Most Cited ICLR "agent communication" Papers
6,124 papers found • Page 15 of 31
Conference
From Search to Sampling: Generative Models for Robust Algorithmic Recourse
Prateek Garg, Lokesh Nagalapatti, Sunita Sarawagi
How Low Can You Go? Searching for the Intrinsic Dimensionality of Complex Networks using Metric Node Embeddings
Nikolaos Nakis, Niels Raunkjær Holm, Andreas Lyhne Fiehn et al.
Salvage: Shapley-distribution Approximation Learning Via Attribution Guided Exploration for Explainable Image Classification
Mehdi Naouar, Hanne Raum, Jens Rahnfeld et al.
Interpreting Global Perturbation Robustness of Image Models using Axiomatic Spectral Importance Decomposition
Róisín Luo, James McDermott, Colm O'Riordan
Dreamweaver: Learning Compositional World Models from Pixels
Junyeob Baek, Yi-Fu Wu, Gautam Singh et al.
CoMotion: Concurrent Multi-person 3D Motion
Alejandro Newell, Peiyun Hu, Lahav Lipson et al.
Towards Marginal Fairness Sliced Wasserstein Barycenter
Khai Nguyen, Hai Nguyen, Nhat Ho
ProAdvPrompter: A Two-Stage Journey to Effective Adversarial Prompting for LLMs
Hao Di, Tong He, Haishan Ye et al.
PharmacoMatch: Efficient 3D Pharmacophore Screening via Neural Subgraph Matching
Daniel Rose, Oliver Wieder, Thomas Seidel et al.
Bisimulation Metric for Model Predictive Control
Yutaka Shimizu, Masayoshi Tomizuka
DEPT: Decoupled Embeddings for Pre-training Language Models
Alex Iacob, Lorenzo Sani, Meghdad Kurmanji et al.
Graph-based Document Structure Analysis
Yufan Chen, Ruiping Liu, Junwei Zheng et al.
Newton Meets Marchenko-Pastur: Massively Parallel Second-Order Optimization with Hessian Sketching and Debiasing
Elad Romanov, Fangzhao Zhang, Mert Pilanci
Towards Certification of Uncertainty Calibration under Adversarial Attacks
Cornelius Emde, Francesco Pinto, Thomas Lukasiewicz et al.
NEAR: A Training-Free Pre-Estimator of Machine Learning Model Performance
Raphael Husistein, Markus Reiher, Marco Eckhoff
Density estimation with LLMs: a geometric investigation of in-context learning trajectories
Toni Liu, Nicolas Boulle, Raphaël Sarfati et al.
Autonomous Evaluation of LLMs for Truth Maintenance and Reasoning Tasks
Rushang Karia, Daniel Bramblett, Daksh Dobhal et al.
Beyond Circuit Connections: A Non-Message Passing Graph Transformer Approach for Quantum Error Mitigation
Tianyi Bao, Xinyu Ye, Hang Ruan et al.
The Directionality of Optimization Trajectories in Neural Networks
Sidak Pal Singh, Bobby He, Thomas Hofmann et al.
Learning to Help in Multi-Class Settings
Yu Wu, Yansong Li, Zeyu Dong et al.
Zero-Shot Natural Language Explanations
Fawaz Sammani, Nikos Deligiannis
Preference Elicitation for Offline Reinforcement Learning
Alizée Pace, Bernhard Schölkopf, Gunnar Ratsch et al.
GLOMA: Global Video Text Spotting with Morphological Association
Han Wang, Yanjie Wang, Yang Li et al.
MIRACLE 3D: Memory-efficient Integrated Robust Approach for Continual Learning on 3D Point Clouds via Shape Model Construction
Hossein Resani, Behrooz Nasihatkon
Towards a learning theory of representation alignment
Francesco Maria Gabriele Insulla, Shuo Huang, Lorenzo Rosasco
Minimal Variance Model Aggregation: A principled, non-intrusive, and versatile integration of black box models
Theo Bourdais, Houman Owhadi
Understanding Constraint Inference in Safety-Critical Inverse Reinforcement Learning
Bo Yue, Shufan Wang, Ashish Gaurav et al.
Theory on Score-Mismatched Diffusion Models and Zero-Shot Conditional Samplers
Yuchen Liang, Peizhong Ju, Yingbin Liang et al.
How to Find the Exact Pareto Front for Multi-Objective MDPs?
Yining Li, Peizhong Ju, Ness Shroff
Out-of-distribution Generalization for Total Variation based Invariant Risk Minimization
Yuanchao Wang, Zhao-Rong Lai, Tianqi Zhong
Outlier Synthesis via Hamiltonian Monte Carlo for Out-of-Distribution Detection
Hengzhuang Li, Teng Zhang
ProtoSnap: Prototype Alignment For Cuneiform Signs
Rachel Mikulinsky, Morris Alper, Shai Gordin et al.
VICtoR: Learning Hierarchical Vision-Instruction Correlation Rewards for Long-horizon Manipulation
Kuo-Han Hung, Pang-Chi Lo, Jia-Fong Yeh et al.
Enhance Multi-View Classification Through Multi-Scale Alignment and Expanded Boundary
Yuena Lin, Yiyuan Wang, Gengyu Lyu et al.
Efficient Distribution Matching of Representations via Noise-Injected Deep InfoMax
Ivan Butakov, Alexander Semenenko, Alexander Tolmachev et al.
GMValuator: Similarity-based Data Valuation for Generative Models
Jiaxi Yang, Wenlong Deng, Benlin Liu et al.
Restyling Unsupervised Concept Based Interpretable Networks with Generative Models
Jayneel Parekh, Quentin Bouniot, Pavlo Mozharovskyi et al.
Warm Diffusion: Recipe for Blur-Noise Mixture Diffusion Models
Hao-Chien Hsueh, Wen-Hsiao Peng, Ching-Chun Huang
Learning on One Mode: Addressing Multi-modality in Offline Reinforcement Learning
Mianchu Wang, Yue Jin, Giovanni Montana
AutoG: Towards automatic graph construction from tabular data
Zhikai Chen, Han Xie, Jian Zhang et al.
Learning to Generate Diverse Pedestrian Movements from Web Videos with Noisy Labels
Zhizheng Liu, Joe Lin, Wayne Wu et al.
Adaptive Shrinkage Estimation for Personalized Deep Kernel Regression in Modeling Brain Trajectories
Vasiliki Tassopoulou, Haochang Shou, Christos Davatzikos
An Optimal Discriminator Weighted Imitation Perspective for Reinforcement Learning
Haoran Xu, Shuozhe Li, Harshit Sikchi et al.
$q$-exponential family for policy optimization
Lingwei Zhu, Haseeb Shah, Han Wang et al.
Offline RL with Smooth OOD Generalization in Convex Hull and its Neighborhood
Qingmao Yao, Zhichao Lei, Tianyuan Chen et al.
InstantPortrait: One-Step Portrait Editing via Diffusion Multi-Objective Distillation
Zhixin Lai, Keqiang Sun, Fu-Yun Wang et al.
Differentiable Rule Induction from Raw Sequence Inputs
Kun Gao, Katsumi Inoue, Yongzhi Cao et al.
TopoGaussian: Inferring Internal Topology Structures from Visual Clues
Xiaoyu Xiong, Changyu Hu, Chunru Lin et al.
REBIND: Enhancing Ground-state Molecular Conformation Prediction via Force-Based Graph Rewiring
Taewon Kim, Hyunjin Seo, Sungsoo Ahn et al.
CPSample: Classifier Protected Sampling for Guarding Training Data During Diffusion
Joshua Kazdan, Hao Sun, Jiaqi Han et al.
Generalization in VAE and Diffusion Models: A Unified Information-Theoretic Analysis
Qi Chen, Jierui Zhu, Florian Shkurti
LLM-based Typed Hyperresolution for Commonsense Reasoning with Knowledge Bases
Armin Toroghi, Ali Pesaranghader, Tanmana Sadhu et al.
Measuring And Improving Engagement of Text-to-Image Generation Models
Varun Khurana, Yaman Singla, Jayakumar Subramanian et al.
3D-SPATIAL MULTIMODAL MEMORY
Xueyan Zou, Yuchen Song, Ri-Zhao Qiu et al.
SeedLM: Compressing LLM Weights into Seeds of Pseudo-Random Generators
Rasoul Shafipour, David Harrison, Maxwell Horton et al.
Physiome-ODE: A Benchmark for Irregularly Sampled Multivariate Time-Series Forecasting Based on Biological ODEs
Christian Klötergens, Vijaya Krishna Yalavarthi, Randolf Scholz et al.
AIMS.au: A Dataset for the Analysis of Modern Slavery Countermeasures in Corporate Statements
Adriana-Eufrosina Bora, Pierre-Luc St-Charles, Mirko Bronzi et al.
Weakly Supervised Video Scene Graph Generation via Natural Language Supervision
Kibum Kim, Kanghoon Yoon, Yeonjun In et al.
Demystifying Topological Message-Passing with Relational Structures: A Case Study on Oversquashing in Simplicial Message-Passing
Diaaeldin Taha, James Chapman, Marzieh Eidi et al.
RFMamba: Frequency-Aware State Space Model for RF-Based Human-Centric Perception
Rui Zhang, Ruixu Geng, Yadong Li et al.
Diverse Policies Recovering via Pointwise Mutual Information Weighted Imitation Learning
Hanlin Yang, Jian Yao, Weiming Liu et al.
Controlled LLM Decoding via Discrete Auto-regressive Biasing
Patrick Pynadath, Ruqi Zhang
PvNeXt: Rethinking Network Design and Temporal Motion for Point Cloud Video Recognition
Jie Wang, Tingfa Xu, Lihe Ding et al.
Lambda-Skip Connections: the architectural component that prevents Rank Collapse
Federico Arangath Joseph, Jerome Sieber, Melanie Zeilinger et al.
Asymptotic Analysis of Two-Layer Neural Networks after One Gradient Step under Gaussian Mixtures Data with Structure
Samet Demir, Zafer Dogan
Dynamic Contrastive Skill Learning with State-Transition Based Skill Clustering and Dynamic Length Adjustment
Jinwoo Choi, Seung-Woo Seo
MIND over Body: Adaptive Thinking using Dynamic Computation
Mrinal Mathur, Barak Pearlmutter, Sergey Plis
An Asynchronous Bundle Method for Distributed Learning Problems
Daniel Cederberg, Xuyang Wu, Stephen Boyd et al.
Physics-informed Temporal Difference Metric Learning for Robot Motion Planning
Ruiqi Ni, zherong pan, Ahmed Hussain Qureshi
Solving Differential Equations with Constrained Learning
Viggo Moro, Luiz Chamon
Fast Direct: Query-Efficient Online Black-box Guidance for Diffusion-model Target Generation
Kim Yong Tan, YUEMING LYU, Ivor Tsang et al.
REVISITING MULTI-PERMUTATION EQUIVARIANCE THROUGH THE LENS OF IRREDUCIBLE REPRESENTATIONS
Yonatan Sverdlov, Ido Springer, Nadav Dym
The Breakdown of Gaussian Universality in Classification of High-dimensional Linear Factor Mixtures
Xiaoyi MAI, Zhenyu Liao
KooNPro: A Variance-Aware Koopman Probabilistic Model Enhanced by Neural Process for Time Series Forecasting
Ronghua Zheng, Hanru Bai, Weiyang Ding
A Non-Contrastive Learning Framework for Sequential Recommendation with Preference-Preserving Profile Generation
Huimin Zeng, Xiaojie Wang, Anoop Jain et al.
An Auditing Test to Detect Behavioral Shift in Language Models
Leo Richter, Xuanli He, Pasquale Minervini et al.
Latent Intuitive Physics: Learning to Transfer Hidden Physics from A 3D Video
Xiangming Zhu, Huayu Deng, Haochen Yuan et al.
Mining your own secrets: Diffusion Classifier Scores for Continual Personalization of Text-to-Image Diffusion Models
Saurav Jha, Shiqi Yang, Masato Ishii et al.
Revealing the 3D Cosmic Web through Gravitationally Constrained Neural Fields
Brandon Zhao, Aviad Levis, Liam Connor et al.
Continuous Exposure Learning for Low-light Image Enhancement using Neural ODEs
Donggoo Jung, Daehyun Kim, Tae Hyun Kim
Towards a Unified and Verified Understanding of Group-Operation Networks
Wilson Wu, Louis Jaburi, jacob drori et al.
Discovering Group Structures via Unitary Representation Learning
Dongsung Huh
Long-time asymptotics of noisy SVGD outside the population limit
Victor Priser, PASCAL BIANCHI, Adil Salim
LevAttention: Time, Space and Streaming Efficient Algorithm for Heavy Attentions
Ravindran Kannan, Chiranjib Bhattacharyya, Praneeth Kacham et al.
Dysca: A Dynamic and Scalable Benchmark for Evaluating Perception Ability of LVLMs
Jie Zhang, Zhongqi Wang, Mengqi Lei et al.
OptionZero: Planning with Learned Options
Po-Wei Huang, Pei-Chiun Peng, Hung Guei et al.
Geometry of Long-Tailed Representation Learning: Rebalancing Features for Skewed Distributions
Lingjie Yi, Michael Yao, Weimin Lyu et al.
Tight Lower Bounds under Asymmetric High-Order Hölder Smoothness and Uniform Convexity
Cedar Site Bai, Brian Bullins
Training Large Language Models for Retrieval-Augmented Question Answering through Backtracking Correction
Huawen Feng, ZekunYao, Junhao Zheng et al.
Generative Adversarial Ranking Nets
Yinghua Yao, Yuangang Pan, Jing Li et al.
Towards Learning High-Precision Least Squares Algorithms with Sequence Models
Jerry Liu, Jessica Grogan, Owen Dugan et al.
Bayesian Bi-clustering of Neural Spiking Activity with Latent Structures
Ganchao Wei
When GNNs meet symmetry in ILPs: an orbit-based feature augmentation approach
Qian Chen, Lei Li, Qian Li et al.
NfgTransformer: Equivariant Representation Learning for Normal-form Games
SIQI LIU, Luke Marris, Georgios Piliouras et al.
Towards Scalable Topological Regularizers
Wong Hiu-Tung, Darrick Lee, Hong Yan
Systems with Switching Causal Relations: A Meta-Causal Perspective
Moritz Willig, Tim Tobiasch, Florian Busch et al.
Stochastic Bandits Robust to Adversarial Attacks
Xuchuang Wang, Maoli Liu, Jinhang Zuo et al.
Optimal Learning of Kernel Logistic Regression for Complex Classification Scenarios
Hongwei Wen, Annika Betken, Hanyuan Hang
Weighted Multi-Prompt Learning with Description-free Large Language Model Distillation
Sua Lee, Kyubum Shin, Jung Ho Park
Zero-cost Proxy for Adversarial Robustness Evaluation
Yuqi Feng, Yuwei Ou, Jiahao Fan et al.
VOILA: Evaluation of MLLMs For Perceptual Understanding and Analogical Reasoning
Nilay Yilmaz, Maitreya Patel, Lawrence Luo et al.
Learning Randomized Algorithms with Transformers
Johannes von Oswald, Seijin Kobayashi, Yassir Akram et al.
Adversarial Latent Feature Augmentation for Fairness
Hoin Jung, Junyi Chai, Xiaoqian Wang
Minimal Impact ControlNet: Advancing Multi-ControlNet Integration
Shikun Sun, Min Zhou, Zixuan Wang et al.
ConcreTizer: Model Inversion Attack via Occupancy Classification and Dispersion Control for 3D Point Cloud Restoration
Youngseok Kim, Sunwook Hwang, Hyung-Sin Kim et al.
Learning Regularized Graphon Mean-Field Games with Unknown Graphons
Fengzhuo Zhang, Vincent Tan, Zhaoran Wang et al.
Long-Context Linear System Identification
Oğuz Kaan Yüksel, Mathieu Even, Nicolas Flammarion
Training Robust Ensembles Requires Rethinking Lipschitz Continuity
Ali Ebrahimpour Boroojeny, Hari Sundaram, Varun Chandrasekaran
Collapsed Language Models Promote Fairness
Jingxuan Xu, Wuyang Chen, Linyi Li et al.
Selective Mixup Fine-Tuning for Optimizing Non-Decomposable Objectives
Shrinivas Ramasubramanian, Harsh Rangwani, Sho Takemori et al.
Fast and Accurate Blind Flexible Docking
Zizhuo Zhang, Lijun Wu, Kaiyuan Gao et al.
Pareto Prompt Optimization
Guang Zhao, Byung-Jun Yoon, Gilchan Park et al.
On the Importance of Language-driven Representation Learning for Heterogeneous Federated Learning
Yunlu Yan, Chun-Mei Feng, Wangmeng Zuo et al.
Causal Effect Estimation with Mixed Latent Confounders and Post-treatment Variables
Yaochen Zhu, Jing Ma, Liang Wu et al.
Elliptic Loss Regularization
Ali Hasan, Haoming Yang, Yuting Ng et al.
Dynamic Assortment Selection and Pricing with Censored Preference Feedback
Jung-hun Kim, Min-hwan Oh
Optimizing importance weighting in the presence of sub-population shifts
Floris Holstege, Bram Wouters, Noud Giersbergen et al.
Learning Robust Representations with Long-Term Information for Generalization in Visual Reinforcement Learning
Rui Yang, Jie Wang, Qijie Peng et al.
Proximal Mapping Loss: Understanding Loss Functions in Crowd Counting & Localization
Wei LIN, Jia Wan, Antoni Chan
Regret Bounds for Episodic Risk-Sensitive Linear Quadratic Regulator
Wenhao Xu, Xuefeng Gao, Xuedong He
DynAlign: Unsupervised Dynamic Taxonomy Alignment for Cross-Domain Segmentation
HAN SUN, Rui Gong, Ismail Nejjar et al.
Improving Graph Neural Networks by Learning Continuous Edge Directions
Seong Ho Pahng, Sahand Hormoz
L3Ms — Lagrange Large Language Models
Guneet Singh Dhillon, Xingjian Shi, Yee Whye Teh et al.
Achieving Sample and Computational Efficient Reinforcement Learning by Action Space Reduction via Grouping
Yining Li, Peizhong Ju, Ness Shroff
Separation Power of Equivariant Neural Networks
Marco Pacini, Xiaowen Dong, Bruno Lepri et al.
Event-Driven Online Vertical Federated Learning
Ganyu Wang, Boyu Wang, Bin Gu et al.
Scale-aware Recognition in Satellite Images under Resource Constraints
Shreelekha Revankar, Cheng Perng Phoo, Utkarsh Kumar Mall et al.
Towards Empowerment Gain through Causal Structure Learning in Model-Based Reinforcement Learning
Hongye Cao, Fan Feng, Meng Fang et al.
The Journey Matters: Average Parameter Count over Pre-training Unifies Sparse and Dense Scaling Laws
Tian Jin, Ahmed Imtiaz Humayun, Utku Evci et al.
TTVD: Towards a Geometric Framework for Test-Time Adaptation Based on Voronoi Diagram
Mingxi Lei, Chunwei Ma, Meng Ding et al.
Understanding the Robustness of Randomized Feature Defense Against Query-Based Adversarial Attacks
Hung Quang Nguyen, Yingjie Lao, Tung Pham et al.
Last Iterate Convergence of Incremental Methods as a Model of Forgetting
Xufeng Cai, Jelena Diakonikolas
Generalized Video Moment Retrieval
Qin You, Qilong Wu, Yicong Li et al.
Trajectory-Class-Aware Multi-Agent Reinforcement Learning
Hyungho Na, Kwanghyeon Lee, Sumin Lee et al.
ComLoRA: A Competitive Learning Approach for Enhancing LoRA
Qiushi Huang, Tom Ko, Lilian Tang et al.
Balanced Ranking with Relative Centrality: A multi-core periphery perspective
Chandra Sekhar Mukherjee, Jiapeng Zhang
Centrality-guided Pre-training for Graph
Bin Liang, Shiwei Chen, Lin Gui et al.
Metric-Driven Attributions for Vision Transformers
Chase Walker, Sumit Jha, Rickard Ewetz
Execution-guided within-prompt search for programming-by-example
Gust Verbruggen, Ashish Tiwari, Mukul Singh et al.
Towards Explaining the Power of Constant-depth Graph Neural Networks for Structured Linear Programming
Qian Li, Minghui Ouyang, Tian Ding et al.
Privacy-Aware Lifelong Learning
Ozan Özdenizci, Elmar Rueckert, Robert Legenstein
Beyond single neurons: population response geometry in digital twins of mouse visual cortex
Dario Liscai, Emanuele Luconi, Alessandro Marin Vargas et al.
Clique Number Estimation via Differentiable Functions of Adjacency Matrix Permutations
Indradyumna Roy, Eeshaan Jain, Soumen Chakrabarti et al.
Interactive Adjustment for Human Trajectory Prediction with Individual Feedback
Jianhua Sun, Yuxuan Li, Liang Chai et al.
ADAM Optimization with Adaptive Batch Selection
Gyu Yeol Kim, Min-hwan Oh
Prompt as Knowledge Bank: Boost Vision-language model via Structural Representation for zero-shot medical detection
Yuguang Yang, Tongfei Chen, Haoyu Huang et al.
Locally Connected Echo State Networks for Time Series Forecasting
Filip Matzner, František Mráz
Node Similarities under Random Projections: Limits and Pathological Cases
Tvrtko Tadić, Cassiano O Becker, Jennifer Neville
Learning Gain Map for Inverse Tone Mapping
yinuo liao, Yuanshen Guan, Ruikang Xu et al.
A Large-scale Training Paradigm for Graph Generative Models
Yu Wang, Ryan Rossi, Namyong Park et al.
LiFT: Learning to Fine-Tune via Bayesian Parameter Efficient Meta Fine-Tuning
Minyoung Kim, Timothy Hospedales
Rethinking and Extending the Probabilistic Inference Capacity of GNNs
Tuo Xu, Lei Zou
Risk-Sensitive Variational Actor-Critic: A Model-Based Approach
Alonso Granados, Mohammadreza Ebrahimi, Jason Pacheco
Leveraging Uncertainty Estimates To Improve Classifier Performance
Gundeep Arora, Srujana Merugu, Anoop Saladi et al.
Decoupled Finetuning for Domain Generalizable Semantic Segmentation
Jaehyun Pahk, Donghyeon Kwon, Seong Joon Oh et al.
Generalization and Distributed Learning of GFlowNets
Tiago Silva, Amauri Souza, Omar Rivasplata et al.
PRDP: Progressively Refined Differentiable Physics
Kanishk Bhatia, Felix Koehler, Nils Thuerey
How Learnable Grids Recover Fine Detail in Low Dimensions: A Neural Tangent Kernel Analysis of Multigrid Parametric Encodings
Samuel Audia, Soheil Feizi, Matthias Zwicker et al.
LEAD: Min-Max Optimization from a Physical Perspective
Guillaume Lajoie, Amartya Mitra, Reyhane Askari Hemmat et al.
Multimodal Unsupervised Domain Generalization by Retrieving Across the Modality Gap
Christopher Liao, Christian So, Theodoros Tsiligkaridis et al.
CoMRes: Semi-Supervised Time Series Forecasting Utilizing Consensus Promotion of Multi-Resolution
Yunju Cho, Jay-Yoon Lee
High-Dynamic Radar Sequence Prediction for Weather Nowcasting Using Spatiotemporal Coherent Gaussian Representation
Ziye Wang, Yiran Qin, Lin Zeng et al.
Feedback Schrödinger Bridge Matching
Panagiotis Theodoropoulos, Nikolaos Komianos, Vincent Pacelli et al.
Minimax Optimal Two-Stage Algorithm For Moment Estimation Under Covariate Shift
Zhen Zhang, Xin Liu, Shaoli Wang et al.
Gaussian Differentially Private Human Faces Under a Face Radial Curve Representation
Carlos Soto, Matthew Reimherr, Aleksandra Slavkovic et al.
HADAMRNN: BINARY AND SPARSE TERNARY ORTHOGONAL RNNS
Armand Foucault, Francois Malgouyres, Franck Mamalet
Efficient Policy Evaluation with Safety Constraint for Reinforcement Learning
Claire Chen, Shuze Liu, Shangtong Zhang
Rethinking Self-Distillation: Label Averaging and Enhanced Soft Label Refinement with Partial Labels
Hyeonsu Jeong, Hye Won Chung
Gaussian Splatting Lucas-Kanade
Liuyue Xie, Joel Julin, Koichiro Niinuma et al.
PolyhedronNet: Representation Learning for Polyhedra with Surface-attributed Graph
Dazhou Yu, Genpei Zhang, Liang Zhao
Pooling Image Datasets with Multiple Covariate Shift and Imbalance
Sotirios Panagiotis Chytas, Vishnu Lokhande, Vikas Singh
Input Space Mode Connectivity in Deep Neural Networks
Jakub Vrabel, Ori Shem-ur, Yaron Oz et al.
Learning a Fast Mixing Exogenous Block MDP using a Single Trajectory
Alexander Levine, Peter Stone, Amy Zhang
Learning Successor Features with Distributed Hebbian Temporal Memory
Evgenii Dzhivelikian, Petr Kuderov, Aleksandr Panov
Capability Localization: Capabilities Can be Localized rather than Individual Knowledge
Xiusheng Huang, Jiaxiang Liu, Yequan Wang et al.
PIED: Physics-Informed Experimental Design for Inverse Problems
Apivich Hemachandra, Gregory Kang Ruey Lau, See-Kiong Ng et al.
Going Beyond Static: Understanding Shifts with Time-Series Attribution
Jiashuo Liu, Nabeel Seedat, Peng Cui et al.
Release the Powers of Prompt Tuning: Cross-Modality Prompt Transfer
Ningyuan Zhang, Jie Lu, Keqiuyin Li et al.
EDiT: A Local-SGD-Based Efficient Distributed Training Method for Large Language Models
Jialiang Cheng, Ning Gao, Yun Yue et al.
Fitting Networks with a Cancellation Trick
Jiashun Jin, Jingming Wang
Robust Model Based Reinforcement Learning Using $\mathcal{L}_1$ Adaptive Control
Minjun Sung, Sambhu Harimanas Karumanchi, Aditya Gahlawat et al.
Satisficing Regret Minimization in Bandits
Qing Feng, Tianyi Ma, Ruihao Zhu
Neural networks on Symmetric Spaces of Noncompact Type
Xuan Son Nguyen, Yang, Aymeric Histace
Conservative Contextual Bandits: Beyond Linear Representations
Rohan Deb, Mohammad Ghavamzadeh, Arindam Banerjee
Scale-Free Graph-Language Models
Jianglin Lu, Yixuan Liu, Yitian Zhang et al.
On Rollouts in Model-Based Reinforcement Learning
Bernd Frauenknecht, Devdutt Subhasish, Friedrich Solowjow et al.
Utilitarian Algorithm Configuration for Infinite Parameter Spaces
Devon Graham, Kevin Leyton-Brown
GALA: Geometry-Aware Local Adaptive Grids for Detailed 3D Generation
Dingdong Yang, Yizhi Wang, Konrad Schindler et al.
The "Law'' of the Unconscious Contrastive Learner: Probabilistic Alignment of Unpaired Modalities
Yongwei Che, Benjamin Eysenbach
Democratic Training Against Universal Adversarial Perturbations
Bing Sun, Jun Sun, Wei Zhao
Learning Structured Representations by Embedding Class Hierarchy with Fast Optimal Transport
Siqi Zeng, Sixian Du, Makoto Yamada et al.
Associative memory and dead neurons
Vladimir Fanaskov, Ivan Oseledets
RESfM: Robust Deep Equivariant Structure from Motion
Fadi Khatib, Yoni Kasten, Dror Moran et al.
A Large-scale Dataset and Benchmark for Commuting Origin-Destination Flow Generation
Can Rong, Jingtao Ding, Yan Liu et al.
Distribution Backtracking Builds A Faster Convergence Trajectory for Diffusion Distillation
Shengyuan Zhang, Ling Yang, Zejian Li et al.
Analyzing Neural Scaling Laws in Two-Layer Networks with Power-Law Data Spectra
Roman Worschech, Bernd Rosenow
Improved Diffusion-based Generative Model with Better Adversarial Robustness
Zekun Wang, Mingyang Yi, Shuchen Xue et al.
Local Steps Speed Up Local GD for Heterogeneous Distributed Logistic Regression
Michael Crawshaw, Blake Woodworth, Mingrui Liu
Unsupervised Disentanglement of Content and Style via Variance-Invariance Constraints
Yuxuan Wu, Ziyu Wang, Bhiksha Raj et al.
Debiasing Federated Learning with Correlated Client Participation
Zhenyu Sun, Ziyang Zhang, Zheng Xu et al.