Most Cited ICLR "uniform argument stability" Papers
6,124 papers found • Page 24 of 31
Conference
Fixed-Budget Differentially Private Best Arm Identification
Zhirui Chen, P. N. Karthik, Yeow Meng Chee et al.
UIFace: Unleashing Inherent Model Capabilities to Enhance Intra-Class Diversity in Synthetic Face Recognition
Xiao Lin, Yuge Huang, Jianqing Xu et al.
Decentralized Optimization with Coupled Constraints
Demyan Yarmoshik, Alexander Rogozin, Nikita Kiselev et al.
DEPT: Decoupled Embeddings for Pre-training Language Models
Alex Iacob, Lorenzo Sani, Meghdad Kurmanji et al.
AI2TALE: An Innovative Information Theory-based Approach for Learning to Localize Phishing Attacks
Van Nguyen, Tingmin Wu, Xingliang YUAN et al.
ADAM Optimization with Adaptive Batch Selection
Gyu Yeol Kim, Min-hwan Oh
Non-Stationary Dueling Bandits Under a Weighted Borda Criterion
Joe Suk, Arpit Agarwal
Causal Graphical Models for Vision-Language Compositional Understanding
Fiorenzo Parascandolo, Nicholas Moratelli, Enver Sangineto et al.
How to Find the Exact Pareto Front for Multi-Objective MDPs?
Yining Li, Peizhong Ju, Ness Shroff
Can a Large Language Model be a Gaslighter?
Wei Li, Luyao Zhu, Yang Song et al.
PINP: Physics-Informed Neural Predictor with latent estimation of fluid flows
Huaguan Chen, Yang Liu, Hao Sun
FlashRNN: I/O-Aware Optimization of Traditional RNNs on modern hardware
Korbinian Pöppel, Maximilian Beck, Sepp Hochreiter
Variance-Reducing Couplings for Random Features
Isaac Reid, Stratis Markou, Krzysztof Choromanski et al.
Teaching Human Behavior Improves Content Understanding Abilities Of VLMs
SOMESH SINGH, Harini S I, Yaman Singla et al.
DS-LLM: Leveraging Dynamical Systems to Enhance Both Training and Inference of Large Language Models
Ruibing Song, Chuan Liu, Chunshu Wu et al.
Learning semilinear neural operators: A unified recursive framework for prediction and data assimilation.
Ashutosh Singh, Ricardo Borsoi, Deniz Erdogmus et al.
Autonomous Evaluation of LLMs for Truth Maintenance and Reasoning Tasks
Rushang Karia, Daniel Bramblett, Daksh Dobhal et al.
Flash Inference: Near Linear Time Inference for Long Convolution Sequence Models and Beyond
Costin-Andrei Oncescu, Sanket Jayant Purandare, Stratos Idreos et al.
Neural Functions for Learning Periodic Signal
Woojin Cho, Minju Jo, Kookjin Lee et al.
Swift Hydra: Self-Reinforcing Generative Framework for Anomaly Detection with Multiple Mamba Models
Hoang Khoi Nguyen Do, Truc Nguyen, Malik Hassanaly et al.
Belief-Enriched Pessimistic Q-Learning against Adversarial State Perturbations
Xiaolin Sun, Zizhan Zheng
A Poincaré Inequality and Consistency Results for Signal Sampling on Large Graphs
Thien Le, Luana Ruiz, Stefanie Jegelka
BaB-ND: Long-Horizon Motion Planning with Branch-and-Bound and Neural Dynamics
Keyi Shen, Jiangwei Yu, Jose Barreiros et al.
Towards Generalizable Reinforcement Learning via Causality-Guided Self-Adaptive Representations
Yupei Yang, Biwei Huang, Fan Feng et al.
Language-Assisted Feature Transformation for Anomaly Detection
EungGu Yun, Heonjin Ha, Yeongwoo Nam et al.
DynFrs: An Efficient Framework for Machine Unlearning in Random Forest
Shurong Wang, Zhuoyang Shen, Xinbao Qiao et al.
CoMotion: Concurrent Multi-person 3D Motion
Alejandro Newell, Peiyun Hu, Lahav Lipson et al.
Bayesian Analysis of Combinatorial Gaussian Process Bandits
Jack Sandberg, Niklas Åkerblom, Morteza Haghir Chehreghani
Few-Class Arena: A Benchmark for Efficient Selection of Vision Models and Dataset Difficulty Measurement
Bryan Bo Cao, Lawrence OGorman, Michael Coss et al.
Towards Marginal Fairness Sliced Wasserstein Barycenter
Khai Nguyen, Hai Nguyen, Nhat Ho
Easing Training Process of Rectified Flow Models Via Lengthening Inter-Path Distance
Shifeng Xu, Yanzhu Liu, Adams Kong
Fast unsupervised ground metric learning with tree-Wasserstein distance
Kira Michaela Düsterwald, Samo Hromadka, Makoto Yamada
Learning system dynamics without forgetting
Xikun ZHANG, Dongjin Song, Yushan Jiang et al.
An Investigation of Representation and Allocation Harms in Contrastive Learning
Subha Maity, Mayank Agarwal, Mikhail Yurochkin et al.
FACTS: A Factored State-Space Framework for World Modelling
Li Nanbo, Firas Laakom, Yucheng XU et al.
DOPL: Direct Online Preference Learning for Restless Bandits with Preference Feedback
GUOJUN XIONG, Ujwal Dinesha, Debajoy Mukherjee et al.
Bidirectional Temporal Diffusion Model for Temporally Consistent Human Animation
Tserendorj Adiya, Jae Shin Yoon, Jung Eun Lee et al.
Learning Thresholds with Latent Values and Censored Feedback
Jiahao Zhang, Tao Lin, Weiqiang Zheng et al.
Gaussian Mixture Counterfactual Generator
Jong-Hoon Ahn, Akshay Vashist
Understanding Constraint Inference in Safety-Critical Inverse Reinforcement Learning
Bo Yue, Shufan Wang, Ashish Gaurav et al.
Feature-aligned N-BEATS with Sinkhorn divergence
Joonhun Lee, Myeongho Jeon, Myungjoo Kang et al.
NeurFlow: Interpreting Neural Networks through Neuron Groups and Functional Interactions
Tue Cao, Nhat Hoang-Xuan, Hieu Pham et al.
EMMA: Empowering Multi-modal Mamba with Structural and Hierarchical Alignment
Yifei Xing, Xiangyuan Lan, Ruiping Wang et al.
How Much is Unseen Depends Chiefly on Information About the Seen
Seongmin Lee, Marcel Boehme
Progressive Token Length Scaling in Transformer Encoders for Efficient Universal Segmentation
Abhishek Aich, Yumin Suh, Samuel Schulter et al.
Positive-Unlabeled Diffusion Models for Preventing Sensitive Data Generation
Hiroshi Takahashi, Tomoharu Iwata, Atsutoshi Kumagai et al.
Optimality and Adaptivity of Deep Neural Features for Instrumental Variable Regression
Juno Kim, Dimitri Meunier, Arthur Gretton et al.
Loss Landscape of Shallow ReLU-like Neural Networks: Stationary Points, Saddle Escape, and Network Embedding
Frank Zhengqing Wu, Berfin Simsek, François Ged
Fine-tuning with Reserved Majority for Noise Reduction
Shuyang Jiang, Yusheng Liao, Ya Zhang et al.
Discrete Distribution Networks
Lei Yang
Towards a learning theory of representation alignment
Francesco Maria Gabriele Insulla, Shuo Huang, Lorenzo Rosasco
TeaserGen: Generating Teasers for Long Documentaries
Weihan Xu, Paul Pu Liang, Haven Kim et al.
Graph Neural Networks Are More Than Filters: Revisiting and Benchmarking from A Spectral Perspective
Yushun Dong, Patrick Soga, Yinhan He et al.
InstantPortrait: One-Step Portrait Editing via Diffusion Multi-Objective Distillation
Zhixin Lai, Keqiang Sun, Fu-Yun Wang et al.
FLOPS: Forward Learning with OPtimal Sampling
Tao Ren, Zishi Zhang, Jinyang Jiang et al.
Prompt as Knowledge Bank: Boost Vision-language model via Structural Representation for zero-shot medical detection
Yuguang Yang, Tongfei Chen, Haoyu Huang et al.
Prototype antithesis for biological few-shot class-incremental learning
Binghao Liu, Han Yang, Fang Wan et al.
A Conditional Independence Test in the Presence of Discretization
Boyang Sun, Yu Yao, Guang-Yuan Hao et al.
Physics-informed Temporal Difference Metric Learning for Robot Motion Planning
Ruiqi Ni, zherong pan, Ahmed Hussain Qureshi
Beyond-Expert Performance with Limited Demonstrations: Efficient Imitation Learning with Double Exploration
Heyang Zhao, Xingrui Yu, David Bossens et al.
Near-Optimal Online Learning for Multi-Agent Submodular Coordination: Tight Approximation and Communication Efficiency
Qixin ZHANG, Zongqi Wan, Yu Yang et al.
Beyond Spatio-Temporal Representations: Evolving Fourier Transform for Temporal Graphs
Anson Simon Bastos, Kuldeep Singh, Abhishek Nadgeri et al.
Bayesian Coreset Optimization for Personalized Federated Learning
Prateek Chanda, Shrey Modi, Ganesh Ramakrishnan
ImpScore: A Learnable Metric For Quantifying The Implicitness Level of Sentences
Yuxin Wang, Xiaomeng Zhu, Weimin Lyu et al.
Evaluating Semantic Variation in Text-to-Image Synthesis: A Causal Perspective
Xiangru Zhu, Penglei Sun, Yaoxian Song et al.
Enhancing Document Understanding with Group Position Embedding: A Novel Approach to Incorporate Layout Information
Yuke Zhu, Yue Zhang, Dongdong Liu et al.
Towards Characterizing Domain Counterfactuals for Invertible Latent Causal Models
Zeyu Zhou, Ruqi Bai, Sean Kulinski et al.
Toward Exploratory Inverse Constraint Inference with Generative Diffusion Verifiers
Runyi Zhao, Sheng Xu, Bo Yue et al.
Dynamic Contrastive Skill Learning with State-Transition Based Skill Clustering and Dynamic Length Adjustment
Jinwoo Choi, Seung-Woo Seo
Exploiting Structure in Offline Multi-Agent RL: The Benefits of Low Interaction Rank
Wenhao Zhan, Scott Fujimoto, Zheqing Zhu et al.
Geometry of Long-Tailed Representation Learning: Rebalancing Features for Skewed Distributions
Lingjie Yi, Michael Yao, Weimin Lyu et al.
Learning from Aggregate responses: Instance Level versus Bag Level Loss Functions
Adel Javanmard, Lin Chen, Vahab Mirrokni et al.
A Precise Characterization of SGD Stability Using Loss Surface Geometry
Gregory Dexter, Borja Ocejo, Sathiya Keerthi et al.
Beyond IID weights: sparse and low-rank deep Neural Networks are also Gaussian Processes
Thiziri Nait Saada, Alireza Naderi, Jared Tanner
PharmacoMatch: Efficient 3D Pharmacophore Screening via Neural Subgraph Matching
Daniel Rose, Oliver Wieder, Thomas Seidel et al.
Newton Meets Marchenko-Pastur: Massively Parallel Second-Order Optimization with Hessian Sketching and Debiasing
Elad Romanov, Fangzhao Zhang, Mert Pilanci
INFER: A Neural-symbolic Model For Extrapolation Reasoning on Temporal Knowledge Graph
Ningyuan Li, Haihong E, Tianyu Yao et al.
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
RuAG: Learned-rule-augmented Generation for Large Language Models
Yudi Zhang, Pei Xiao, Lu Wang et al.
The Breakdown of Gaussian Universality in Classification of High-dimensional Linear Factor Mixtures
Xiaoyi MAI, Zhenyu Liao
The Directionality of Optimization Trajectories in Neural Networks
Sidak Pal Singh, Bobby He, Thomas Hofmann et al.
Predicting the Energy Landscape of Stochastic Dynamical System via Physics-informed Self-supervised Learning
Ruikun Li, Huandong Wang, Qingmin Liao et al.
Doubly Robust Instance-Reweighted Adversarial Training
Daouda Sow, Sen Lin, Zhangyang Wang et al.
CBMA: Improving Conformal Prediction through Bayesian Model Averaging
Pankaj Bhagwat, Linglong Kong, Bei Jiang
Linear Spherical Sliced Optimal Transport: A Fast Metric for Comparing Spherical Data
Xinran Liu, Yikun Bai, Rocio Diaz Martin et al.
Rethinking the Uniformity Metric in Self-Supervised Learning
Xianghong Fang, Jian Li, Qiang Sun et al.
Learning under Temporal Label Noise
Sujay Nagaraj, Walter Gerych, Sana Tonekaboni 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
Data-centric Prediction Explanation via Kernelized Stein Discrepancy
Mahtab Sarvmaili, Hassan Sajjad, Ga Wu
$q$-exponential family for policy optimization
Lingwei Zhu, Haseeb Shah, Han Wang et al.
Preference Elicitation for Offline Reinforcement Learning
Alizée Pace, Bernhard Schölkopf, Gunnar Ratsch et al.
Global Convergence of Policy Gradient in Average Reward MDPs
Navdeep Kumar, Yashaswini Murthy, Itai Shufaro et al.
Towards Auto-Regressive Next-Token Prediction: In-context Learning Emerges from Generalization
Zixuan Gong, Xiaolin Hu, Huayi Tang et al.
Efficient Online Pruning and Abstraction for Imperfect Information Extensive-Form Games
Boning Li, Longbo Huang
Bounds on $L_p$ Errors in Density Ratio Estimation via $f$-Divergence Loss Functions
Yoshiaki Kitazawa
Rethinking Audio-Visual Adversarial Vulnerability from Temporal and Modality Perspectives
Zeliang Zhang, Susan Liang, Daiki Shimada et al.
Mask-Based Modeling for Neural Radiance Fields
Ganlin Yang, Guoqiang Wei, Zhizheng Zhang et al.
Sequential Stochastic Combinatorial Optimization Using Hierarchal Reinforcement Learning
Xinsong Feng, Zihan Yu, Yanhai Xiong et al.
Can Neural Networks Achieve Optimal Computational-statistical Tradeoff? An Analysis on Single-Index Model
Siyu Chen, Beining Wu, Miao Lu et al.
Generalizable Motion Planning via Operator Learning
Sharath Matada, Luke Bhan, Yuanyuan Shi et al.
InstaRevive: One-Step Image Enhancement via Dynamic Score Matching
Yixuan Zhu, Haolin Wang, Ao Li et al.
Deriving Causal Order from Single-Variable Interventions: Guarantees & Algorithm
Mathieu Chevalley, Patrick Schwab, Arash Mehrjou
COFlowNet: Conservative Constraints on Flows Enable High-Quality Candidate Generation
Yudong Zhang, Xuan Yu, Xu Wang et al.
Continuous Exposure Learning for Low-light Image Enhancement using Neural ODEs
Donggoo Jung, Daehyun Kim, Tae Hyun Kim
REVISITING MULTI-PERMUTATION EQUIVARIANCE THROUGH THE LENS OF IRREDUCIBLE REPRESENTATIONS
Yonatan Sverdlov, Ido Springer, Nadav Dym
Cascading Reinforcement Learning
Yihan Du, R. Srikant, Wei Chen
Exact Community Recovery under Side Information: Optimality of Spectral Algorithms
Julia Gaudio, Nirmit Joshi
An Asynchronous Bundle Method for Distributed Learning Problems
Daniel Cederberg, Xuyang Wu, Stephen Boyd et al.
MIND over Body: Adaptive Thinking using Dynamic Computation
Mrinal Mathur, Barak Pearlmutter, Sergey Plis
Sample Efficient Myopic Exploration Through Multitask Reinforcement Learning with Diverse Tasks
Ziping Xu, Zifan Xu, Runxuan Jiang et al.
Content-Style Learning from Unaligned Domains: Identifiability under Unknown Latent Dimensions
Sagar Shrestha, Xiao Fu
PaLD: Detection of Text Partially Written by Large Language Models
Eric Lei, Hsiang Hsu, Chun-Fu Chen
Leave-One-Out Stable Conformal Prediction
Kiljae Lee, Yuan Zhang
Supervised and Semi-Supervised Diffusion Maps with Label-Driven Diffusion
Harel Mendelman, Ronen Talmon
An Agnostic View on the Cost of Overfitting in (Kernel) Ridge Regression
Lijia Zhou, James Simon, Gal Vardi et al.
SeedLM: Compressing LLM Weights into Seeds of Pseudo-Random Generators
Rasoul Shafipour, David Harrison, Maxwell Horton et al.
Shapley-Guided Utility Learning for Effective Graph Inference Data Valuation
Hongliang Chi, Qiong Wu, Zhengyi Zhou et al.
Learning to Generate Diverse Pedestrian Movements from Web Videos with Noisy Labels
Zhizheng Liu, Joe Lin, Wayne Wu et al.
Restyling Unsupervised Concept Based Interpretable Networks with Generative Models
Jayneel Parekh, Quentin Bouniot, Pavlo Mozharovskyi et al.
Group Ligands Docking to Protein Pockets
Jiaqi Guan, Jiahan Li, Xiangxin Zhou et al.
FOSI: Hybrid First and Second Order Optimization
Hadar Sivan, Moshe Gabel, Assaf Schuster
Order-aware Interactive Segmentation
Bin Wang, Anwesa Choudhuri, Meng Zheng et al.
Towards a Unified and Verified Understanding of Group-Operation Networks
Wilson Wu, Louis Jaburi, jacob drori et al.
Beyond Circuit Connections: A Non-Message Passing Graph Transformer Approach for Quantum Error Mitigation
Tianyi Bao, Xinyu Ye, Hang Ruan et al.
Quantifying Network Similarity using Graph Cumulants
Gecia Bravo-Hermsdorff, Lee M. Gunderson, Pierre-André Maugis et al.
Masked Distillation Advances Self-Supervised Transformer Architecture Search
Caixia Yan, Xiaojun Chang, Zhihui Li et al.
Graph Transformers Dream of Electric Flow
Xiang Cheng, Lawrence Carin, Suvrit Sra
Convex Formulations for Training Two-Layer ReLU Neural Networks
Karthik Prakhya, Tolga Birdal, Alp Yurtsever
Computational Explorations of Total Variation Distance
Arnab Bhattacharyya, Sutanu Gayen, Kuldeep S. Meel et al.
Adaptive Shrinkage Estimation for Personalized Deep Kernel Regression in Modeling Brain Trajectories
Vasiliki Tassopoulou, Haochang Shou, Christos Davatzikos
On Designing General and Expressive Quantum Graph Neural Networks with Applications to MILP Instance Representation
Xinyu Ye, Hao Xiong, Jianhao Huang et al.
Align With Purpose: Optimize Desired Properties in CTC Models with a General Plug-and-Play Framework
Eliya Segev, Maya Alroy, Ronen Katsir et al.
Integrating Protein Dynamics into Structure-Based Drug Design via Full-Atom Stochastic Flows
Xiangxin Zhou, Yi Xiao, Haowei Lin et al.
Toward Efficient Multi-Agent Exploration With Trajectory Entropy Maximization
Tianxu Li, Kun Zhu
For Better or For Worse? Learning Minimum Variance Features With Label Augmentation
Muthu Chidambaram, Rong Ge
Provably Reliable Conformal Prediction Sets in the Presence of Data Poisoning
Yan Scholten, Stephan Günnemann
Verifying Properties of Binary Neural Networks Using Sparse Polynomial Optimization
Jianting Yang, Srecko Durasinovic, Jean Bernard Lasserre 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.
Views Can Be Deceiving: Improved SSL Through Feature Space Augmentation
Kimia Hamidieh, Haoran Zhang, Swami Sankaranarayanan et al.
REBIND: Enhancing Ground-state Molecular Conformation Prediction via Force-Based Graph Rewiring
Taewon Kim, Hyunjin Seo, Sungsoo Ahn et al.
Self-Attention-Based Contextual Modulation Improves Neural System Identification
Isaac Lin, Tianye Wang, Shang Gao et al.
Learning from Imperfect Human Feedback: A Tale from Corruption-Robust Dueling
Yuwei Cheng, Fan Yao, Xuefeng Liu et al.
NetInfoF Framework: Measuring and Exploiting Network Usable Information
Meng-Chieh Lee, Haiyang Yu, Jian Zhang et al.
Swing-by Dynamics in Concept Learning and Compositional Generalization
Yongyi Yang, Core Francisco Park, Ekdeep Singh Lubana et al.
A Differentiable Rank-Based Objective for Better Feature Learning
Krunoslav Lehman Pavasovic, Giulio Biroli, Levent Sagun
Sample-Efficient Multi-Agent RL: An Optimization Perspective
Nuoya Xiong, Zhihan Liu, Zhaoran Wang et al.
Geometry-Aware Approaches for Balancing Performance and Theoretical Guarantees in Linear Bandits
Yuwei Luo, Mohsen Bayati
Generalization in VAE and Diffusion Models: A Unified Information-Theoretic Analysis
Qi Chen, Jierui Zhu, Florian Shkurti
Graph Neural Networks Can (Often) Count Substructures
Paolo Pellizzoni, Till Schulz, Karsten Borgwardt
MAGNet: Motif-Agnostic Generation of Molecules from Scaffolds
Leon Hetzel, Johanna Sommer, Bastian Rieck et al.
LLM-based Typed Hyperresolution for Commonsense Reasoning with Knowledge Bases
Armin Toroghi, Ali Pesaranghader, Tanmana Sadhu et al.
GLOMA: Global Video Text Spotting with Morphological Association
Han Wang, Yanjie Wang, Yang Li et al.
Learning mirror maps in policy mirror descent
Carlo Alfano, Sebastian Towers, Silvia Sapora et al.
A Multiscale Frequency Domain Causal Framework for Enhanced Pathological Analysis
Xiaoyu Cui, Weixing Chen, Jiandong Su
Durable Quantization Conditioned Misalignment Attack on Large Language Models
Peiran Dong, Haowei Li, Song Guo
Leveraging Low-Rank and Sparse Recurrent Connectivity for Robust Closed-Loop Control
Neehal Tumma, Mathias Lechner, Noel Loo et al.
Residual Deep Gaussian Processes on Manifolds
Kacper Wyrwal, Andreas Krause, Viacheslav (Slava) Borovitskiy
IV-mixed Sampler: Leveraging Image Diffusion Models for Enhanced Video Synthesis
Shitong Shao, zikai zhou, Lichen Bai et al.
PianoMotion10M: Dataset and Benchmark for Hand Motion Generation in Piano Performance
Qijun Gan, Song Wang, Shengtao Wu et al.
Cross-Attention Head Position Patterns Can Align with Human Visual Concepts in Text-to-Image Generative Models
Jungwon Park, Jungmin Ko, Dongnam Byun et al.
DynaVol: Unsupervised Learning for Dynamic Scenes through Object-Centric Voxelization
Yanpeng Zhao, Siyu Gao, Yunbo Wang et al.
Inner Information Analysis Algorithm for Deep Neural Network based on Community
Guipeng Lan, Shuai Xiao, Meng Xi et al.
Warm Diffusion: Recipe for Blur-Noise Mixture Diffusion Models
Hao-Chien Hsueh, Wen-Hsiao Peng, Ching-Chun Huang
Physiome-ODE: A Benchmark for Irregularly Sampled Multivariate Time-Series Forecasting Based on Biological ODEs
Christian Klötergens, Vijaya Krishna Yalavarthi, Randolf Scholz et al.
Optimistic Games for Combinatorial Bayesian Optimization with Application to Protein Design
Melis Ilayda Bal, Pier Giuseppe Sessa, Mojmir Mutny et al.
SparsyFed: Sparse Adaptive Federated Learning
Adriano Guastella, Lorenzo Sani, Alex Iacob et al.
Adversaries With Incentives: A Strategic Alternative to Adversarial Robustness
Maayan Ehrenberg, Roy Ganz, Nir Rosenfeld
Progressive Parameter Efficient Transfer Learning for Semantic Segmentation
Nan Zhou, Huiqun Wang, Yaoyan Zheng et al.
Improved Algorithms for Kernel Matrix-Vector Multiplication Under Sparsity Assumptions
Piotr Indyk, Michael Kapralov, Kshiteej Jitesh Sheth et al.
SAGEPhos: Sage Bio-Coupled and Augmented Fusion for Phosphorylation Site Detection
Jingjie Zhang, Hanqun Cao, Zijun Gao et al.
Prevalence of Negative Transfer in Continual Reinforcement Learning: Analyses and a Simple Baseline
Hongjoon Ahn, Jinu Hyeon, Youngmin Oh et al.
Isometric Regularization for Manifolds of Functional Data
Hyeongjun Heo, Seonghun Oh, JaeYong Lee 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.
Privacy-Aware Lifelong Learning
Ozan Özdenizci, Elmar Rueckert, Robert Legenstein
RFMamba: Frequency-Aware State Space Model for RF-Based Human-Centric Perception
Rui Zhang, Ruixu Geng, Yadong Li et al.
The Computational Complexity of Positive Non-Clashing Teaching in Graphs
Robert Ganian, Liana Khazaliya, Fionn Mc Inerney et al.
Diffusion Sampling with Momentum for Mitigating Divergence Artifacts
Suttisak Wisadwongsa, Worameth Chinchuthakun, Pramook Khungurn et al.
PvNeXt: Rethinking Network Design and Temporal Motion for Point Cloud Video Recognition
Jie Wang, Tingfa Xu, Lihe Ding et al.
Communication-Efficient Federated Non-Linear Bandit Optimization
Chuanhao Li, Chong Liu, Yu-Xiang Wang
Test-time Adaptation for Image Compression with Distribution Regularization
Kecheng Chen, Pingping Zhang, Tiexin Qin et al.
Parameter Expanded Stochastic Gradient Markov Chain Monte Carlo
Hyunsu Kim, Giung Nam, Chulhee Yun et al.
OMG: Opacity Matters in Material Modeling with Gaussian Splatting
Silong Yong, Venkata Nagarjun Pudureddiyur Manivannan, Bernhard Kerbl et al.
On the Almost Sure Convergence of the Stochastic Three Points Algorithm
Taha EL BAKKALI EL KADI, Omar Saadi
Test-Time Adaptation for Combating Missing Modalities in Egocentric Videos
Merey Ramazanova, Alejandro Pardo, Bernard Ghanem et al.
The adaptive complexity of parallelized log-concave sampling
Huanjian Zhou, Baoxiang Wang, Masashi Sugiyama
QPM: Discrete Optimization for Globally Interpretable Image Classification
Thomas Norrenbrock, Timo Kaiser, Sovan Biswas et al.
T2V-Turbo-v2: Enhancing Video Model Post-Training through Data, Reward, and Conditional Guidance Design
Jiachen Li, Qian Long, Jian (Skyler) Zheng et al.
Unified Projection-Free Algorithms for Adversarial DR-Submodular Optimization
Mohammad Pedramfar, Yididiya Nadew, Chris Quinn et al.
Solving Differential Equations with Constrained Learning
Viggo Moro, Luiz Chamon
Are Transformers Able to Reason by Connecting Separated Knowledge in Training Data?
Yutong Yin, Zhaoran Wang
Towards Faster Decentralized Stochastic Optimization with Communication Compression
Rustem Islamov, Yuan Gao, Sebastian Stich
Decoupling regularization from the action space
Sobhan Mohammadpour, Emma Frejinger, Pierre-Luc Bacon
InvestESG: A multi-agent reinforcement learning benchmark for studying climate investment as a social dilemma
Xiaoxuan Hou, Jiayi Yuan, Joel Z Leibo et al.
ZeroDiff: Solidified Visual-semantic Correlation in Zero-Shot Learning
Zihan Ye, Shreyank Gowda, Shiming Chen et al.
Recognize Any Surgical Object: Unleashing the Power of Weakly-Supervised Data
Jiajie Li, Brian Quaranto, Chenhui Xu et al.
Learning 3D Perception from Others' Predictions
Jinsu Yoo, Zhenyang Feng, Tai-Yu Pan et al.
Protecting against simultaneous data poisoning attacks
Neel Alex, Muhammad Shoaib Ahmed Siddiqui, Amartya Sanyal et al.