks of connected agents or sensors to exchange information about the distribution of a set of targets with their immediate neighbors without the need of a centralized node or layer. We present decentralized consensus-based fusion techniques for a system whose target prior estimates are a weighted mixture of Gaussian probability density functions (PDFs) for the following cases: 1) in which all agents …

Neighbors

Went over to the neighbors this morning for coffee on the porch. A little gathering of neighbors they host once in awhile.
Noticed his wife was not remembering well, we attributed it to the fact we are all getting a bit on the old side.
I gave her a bar of soap I made and explained it was chocolate soap. Made with cocoa butter, cherry kernel, almond and avocado oils and colored with cocoa powder and smelled and looked like a chunk of chocolate. Explained she should test it on her…

RADAR: Recall Augmentation through Deferred Asynchronous Retrieval
Amit Jaspal, Qian Dang, Ajantha Ramineni
https://arxiv.org/abs/2506.07261 https://

RADAR: Recall Augmentation through Deferred Asynchronous Retrieval
Modern large-scale recommender systems employ multi-stage ranking funnel (Retrieval, Pre-ranking, Ranking) to balance engagement and computational constraints (latency, CPU). However, the initial retrieval stage, often relying on efficient but less precise methods like K-Nearest Neighbors (KNN), struggles to effectively surface the most engaging items from billion-scale catalogs, particularly distinguishing highly relevant and engaging candidates from merely relevant ones. We introduce Recall A…

This https://arxiv.org/abs/2202.12453 has been replaced.
link: https://scholar.google.com/scholar?q=a

Social Learning under Platform Influence: Consensus and Persistent Disagreement
Individuals increasingly rely on social networking platforms to form opinions. However, these platforms typically aim to maximize engagement, which may not align with social good. In this paper, we introduce an opinion dynamics model where agents are connected in a social network, and update their opinions based on their neighbors' opinions and on the content shown to them by the platform. We focus on a stochastic block model with two blocks, where the initial opinions of the individuals in dif…

TADA: Training-free Attribution and Out-of-Domain Detection of Audio Deepfakes
Adriana Stan, David Combei, Dan Oneata, Hora Cucu
https://arxiv.org/abs/2506.05802

TADA: Training-free Attribution and Out-of-Domain Detection of Audio Deepfakes
Deepfake detection has gained significant attention across audio, text, and image modalities, with high accuracy in distinguishing real from fake. However, identifying the exact source--such as the system or model behind a deepfake--remains a less studied problem. In this paper, we take a significant step forward in audio deepfake model attribution or source tracing by proposing a training-free, green AI approach based entirely on k-Nearest Neighbors (kNN). Leveraging a pre-trained self-supervi…

If you want to show solidarity with Los Angeles, the best thing to do is organize protests against ICE tonight/tomorrow in your own cities.
Search the web for ICE rapid response networks in your own city / state and sign up. Help your neighbors.
https://bsky.app/profile/chadloder.bsk

Coherence and Transients in Nonlocally Coupled Dissipative Kicked Rotors
Jin Yan
https://arxiv.org/abs/2506.10828 https://arxiv.org/p…

Coherence and Transients in Nonlocally Coupled Dissipative Kicked Rotors
The dynamics of nonlocally coupled dissipative kicked rotors is rich and complex. In this study, we consider a network of rotors where each interacts equally with a certain range of its neighbors. We focus on the influence of the coupling strength and the coupling range, and show both analytically and numerically the critical transitions in the phase diagram, which include bifurcations of simple spatiotemporal patterns and changes in basin sizes of coherent states with different wavenumbers. We…

This https://arxiv.org/abs/2501.17432 has been replaced.
initial toot: https://mastoxiv.page/@arX…

Diagonal superexchange in a simple square CuO$_2$ lattice
Many microscopic models with the interaction between the next-nearest neighbours as a key parameter for cuprate physics have inspired us to study the diagonal superexchange interaction in a CuO$_2$ layer. Our investigation shows that models with extended hopping provide a correct representation of magnetic interactions only in a hypothetical square CuO$_2$ layer, where the diagonal superexchange interaction with the next-nearest neighbors always has the AFM nature. The conclusions are based on …

Rumors on evolving graphs through stationary times
Vicenzo Bonasorte
https://arxiv.org/abs/2506.04386 https://arxiv.org/pdf/2506.0438…

Rumors on evolving graphs through stationary times
We study rumor spreading in dynamic random graphs. Starting with a single informed vertex, the information flows until it reaches all the vertices of the graph (completion), according to the following process. At each step $k$, the information is propagated to neighbors of the informed vertices, in the $k$-th generated random graph. The way this information propagates from vertex to vertex at each step will depend on the ``protocol". We provide a method based on strong stationary times to study…

Heterogeneous Sequel-Aware Graph Neural Networks for Sequential Learning
Anushka Tiwari, Haimonti Dutta, Shahrzad Khanizadeh
https://arxiv.org/abs/2506.05625

Heterogeneous Sequel-Aware Graph Neural Networks for Sequential Learning
Graph-based recommendation systems use higher-order user and item embeddings for next-item predictions. Dynamically adding collaborative signals from neighbors helps to use similar users' preferences during learning. While item-item correlations and their impact on recommendations have been studied, the efficacy of temporal item sequences for recommendations is much less explored. In this paper, we examine temporal item sequence (sequel-aware) embeddings along with higher-order user embeddings …

This https://arxiv.org/abs/2412.17779 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_sta…

Ergodic Network Stochastic Differential Equations
We propose a novel framework for Network Stochastic Differential Equations (N-SDE), where each node in a network is governed by an SDE influenced by interactions with its neighbors. The evolution of each node is driven by the interplay of three key components: the node's intrinsic dynamics (\emph{momentum effect}), feedback from neighboring nodes (\emph{network effect}), and a \emph{stochastic volatility} term modeled by Brownian motion. Our primary objective is to estimate the parameters of th…

The GAIN Model: A Nature-Inspired Neural Network Framework Based on an Adaptation of the Izhikevich Model
Gage K. R. Hooper
https://arxiv.org/abs/2506.04247

The GAIN Model: A Nature-Inspired Neural Network Framework Based on an Adaptation of the Izhikevich Model
While many neural networks focus on layers to process information, the GAIN model uses a grid-based structure to improve biological plausibility and the dynamics of the model. The grid structure helps neurons to interact with their closest neighbors and improve their connections with one another, which is seen in biological neurons. While also being implemented with the Izhikevich model this approach allows for a computationally efficient and biologically accurate simulation that can aid in the…

This https://arxiv.org/abs/2402.15311 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_mat…

Scaling Limit of the Kuramoto Model on Random Geometric Graphs
We consider the Kuramoto model on a graph with nodes given by $n$ i.i.d. points uniformly distributed on the $d$ dimensional torus. Two nodes are declared neighbors if they are at distance less than $ε$. We prove a scaling limit for this model in compact time intervals as $n\to\infty$ and $ε\to 0$ such that $ε^{d+2}n/\log n \to \infty$. The limiting object is given by the heat equation. On the one hand this shows that the nonlinearity given by the sine function disappears under this scaling …

Quake: Adaptive Indexing for Vector Search
Jason Mohoney, Devesh Sarda, Mengze Tang, Shihabur Rahman Chowdhury, Anil Pacaci, Ihab F. Ilyas, Theodoros Rekatsinas, Shivaram Venkataraman
https://arxiv.org/abs/2506.03437

Quake: Adaptive Indexing for Vector Search
Vector search, the task of finding the k-nearest neighbors of high-dimensional vectors, underpins many machine learning applications, including recommendation systems and information retrieval. However, existing approximate nearest neighbor (ANN) methods perform poorly under dynamic, skewed workloads where data distributions evolve. We introduce Quake, an adaptive indexing system that maintains low latency and high recall in such environments. Quake employs a hierarchical partitioning scheme th…

This https://arxiv.org/abs/2402.08628 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_mat…

Nonlinear Graphon mean-field systems
We address a system of weakly interacting particles where the heterogenous connections among the particles are described by a graph sequence and the number of particles grows to infinity. Our results extend the existing law of large numbers and propagation of chaos results to the case where the interaction between one particle and its neighbors is expressed as a nonlinear function of the local empirical measure. In the limit of the number of particles which tends to infinity, if the graph seque…

The liberal obsession with optics serves the right and persuades no one. There is literally an active ethnic cleansing happening in the US right now, and the only thing that matters is making that as hard as possible to carry out.
Anarchists destroying intelligence assets saves lives. Every escooter thrown at a cop car is one less escort for a goon too afraid to kidnap random brown people without being flanked by a branch full of bad apples. Spray paint is not violence. Vandalism is not violence. Community self defense in all forms is legitimate.
Make no mistake, these raids are about changing demographics. Demographic trends have been shifting blue for a long time, and the right has, for a long time, been blaming "white replacement." Conspiracy theory aside, Democrats have also been relying on the growth of black and brown voters as a block. The nuances of whiteness as an identity are lost on the current administration and their supporters. They see that "white people will be a minority by 2050" and equate that with the "end of Western Civilization."
The only way to "save Western Civilization" is to change those demographics. Forced birth and forced removal are two sides of the same white nationalist objective. Of course they can't have due process, because they need to be able to kidnap anyone who they see as a threat to their demographic future.
They don't care about optics. The plan is to murder away any threat and flood everyone else with propaganda. There is no mythical middle. There's no one unconvinced. They know this, but they win when democrats buy that myth and save the police the work of policing the protests.
If your protest is 90% "peaceful," they'll take pictures of the 10% that isn't. If it's 99% peaceful, they'll shoot rubber bullets and teargas until someone throws a brick and take 100 pictures from a dozen angles. If its 100% "peaceful" and no one can be provoked, they'll generate pictures with AI or photoshop like they did during the George Floyd uprising and the pictures from the CHOP/CHAZ. Do you have literally no memory?
#USPol #FiftyFiftyOne #50501movenent #resistance #NoKingsDay #NoKingsDayOfAction