Most Cited ICML "transposable sparsity" Papers

Continual Generalized Category Discovery: Learning and Forgetting from a Bayesian Perspective

Hao Dai, Jagmohan Chauhan

Adversarial Inputs for Linear Algebra Backends

Jonas Möller, Lukas Pirch, Felix Weissberg et al.

Optimization for Neural Operators can Benefit from Width

Pedro Cisneros-Velarde, Bhavesh Shrimali, Arindam Banerjee

Position: LLMs Can’t Plan, But Can Help Planning in LLM-Modulo Frameworks

Subbarao Kambhampati, Karthik Valmeekam, Lin Guan et al.

New Sample Complexity Bounds for Sample Average Approximation in Heavy-Tailed Stochastic Programming

Hongcheng Liu, Jindong Tong

Understanding Complexity in VideoQA via Visual Program Generation

Cristobal Eyzaguirre, Igor Vasiljevic, Achal Dave et al.

Feature Reuse and Scaling: Understanding Transfer Learning with Protein Language Models

Francesca-Zhoufan Li, Ava Amini, Yisong Yue et al.

In-Context Adaptation to Concept Drift for Learned Database Operations

Jiaqi Zhu, Shaofeng Cai, Shen et al.

Not All Wrong is Bad: Using Adversarial Examples for Unlearning

Ali Ebrahimpour-Boroojeny, Hari Sundaram, Varun Chandrasekaran

UltraTWD: Optimizing Ultrametric Trees for Tree-Wasserstein Distance

Fangchen Yu, Yanzhen Chen, Jiaxing Wei et al.

Towards Understanding Gradient Dynamics of the Sliced-Wasserstein Distance via Critical Point Analysis

Christophe Vauthier, Anna Korba, Quentin Mérigot

Towards Global-level Mechanistic Interpretability: A Perspective of Modular Circuits of Large Language Models

Yinhan He, Wendy Zheng, Yushun Dong et al.

A Generic Family of Graphical Models: Diversity, Efficiency, and Heterogeneity

Yufei Huang, Changhu Wang, Junjie Tang et al.

Improved Learning via k-DTW: A Novel Dissimilarity Measure for Curves

Amer Krivosija, Alexander Munteanu, André Nusser et al.

Alberta Wells Dataset: Pinpointing Oil and Gas Wells from Satellite Imagery

Pratinav Seth, Michelle Lin, BREFO YAW et al.

Lean and Mean Adaptive Optimization via Subset-Norm and Subspace-Momentum with Convergence Guarantees

Thien Nguyen, Huy Nguyen

NeuralCohort: Cohort-aware Neural Representation Learning for Healthcare Analytics

Changshuo Liu, Lingze Zeng, Kaiping Zheng et al.

A Cross Modal Knowledge Distillation & Data Augmentation Recipe for Improving Transcriptomics Representations through Morphological Features

Ihab Bendidi, Yassir El Mesbahi, Alisandra Denton et al.

Graph Minimum Factor Distance and Its Application to Large-Scale Graph Data Clustering

Jicong Fan

Instance Correlation Graph-based Naive Bayes

Chengyuan Li, Liangxiao Jiang, Wenjun Zhang et al.

Integration-free Kernels for Equivariant Gaussian Process Modelling

Tim Steinert, David Ginsbourger, August Lykke-Møller et al.

Ameliorate Spurious Correlations in Dataset Condensation

Jiaxing Cui, Ruochen Wang, Yuanhao Xiong et al.

Adapting While Learning: Grounding LLMs for Scientific Problems with Tool Usage Adaptation

Bohan Lyu, Yadi Cao, Duncan Watson-Parris et al.

Data-Driven Selection of Instrumental Variables for Additive Nonlinear, Constant Effects Models

Xichen Guo, Feng Xie, Yan Zeng et al.

Diversified Flow Matching with Translation Identifiability

Sagar Shrestha, Xiao Fu

How do Transformers Perform In-Context Autoregressive Learning ?

Michael Sander, Raja Giryes, Taiji Suzuki et al.

Vision Transformers as Probabilistic Expansion from Learngene

Qiufeng Wang, Xu Yang, Haokun Chen et al.

Efficient and Privacy-Preserving Soft Prompt Transfer for LLMs

Xun Wang, Jing Xu, Franziska Boenisch et al.

Learning to Quantize for Training Vector-Quantized Networks

Peijia Qin, Jianguo Zhang

Generative Point Cloud Registration

Haobo Jiang, Jin Xie, jian Yang et al.

MTSTRec: Multimodal Time-Aligned Shared Token Recommender

Ming-Yi Hong, Yen-Jung Hsu, Miao-Chen Chiang et al.

Modeling Language Tokens as Functionals of Semantic Fields

Zhengqi Pei, Anran Zhang, Shuhui Wang et al.

Inferring Change Points in High-Dimensional Linear Regression via Approximate Message Passing

Gabriel Arpino, Xiaoqi Liu, Ramji Venkataramanan

MIRROR: Make Your Object-Level Multi-View Generation More Consistent with Training-Free Rectification

TianChi Xing, Bonan Li, Congying Han et al.

Score-Based Causal Discovery of Latent Variable Causal Models

Ignavier Ng, Xinshuai Dong, Haoyue Dai et al.

ENAHPool: The Edge-Node Attention-based Hierarchical Pooling for Graph Neural Networks

Zhehan Zhao, Lu Bai, Lixin Cui et al.

Divide and Conquer: Exploring Language-centric Tree Reasoning for Video Question-Answering

Zhaohe Liao, Jiangtong Li, Siyu Sun et al.

Enhancing Parallelism in Decentralized Stochastic Convex Optimization

Ofri Eisen, Ron Dorfman, Kfir Levy

Surrogate Prompt Learning: Towards Efficient and Diverse Prompt Learning for Vision-Language Models

Liangchen Liu, Nannan Wang, Xi Yang et al.

FedPHA: Federated Prompt Learning for Heterogeneous Client Adaptation

Chengying Fang, Wenke Huang, Guancheng Wan et al.

Strategic Planning: A Top-Down Approach to Option Generation

Max Ruiz Luyten, Antonin Berthon, Mihaela van der Schaar

Vector Grimoire: Codebook-based Shape Generation under Raster Image Supervision

Marco Cipriano, Moritz Feuerpfeil, Gerard de Melo

MP-Nav: Enhancing Data Poisoning Attacks against Multimodal Learning

Jingfeng Zhang, Prashanth Krishnamurthy, Naman Patel et al.

Position: Deep Learning is Not So Mysterious or Different

Andrew Wilson

Position: Truly Self-Improving Agents Require Intrinsic Metacognitive Learning

Tennison Liu, Mihaela van der Schaar

Position: It Is Time We Test Neural Computation In Vitro

Frithjof Gressmann, Ashley Chen, Lily Xie et al.

Multi-Timescale Dynamics Model Bayesian Optimization for Plasma Stabilization in Tokamaks

Rohit Sonker, Alexandre Capone, Andrew Rothstein et al.

Position: Graph Matching Systems Deserve Better Benchmarks

Indradyumna Roy, Saswat Meher, Eeshaan Jain et al.

Position: The Right to AI

Rashid Mushkani, Hugo Berard, Allison Cohen et al.

Position: Retrieval-augmented systems can be dangerous medical communicators

Lionel Wong, Ayman Ali, Raymond M Xiong et al.

Position: AI Should Not Be An Imitation Game: Centaur Evaluations

Andreas Haupt, Erik Brynjolfsson

Position: LLMs Need a Bayesian Meta-Reasoning Framework for More Robust and Generalizable Reasoning

Hanqi Yan, Linhai Zhang, Jiazheng Li et al.

Position: AI's growing due process problem

Sunayana Rane

Position: Probabilistic Modelling is Sufficient for Causal Inference

Bruno Mlodozeniec, David Krueger, Richard E Turner

Improving the Continuity of Goal-Achievement Ability via Policy Self-Regularization for Goal-Conditioned Reinforcement Learning

Xudong Gong, Sen Yang, Feng Dawei et al.

Position: Rethinking Explainable Machine Learning as Applied Statistics

Sebastian Bordt, Eric Raidl, Ulrike Luxburg

Position: Challenges and Future Directions of Data-Centric AI Alignment

Min-Hsuan Yeh, Jeffrey Wang, Xuefeng Du et al.

Position: Generative AI Regulation Can Learn from Social Media Regulation

Ruth Elisabeth Appel

Position: Iterative Online-Offline Joint Optimization is Needed to Manage Complex LLM Copyright Risks

Yanzhou Pan, Jiayi Chen, Jiamin Chen et al.

Ex-VAD: Explainable Fine-grained Video Anomaly Detection Based on Visual-Language Models

Chao Huang, Yushu Shi, Jie Wen et al.

Position: Humanity Faces Existential Risk from Gradual Disempowerment

Jan Kulveit, Raymond Douglas, Nora Ammann et al.

Position: Machine Learning Models Have a Supply Chain Problem

Sarah Meiklejohn, Hayden Blauzvern, Mihai Maruseac et al.

Heads up! Large Language Models Can Perform Tasks Without Your Instruction via Selective Attention Head Masking

Senyu Han, Hongchuan Zeng, Kai Yu et al.

QPRL : Learning Optimal Policies with Quasi-Potential Functions for Asymmetric Traversal

Jumman Hossain, Nirmalya Roy

EnsLoss: Stochastic Calibrated Loss Ensembles for Preventing Overfitting in Classification

Ben Dai

Dimension-Free Adaptive Subgradient Methods with Frequent Directions

Sifan Yang, Yuanyu Wan, Peijia Li et al.

Multi-objective Linear Reinforcement Learning with Lexicographic Rewards

Bo Xue, Dake Bu, Ji Cheng et al.

Tractable Transformers for Flexible Conditional Generation

Anji Liu, Xuejie Liu, Dayuan Zhao et al.

TtBA: Two-third Bridge Approach for Decision-Based Adversarial Attack

Feiyang Wang, Xingquan Zuo, Hai Huang et al.

Feature out! Let Raw Image as Your Condition for Blind Face Restoration

XINMIN QIU, Gege Chen, Bonan Li et al.

AKORN: Adaptive Knots generated Online for RegressioN splines

Sunil Madhow, Dheeraj Baby, Yu-Xiang Wang

Curvature-aware Graph Attention for PDEs on Manifolds

Yunfeng Liao, Jiawen Guan, Xiucheng Li

Volume-Aware Distance for Robust Similarity Learning

Shuo Chen, Chen Gong, Jun Li et al.

R*: Efficient Reward Design via Reward Structure Evolution and Parameter Alignment Optimization with Large Language Models

Pengyi Li, Jianye Hao, Hongyao Tang et al.

Permutation-Free High-Order Interaction Tests

Zhaolu Liu, Robert Peach, Mauricio Barahona

An Error Analysis of Flow Matching for Deep Generative Modeling

Zhengyu Zhou, Weiwei Liu

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Position: Towards Unified Alignment Between Agents, Humans, and Environment

Zonghan Yang, an liu, Zijun Liu et al.

Consistent Submodular Maximization

PAUL DUETTING, Federico Fusco, Silvio Lattanzi et al.

Relaxing the Accurate Imputation Assumption in Doubly Robust Learning for Debiased Collaborative Filtering

Haoxuan Li, Chunyuan Zheng, Shuyi Wang et al.

Multi-Modal Object Re-identification via Sparse Mixture-of-Experts

Yingying Feng, Jie Li, Chi Xie et al.

Model-based Reinforcement Learning for Confounded POMDPs

Mao Hong, Zhengling Qi, Yanxun Xu

Position: A Call for Embodied AI

Giuseppe Paolo, Jonas Gonzalez-Billandon, Balázs Kégl

Constrained Exploitability Descent: An Offline Reinforcement Learning Method for Finding Mixed-Strategy Nash Equilibrium

Runyu Lu, Yuanheng Zhu, Dongbin Zhao

WARM: On the Benefits of Weight Averaged Reward Models

Alexandre Rame, Nino Vieillard, Léonard Hussenot et al.

Counting atoms faster: policy-based nuclear magnetic resonance pulse sequencing for atomic abundance measurement

Rohan Shenoy, Evan Coleman, Hans Gaensbauer et al.

LLMs Can Reason Faster Only If We Let Them

Bilgehan Sel, Lifu Huang, Naren Ramakrishnan et al.

Kernel-Based Evaluation of Conditional Biological Sequence Models

Pierre Glaser, Steffan Paul, Alissa M. Hummer et al.

Optimal Information Retention for Time-Series Explanations

Jinghang Yue, Jing Wang, Lu Zhang et al.

Learning Associative Memories with Gradient Descent

Vivien Cabannnes, Berfin Simsek, Alberto Bietti

Calibration Bottleneck: Over-compressed Representations are Less Calibratable

Deng-Bao Wang, Min-Ling Zhang

Noise-Guided Predicate Representation Extraction and Diffusion-Enhanced Discretization for Scene Graph Generation

Guoqing Zhang, Shichao Kan, Fanghui Zhang et al.

RuleAdapter: Dynamic Rules for training Safety Reward Models in RLHF

Xiaomin Li, Mingye Gao, Zhiwei Zhang et al.

Adaptive Localization of Knowledge Negation for Continual LLM Unlearning

Abudukelimu Wuerkaixi, Qizhou Wang, Sen Cui et al.

Heterogeneous Sufficient Dimension Reduction and Subspace Clustering

Lei Yan, Xin Zhang, Qing Mai

Deep Principal Support Vector Machines for Nonlinear Sufficient Dimension Reduction

YinFeng Chen, Jin Liu, Rui Qiu

Bayesian Inference for Correlated Human Experts and Classifiers

Markelle Kelly, Alex Boyd, Samuel Showalter et al.

Distribution Alignment Optimization through Neural Collapse for Long-tailed Classification

Jintong Gao, He Zhao, Dandan Guo et al.

How Learning by Reconstruction Produces Uninformative Features For Perception

Randall Balestriero, Yann LeCun

Distributed Parallel Gradient Stacking(DPGS): Solving Whole Slide Image Stacking Challenge in Multi-Instance Learning

Boyuan Wu, wang, Xianwei Lin et al.

Learning Condensed Graph via Differentiable Atom Mapping for Reaction Yield Prediction

Ankit Ghosh, Gargee Kashyap, Sarthak Mittal et al.

Planning, Fast and Slow: Online Reinforcement Learning with Action-Free Offline Data via Multiscale Planners

Chengjie Wu, Hao Hu, yiqin yang et al.

Policy Optimization for CMDPs with Bandit Feedback: Learning Stochastic and Adversarial Constraints

Francesco Emanuele Stradi, Anna Lunghi, Matteo Castiglioni et al.

Plausible Token Amplification for Improving Accuracy of Differentially Private In-Context Learning Based on Implicit Bayesian Inference

Yusuke Yamasaki, Kenta Niwa, Daiki Chijiwa et al.

Gamma Distribution PCA-Enhanced Feature Learning for Angle-Robust SAR Target Recognition

Chong Zhang, Peng Zhang, Mengke Li

SNS-Bench: Defining, Building, and Assessing Capabilities of Large Language Models in Social Networking Services

Hongcheng Guo, Yue Wang, Shaosheng Cao et al.

Incorporating Information into Shapley Values: Reweighting via a Maximum Entropy Approach

Darya Biparva, Donatello Materassi

Are High-Quality AI-Generated Images More Difficult for Models to Detect?

Yao Xiao, Binbin Yang, Weiyan Chen et al.

Agent Reviewers: Domain-specific Multimodal Agents with Shared Memory for Paper Review

Kai Lu, Shixiong Xu, Jinqiu Li et al.

HiRemate: Hierarchical Approach for Efficient Re-materialization of Neural Networks

Julia Gusak, Xunyi Zhao, Théotime Le Hellard et al.

High Probability Bound for Cross-Learning Contextual Bandits with Unknown Context Distributions

Ruiyuan Huang, Zengfeng Huang

Ensemble Pruning for Out-of-distribution Generalization

Fengchun Qiao, Xi Peng

Diffuse, Sample, Project: Plug-And-Play Controllable Graph Generation

Kartik Sharma, Srijan Kumar, Rakshit Trivedi

On the Asymptotic Distribution of the Minimum Empirical Risk

Jacob Westerhout, TrungTin Nguyen, Xin Guo et al.

Approximate Forest Completion and Learning-Augmented Algorithms for Metric Minimum Spanning Trees

Nate Veldt, Thomas Stanley, Benjamin Priest et al.

Bridging Protein Sequences and Microscopy Images with Unified Diffusion Models

Dihan Zheng, Bo Huang

Linear Mode Connectivity between Multiple Models modulo Permutation Symmetries

Akira Ito, Masanori Yamada, Atsutoshi Kumagai

Stream-level Flow Matching with Gaussian Processes

Ganchao Wei, Li Ma

Language Agent Tree Search Unifies Reasoning, Acting, and Planning in Language Models

Andy Zhou, Kai Yan, Michal Shlapentokh-Rothman et al.

Finite-Time Convergence Rates in Stochastic Stackelberg Games with Smooth Algorithmic Agents

Eric Frankel, Kshitij Kulkarni, Dmitriy Drusvyatskiy et al.

Beyond Task-Specific Reasoning: A Unified Conditional Generative Framework for Abstract Visual Reasoning

Fan Shi, Bin Li, Xiangyang Xue

Measures of diversity and space-filling designs for categorical data

AstraZeneca Pharmaceutica, Emilio Domínguez-Sánchez, Merwan Barlier et al.

Compact Matrix Quantum Group Equivariant Neural Networks

Edward Pearce-Crump

Conditional Common Entropy for Instrumental Variable Testing and Partial Identification

Ziwei Jiang, Murat Kocaoglu

Benchmarking Deletion Metrics with the Principled Explanations

Yipei Wang, Xiaoqian Wang

Online Matrix Completion: A Collaborative Approach with Hott Items

Dheeraj Baby, Soumyabrata Pal

On the Convergence of Continuous Single-timescale Actor-critic

Xuyang Chen, Lin Zhao

Benign Overfitting in Adversarial Training of Neural Networks

Yunjuan Wang, Kaibo Zhang, Raman Arora

Semantics-aware Test-time Adaptation for 3D Human Pose Estimation

Qiuxia Lin, Glory Rongyu CHEN, Kerui Gu et al.

Improved Expressivity of Hypergraph Neural Networks through High-Dimensional Generalized Weisfeiler-Leman Algorithms

Detian Zhang, Zhang Chengqiang, Yanghui Rao et al.

Stealix: Model Stealing via Prompt Evolution

Zhixiong Zhuang, Hui-Po Wang, Irina Nicolae et al.

Privacy-Shielded Image Compression: Defending Against Exploitation from Vision-Language Pretrained Models

Xuelin Shen, Jiayin Xu, Kangsheng Yin et al.

A Classification View on Meta Learning Bandits

Mirco Mutti, Jeongyeol Kwon, Shie Mannor et al.

Minimax Optimal Regret Bound for Reinforcement Learning with Trajectory Feedback

Zihan Zhang, Yuxin Chen, Jason Lee et al.

Stable Fair Graph Representation Learning with Lipschitz Constraint

Qiang Chen, Zhongze Wu, Xiu Su et al.

Can Biologically Plausible Temporal Credit Assignment Rules Match BPTT for Neural Similarity? E-prop as an Example

Yuhan Helena Liu, Guangyu Robert Yang, Christopher Cueva

Dataflow-Guided Neuro-Symbolic Language Models for Type Inference

gen li, Yao Wan, Hongyu Zhang et al.

Vector Quantization Pretraining for EEG Time Series with Random Projection and Phase Alignment

Haokun Gui, Xiucheng Li, Xinyang Chen

An Efficient Pruner for Large Language Model with Theoretical Guarantee

Canhong Wen, Yihong Zuo, Wenliang Pan

Hi-Patch: Hierarchical Patch GNN for Irregular Multivariate Time Series

Yicheng Luo, Bowen Zhang, Zhen Liu et al.

GHOST: Generalizable One-Shot Federated Graph Learning with Proxy-Based Topology Knowledge Retention

Jiaru Qian, Guancheng Wan, Wenke Huang et al.

Evaluating Instrument Validity using the Principle of Independent Mechanisms

Patrick F. Burauel

Enhancing Logits Distillation with Plug&Play Kendall's $\tau$ Ranking Loss

Yuchen Guan, Runxi Cheng, Kang Liu et al.

Primitive Vision: Improving Diagram Understanding in MLLMs

Shan Zhang, Aotian Chen, Yanpeng Sun et al.

Competing Bandits in Matching Markets via Super Stability

Soumya Basu

Faster Rates for Private Adversarial Bandits

Hilal Asi, Vinod Raman, Kunal Talwar

On Positivity Condition for Causal Inference

Inwoo Hwang, Yesong Choe, Yeahoon Kwon et al.

SING: Spatial Context in Large Language Model for Next-Gen Wearables

Ayushi Mishra, Yang Bai, Priyadarshan Narayanasamy et al.

Curvature Enhanced Data Augmentation for Regression

Ilya Kaufman, Omri Azencot

A Unified Framework for Generalization Error Analysis of Learning with Arbitrary Discrete Weak Features

Kosuke Sugiyama, Masato Uchida

The Expressive Power of Path-Based Graph Neural Networks

Caterina Graziani, Tamara Drucks, Fabian Jogl et al.

Stray Intrusive Outliers-Based Feature Selection on Intra-Class Asymmetric Instance Distribution or Multiple High-Density Clusters

Lixin Yuan, Yirui Wu, WENXIAO ZHANG et al.

Controllable Data Generation with Hierarchical Neural Representations

Sheyang Tang, xiaoyu xu, Jiayan Qiu et al.

A Generalization Theory for Zero-Shot Prediction

Ronak Mehta, Zaid Harchaoui

Position: Technical Research and Talent is Needed for Effective AI Governance

Anka Reuel, Lisa Soder, Benjamin Bucknall et al.

Robust Secure Swap: Responsible Face Swap With Persons of Interest Redaction and Provenance Traceability

Yunshu Dai, Jianwei Fei, Fangjun Huang et al.

Practical Hamiltonian Monte Carlo on Riemannian Manifolds via Relativity Theory

Kai Xu, Hong Ge

On Learning Parallel Pancakes with Mostly Uniform Weights

Ilias Diakonikolas, Daniel Kane, Sushrut Karmalkar et al.

Fair Clustering via Alignment

Kunwoong Kim, Jihu Lee, Sangchul Park et al.

Gradient Inversion of Multimodal Models

Omri Ben Hemo, Alon Zolfi, Oryan Yehezkel et al.

From Coarse to Fine: Enable Comprehensive Graph Self-supervised Learning with Multi-granular Semantic Ensemble

Qianlong Wen, Mingxuan Ju, Zhongyu Ouyang et al.

ENSUR: Equitable and Statistically Unbiased Recommendation

Nitin Bisht, Xiuwen Gong, Guandong Xu

Sparser, Better, Deeper, Stronger: Improving Static Sparse Training with Exact Orthogonal Initialization

Aleksandra I. Nowak, Łukasz Gniecki, Filip Szatkowski et al.

Safe Exploration in Dose Finding Clinical Trials with Heterogeneous Participants

Isabel Chien, Wessel Bruinsma, Javier Gonzalez et al.

Rethinking Causal Ranking: A Balanced Perspective on Uplift Model Evaluation

Minqin Zhu, Zexu Sun, Ruoxuan Xiong et al.

Low-Rank Thinning

Annabelle Carrell, Albert Gong, Abhishek Shetty et al.

Deep Electromagnetic Structure Design Under Limited Evaluation Budgets

Shijian Zheng, Fangxiao Jin, Shuhai Zhang et al.

Divide and Conquer: Learning Label Distribution with Subtasks

Haitao Wu, Weiwei Li, Xiuyi Jia

PRIME: Deep Imbalanced Regression with Proxies

Jongin Lim, Sucheol Lee, Daeho Um et al.

PPDiff: Diffusing in Hybrid Sequence-Structure Space for Protein-Protein Complex Design

Zhenqiao Song, Tianxiao Li, Lei Li et al.

Joker: Joint Optimization Framework for Lightweight Kernel Machines

Junhong Zhang, Zhihui Lai

Agnostic Interactive Imitation Learning: New Theory and Practical Algorithms

Yichen Li, Chicheng Zhang

On the Generalization Ability of Next-Token-Prediction Pretraining

Zhihao Li, Xue JIANG, Liyuan Liu et al.

Matrix Completion with Incomplete Side Information via Orthogonal Complement Projection

Gengshuo Chang, Wei Zhang, Lehan Zhang

How does Labeling Error Impact Contrastive Learning? A Perspective from Data Dimensionality Reduction

Jun Chen, Hong Chen, Yonghua Yu et al.

MIPT: Multilevel Informed Prompt Tuning for Robust Molecular Property Prediction

Yeyun Chen, Jiangming Shi

Leveraging Attractor Dynamics in Spatial Navigation for Better Language Parsing

Xiaolong Zou, Xingxing Cao, Xiaojiao Yang et al.

Calibrated Value-Aware Model Learning with Probabilistic Environment Models

Claas Voelcker, Anastasiia Pedan, Arash Ahmadian et al.

Closing the Gap: Achieving Global Convergence (Last Iterate) of Actor-Critic under Markovian Sampling with Neural Network Parametrization

Mudit Gaur, Amrit Singh Bedi, Di Wang et al.

Importance Sampling for Nonlinear Models

Prakash Palanivelu Rajmohan, Fred Roosta

Unbiased Multi-Label Learning from Crowdsourced Annotations

Mingxuan Xia, Zenan Huang, Runze Wu et al.

Position: Evolving AI Collectives Enhance Human Diversity and Enable Self-Regulation

Shiyang Lai, Yujin Potter, Junsol Kim et al.

Revisiting Neural Networks for Few-Shot Learning: A Zero-Cost NAS Perspective

Haidong Kang

Learning Scale-Aware Spatio-temporal Implicit Representation for Event-based Motion Deblurring

Wei Yu, Jianing Li, Shengping Zhang et al.

Mind the Boundary: Coreset Selection via Reconstructing the Decision Boundary

Shuo Yang, Zhe Cao, Sheng Guo et al.

Position: Standardization of Behavioral Use Clauses is Necessary for the Adoption of Responsible Licensing of AI

Daniel McDuff, Tim Korjakow, Scott Cambo et al.

Maximum Update Parametrization and Zero-Shot Hyperparameter Transfer for Fourier Neural Operators

Shanda Li, Shinjae Yoo, Yiming Yang

Irregular Multivariate Time Series Forecasting: A Transformable Patching Graph Neural Networks Approach

Weijia Zhang, Chenlong Yin, Hao Liu et al.

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I. Arce, Emiliano Kargieman, G. Richarte et al.

Mean Field Langevin Actor-Critic: Faster Convergence and Global Optimality beyond Lazy Learning

Kakei Yamamoto, Kazusato Oko, Zhuoran Yang et al.

Rethinking the Temperature for Federated Heterogeneous Distillation

Fan Qi, Daxu Shi, Chuokun Xu et al.

Elucidating Flow Matching ODE Dynamics via Data Geometry and Denoisers

Zhengchao Wan, Qingsong Wang, Gal Mishne et al.

Global curvature for second-order optimization of neural networks

Alberto Bernacchia

Policy-Regret Minimization in Markov Games with Function Approximation

Thanh Nguyen-Tang, Raman Arora

Multi-Track Message Passing: Tackling Oversmoothing and Oversquashing in Graph Learning via Preventing Heterophily Mixing

Hongbin Pei, Yu Li, Huiqi Deng et al.

Unified Analysis of Continuous Weak Features Learning with Applications to Learning from Missing Data

Kosuke Sugiyama, Masato Uchida

Learning Bayesian Nash Equilibrium in Auction Games via Approximate Best Response

Kexin Huang, Ziqian Chen, xue wang et al.

Prometheus: Out-of-distribution Fluid Dynamics Modeling with Disentangled Graph ODE

Hao Wu, Huiyuan Wang, kun wang et al.

Identifiable Object Representations under Spatial Ambiguities

Avinash Kori, Francesca Toni, Ben Glocker

Certifiably Robust Model Evaluation in Federated Learning under Meta-Distributional Shifts

Amir Najafi, Samin Mahdizadeh Sani, Farzan Farnia