Most Cited ICML "behaviour policy modes" Papers

Lie Neurons: Adjoint-Equivariant Neural Networks for Semisimple Lie Algebras

Tzu-Yuan Lin, Minghan Zhu, Maani Ghaffari

Enforcing Latent Euclidean Geometry in Single-Cell VAEs for Manifold Interpolation

Alessandro Palma, Sergei Rybakov, Leon Hetzel et al.

CABS: Conflict-Aware and Balanced Sparsification for Enhancing Model Merging

Zongzhen Yang, Binhang Qi, Hailong Sun et al.

M3-JEPA: Multimodal Alignment via Multi-gate MoE based on the Joint-Embedding Predictive Architecture

Hongyang Lei, Xiaolong Cheng, Qi Qin et al.

AdaSplash: Adaptive Sparse Flash Attention

Nuno Gonçalves, Marcos V. Treviso, Andre Martins

DMOSpeech: Direct Metric Optimization via Distilled Diffusion Model in Zero-Shot Speech Synthesis

Yinghao Li, Rithesh Kumar, Zeyu Jin

Unraveling the Impact of Heterophilic Structures on Graph Positive-Unlabeled Learning

Yuhao Wu, Jiangchao Yao, Bo Han et al.

KnowFormer: Revisiting Transformers for Knowledge Graph Reasoning

Junnan Liu, Qianren Mao, Weifeng Jiang et al.

Test-Time Training Provably Improves Transformers as In-context Learners

Halil Alperen Gozeten, Muhammed Emrullah Ildiz, Xuechen Zhang et al.

Parsimonious Learning-Augmented Approximations for Dense Instances of $\mathcal{NP}$-hard Problems

Evripidis Bampis, Bruno Escoffier, Michalis Xefteris

Symmetric Matrix Completion with ReLU Sampling

Huikang Liu, Peng Wang, Longxiu Huang et al.

Confidence-aware Contrastive Learning for Selective Classification

Yu-Chang Wu, Shen-Huan Lyu, Haopu Shang et al.

In-Context Learning and Occam's Razor

Eric Elmoznino, Tom Marty, Tejas Kasetty et al.

Probabilistic Constrained Reinforcement Learning with Formal Interpretability

YANRAN WANG, QIUCHEN QIAN, David Boyle

Sliding Puzzles Gym: A Scalable Benchmark for State Representation in Visual Reinforcement Learning

Bryan L. M. de Oliveira, Luana G. B. Martins, Bruno Brandão et al.

Fast and Low-Cost Genomic Foundation Models via Outlier Removal

Haozheng Luo, Chenghao Qiu, Maojiang Su et al.

The Emperor's New Clothes in Benchmarking? A Rigorous Examination of Mitigation Strategies for LLM Benchmark Data Contamination

Yifan Sun, Han Wang, Dongbai Li et al.

LIFT the Veil for the Truth: Principal Weights Emerge after Rank Reduction for Reasoning-Focused Supervised Fine-Tuning

Zihang Liu, Tianyu Pang, Oleg Balabanov et al.

PID: Prompt-Independent Data Protection Against Latent Diffusion Models

Ang Li, Yichuan Mo, Mingjie Li et al.

Large Language Models to Diffusion Finetuning

Edoardo Cetin, Tianyu Zhao, Yujin Tang

Multi-Region Markovian Gaussian Process: An Efficient Method to Discover Directional Communications Across Multiple Brain Regions

Weihan Li, Chengrui Li, Yule Wang et al.

Promises and Pitfalls of Generative Masked Language Modeling: Theoretical Framework and Practical Guidelines

Yuchen Li, Alexandre Kirchmeyer, Aashay Mehta et al.

When Diffusion Models Memorize: Inductive Biases in Probability Flow of Minimum-Norm Shallow Neural Nets

Chen Zeno, Hila Manor, Gregory Ongie et al.

GaussMarker: Robust Dual-Domain Watermark for Diffusion Models

Kecen Li, Zhicong Huang, Xinwen Hou et al.

LOB-Bench: Benchmarking Generative AI for Finance - an Application to Limit Order Book Data

Peer Nagy, Sascha Frey, Kang Li et al.

Self-Consuming Generative Models with Adversarially Curated Data

Xiukun Wei, Xueru Zhang

Pi-DUAL: Using privileged information to distinguish clean from noisy labels

Ke Wang, Guillermo Ortiz-Jimenez, Rodolphe Jenatton et al.

Open Ad Hoc Teamwork with Cooperative Game Theory

Jianhong Wang, Yang Li, Yuan Zhang et al.

RL-CFR: Improving Action Abstraction for Imperfect Information Extensive-Form Games with Reinforcement Learning

Boning Li, Zhixuan Fang, Longbo Huang

Automatically Identify and Rectify: Robust Deep Contrastive Multi-view Clustering in Noisy Scenarios

xihong yang, Siwei Wang, Fangdi Wang et al.

On the Vulnerability of Applying Retrieval-Augmented Generation within Knowledge-Intensive Application Domains

Xun Xian, Ganghua Wang, Xuan Bi et al.

DipLLM: Fine-Tuning LLM for Strategic Decision-making in Diplomacy

Kaixuan Xu, Jiajun Chai, Sicheng Li et al.

Geometry-Calibrated DRO: Combating Over-Pessimism with Free Energy Implications

Jiashuo Liu, Jiayun Wu, Tianyu Wang et al.

Universal Neural Optimal Transport

Jonathan Geuter, Gregor Kornhardt, Ingimar Tomasson et al.

Diagnosing the Compositional Knowledge of Vision Language Models from a Game-Theoretic View

Jin Wang, Shichao Dong, Yapeng Zhu et al.

Cape: Context-Aware Prompt Perturbation Mechanism with Differential Privacy

Haoqi Wu, Wei Dai, Wang Li et al.

SPEX: Scaling Feature Interaction Explanations for LLMs

Justin S. Kang, Landon Butler, Abhineet Agarwal et al.

On Volume Minimization in Conformal Regression

Batiste Le Bars, Pierre Humbert

Contextual Feature Selection with Conditional Stochastic Gates

Ram Dyuthi Sristi, Ofir Lindenbaum, Shira Lifshitz et al.

David and Goliath: Small One-step Model Beats Large Diffusion with Score Post-training

Weijian Luo, colin zhang, Debing Zhang et al.

Grokking at the Edge of Linear Separability

Alon Beck, Noam Levi, Yohai Bar-Sinai

Tuning Sequential Monte Carlo Samplers via Greedy Incremental Divergence Minimization

Kyurae Kim, Zuheng Xu, Jacob Gardner et al.

Chasing Convex Functions with Long-term Constraints

Adam Lechowicz, Nicolas Christianson, Bo Sun et al.

VIP: Vision Instructed Pre-training for Robotic Manipulation

Zhuoling Li, LiangLiang Ren, Jinrong Yang et al.

Implicit Compressibility of Overparametrized Neural Networks Trained with Heavy-Tailed SGD

Yijun Wan, Melih Barsbey, Abdellatif Zaidi et al.

Understanding the Logic of Direct Preference Alignment through Logic

Kyle Richardson, Vivek Srikumar, Ashish Sabharwal

One Image is Worth a Thousand Words: A Usability Preservable Text-Image Collaborative Erasing Framework

Feiran Li, Qianqian Xu, Shilong Bao et al.

NestQuant: nested lattice quantization for matrix products and LLMs

Semyon Savkin, Eitan Porat, Or Ordentlich et al.

Beyond CVaR: Leveraging Static Spectral Risk Measures for Enhanced Decision-Making in Distributional Reinforcement Learning

Mehrdad Moghimi, Hyejin Ku

Generative Intervention Models for Causal Perturbation Modeling

Nora Schneider, Lars Lorch, Niki Kilbertus et al.

LLaVA-ReID: Selective Multi-image Questioner for Interactive Person Re-Identification

Yiding Lu, Mouxing Yang, Dezhong Peng et al.

On Zero-Initialized Attention: Optimal Prompt and Gating Factor Estimation

Nghiem Diep, Huy Nguyen, Chau Nguyen et al.

QMamba: On First Exploration of Vision Mamba for Image Quality Assessment

Fengbin Guan, Xin Li, Zihao Yu et al.

Accelerated Policy Gradient: On the Convergence Rates of the Nesterov Momentum for Reinforcement Learning

Yen-Ju Chen, Nai-Chieh Huang, Ching-pei Lee et al.

On-Device Collaborative Language Modeling via a Mixture of Generalists and Specialists

Dongyang Fan, Bettina Messmer, Nikita Doikov et al.

Scaling Sparse Feature Circuits For Studying In-Context Learning

Dmitrii Kharlapenko, Stepan Shabalin, Arthur Conmy et al.

Continuous Visual Autoregressive Generation via Score Maximization

Chenze Shao, Fandong Meng, Jie Zhou

Unlocking Post-hoc Dataset Inference with Synthetic Data

Bihe Zhao, Pratyush Maini, Franziska Boenisch et al.

Parameter Estimation in DAGs from Incomplete Data via Optimal Transport

Vy Vo, Trung Le, Tung-Long Vuong et al.

One Size Fits All for Semantic Shifts: Adaptive Prompt Tuning for Continual Learning

Doyoung Kim, Susik Yoon, Dongmin Park et al.

Near-Optimal Regret in Linear MDPs with Aggregate Bandit Feedback

Asaf Cassel, Haipeng Luo, Aviv Rosenberg et al.

Improving Robustness to Multiple Spurious Correlations by Multi-Objective Optimization

Nayeong Kim, Juwon Kang, Sungsoo Ahn et al.

Major-Minor Mean Field Multi-Agent Reinforcement Learning

Kai Cui, Christian Fabian, Anam Tahir et al.

DragLoRA: Online Optimization of LoRA Adapters for Drag-based Image Editing in Diffusion Model

Siwei Xia, Li Sun, Tiantian Sun et al.

Efficient Time Series Processing for Transformers and State-Space Models through Token Merging

Leon Götz, Marcel Kollovieh, Stephan Günnemann et al.

Contextual Online Decision Making with Infinite-Dimensional Functional Regression

Haichen Hu, Rui Ai, Stephen Bates et al.

Multi-band Frequency Reconstruction for Neural Psychoacoustic Coding

Dianwen Ng, Kun Zhou, Yi-Wen Chao et al.

Breaking through the learning plateaus of in-context learning in Transformer

Jingwen Fu, Tao Yang, Yuwang Wang et al.

The Price of Freedom: Exploring Expressivity and Runtime Tradeoffs in Equivariant Tensor Products

YuQing Xie, Ameya Daigavane, Mit Kotak et al.

Falcon: Fast Visuomotor Policies via Partial Denoising

Haojun Chen, Minghao Liu, Chengdong Ma et al.

Beyond The Rainbow: High Performance Deep Reinforcement Learning on a Desktop PC

Tyler Clark, Mark Towers, Christine Evers et al.

LayerMerge: Neural Network Depth Compression through Layer Pruning and Merging

Jinuk Kim, Marwa El Halabi, Mingi Ji et al.

Differential Privacy Under Class Imbalance: Methods and Empirical Insights

Lucas Rosenblatt, Yuliia Lut, Ethan Turok et al.

Differentiable Combinatorial Scheduling at Scale

Mingju Liu, Yingjie Li, Jiaqi Yin et al.

Certifiably Byzantine-Robust Federated Conformal Prediction

Mintong Kang, Zhen Lin, Jimeng Sun et al.

Towards Cost-Effective Reward Guided Text Generation

Ahmad Rashid, Ruotian Wu, Rongqi Fan et al.

Learning-Augmented Hierarchical Clustering

Vladimir Braverman, Jon C. Ergun, Chen Wang et al.

On a Combinatorial Problem Arising in Machine Teaching

Joakim Sunde, Brigt Håvardstun, Jan Kratochvíl et al.

Solving Linear-Gaussian Bayesian Inverse Problems with Decoupled Diffusion Sequential Monte Carlo

Filip Ekström Kelvinius, Zheng Zhao, Fredrik Lindsten

Diffusion Tempering Improves Parameter Estimation with Probabilistic Integrators for Ordinary Differential Equations

Jonas Beck, Nathanael Bosch, Michael Deistler et al.

Hierarchical Refinement: Optimal Transport to Infinity and Beyond

Peter Halmos, Julian Gold, Xinhao Liu et al.

Improving Multimodal Learning Balance and Sufficiency through Data Remixing

Xiaoyu Ma, Hao Chen, Yongjian Deng

Beyond Topological Self-Explainable GNNs: A Formal Explainability Perspective

Steve Azzolin, SAGAR MALHOTRA, Andrea Passerini et al.

Position: Embracing Negative Results in Machine Learning

Florian Karl, Malte Kemeter, Gabriel Dax et al.

Preserving AUC Fairness in Learning with Noisy Protected Groups

Mingyang Wu, Li Lin, Wenbin Zhang et al.

A Comprehensive Framework for Analyzing the Convergence of Adam: Bridging the Gap with SGD

Ruinan Jin, Xiao Li, Yaoliang Yu et al.

Inverse Problem Sampling in Latent Space Using Sequential Monte Carlo

Idan Achituve, Hai Victor Habi, Amir Rosenfeld et al.

Gumiho: A Hybrid Architecture to Prioritize Early Tokens in Speculative Decoding

Jinze Li, Yixing Xu, Haiduo Huang et al.

How Transformers Learn Regular Language Recognition: A Theoretical Study on Training Dynamics and Implicit Bias

Ruiquan Huang, Yingbin LIANG, Jing Yang

TreeLoRA: Efficient Continual Learning via Layer-Wise LoRAs Guided by a Hierarchical Gradient-Similarity Tree

Yu-Yang Qian, Yuan-Ze Xu, Zhen-Yu Zhang et al.

FRUGAL: Memory-Efficient Optimization by Reducing State Overhead for Scalable Training

Filipp Zmushko, Aleksandr Beznosikov, Martin Takac et al.

Positional Attention: Expressivity and Learnability of Algorithmic Computation

Artur Back de Luca, George Giapitzakis, Shenghao Yang et al.

Active Label Correction for Semantic Segmentation with Foundation Models

Hoyoung Kim, SEHYUN HWANG, Suha Kwak et al.

FloE: On-the-Fly MoE Inference on Memory-constrained GPU

Yuxin Zhou, Zheng Li, Jun Zhang et al.

Score-based Pullback Riemannian Geometry: Extracting the Data Manifold Geometry using Anisotropic Flows

Willem Diepeveen, Georgios Batzolis, Zakhar Shumaylov et al.

RVI-SAC: Average Reward Off-Policy Deep Reinforcement Learning

Yukinari Hisaki, Isao Ono

Simulation-Based Inference with Quantile Regression

He Jia

Measuring Diversity: Axioms and Challenges

Mikhail Mironov, Liudmila Prokhorenkova

ToMA: Token Merge with Attention for Diffusion Models

Wenbo Lu, Shaoyi Zheng, Yuxuan Xia et al.

PASOA- PArticle baSed Bayesian Optimal Adaptive design

Jacopo Iollo, Christophe Heinkelé, Pierre Alliez et al.

GRAIL: Graph Edit Distance and Node Alignment using LLM-Generated Code

Samidha Verma, Arushi Goyal, Ananya Mathur et al.

Solving Probabilistic Verification Problems of Neural Networks using Branch and Bound

David Boetius, Stefan Leue, Tobias Sutter

SAFE: Finding Sparse and Flat Minima to Improve Pruning

Dongyeop Lee, Kwanhee Lee, Jinseok Chung et al.

Clustering Properties of Self-Supervised Learning

Xi Weng, Jianing An, Xudong Ma et al.

Point-Level Topological Representation Learning on Point Clouds

Vincent P. Grande, Michael Schaub

Geometric Hyena Networks for Large-scale Equivariant Learning

Artem Moskalev, Mangal Prakash, Junjie Xu et al.

FACTER: Fairness-Aware Conformal Thresholding and Prompt Engineering for Enabling Fair LLM-Based Recommender Systems

Arya Fayyazi, Mehdi Kamal, Massoud Pedram

Provable Privacy with Non-Private Pre-Processing

Yaxi Hu, Amartya Sanyal, Bernhard Schölkopf

The Balanced-Pairwise-Affinities Feature Transform

Daniel Shalam, Simon Korman

Linear $Q$-Learning Does Not Diverge in $L^2$: Convergence Rates to a Bounded Set

Xinyu Liu, Zixuan Xie, Shangtong Zhang

A Primal-Dual Algorithm for Offline Constrained Reinforcement Learning with Linear MDPs

Kihyuk Hong, Ambuj Tewari

Deconstructing the Goldilocks Zone of Neural Network Initialization

Artem Vysogorets, Anna Dawid, Julia Kempe

A Fixed-Point Approach for Causal Generative Modeling

Meyer Scetbon, Joel Jennings, Agrin Hilmkil et al.

PlanDQ: Hierarchical Plan Orchestration via D-Conductor and Q-Performer

Chang Chen, Junyeob Baek, Fei Deng et al.

Unleashing the Power of Meta-tuning for Few-shot Generalization Through Sparse Interpolated Experts

Shengzhuang Chen, Jihoon Tack, Yunqiao Yang et al.

SparseLoRA: Accelerating LLM Fine-Tuning with Contextual Sparsity

Samir Khaki, Xiuyu Li, Junxian Guo et al.

Position: Lifetime tuning is incompatible with continual reinforcement learning

Golnaz Mesbahi, Parham Mohammad Panahi, Olya Mastikhina et al.

Collaborative Heterogeneous Causal Inference Beyond Meta-analysis

Tianyu Guo, Sai Praneeth Karimireddy, Michael Jordan

Score-Based Diffusion Policy Compatible with Reinforcement Learning via Optimal Transport

Mingyang Sun, Pengxiang Ding, Weinan Zhang et al.

Low-Rank Adapting Models for Sparse Autoencoders

Matthew Chen, Josh Engels, Max Tegmark

Representations Shape Weak-to-Strong Generalization: Theoretical Insights and Empirical Predictions

Yihao Xue, Jiping Li, Baharan Mirzasoleiman

Statistical Collusion by Collectives on Learning Platforms

Etienne Gauthier, Francis Bach, Michael Jordan

AdaPTS: Adapting Univariate Foundation Models to Probabilistic Multivariate Time Series Forecasting

Abdelhakim Benechehab, Vasilii Feofanov, Giuseppe Paolo et al.

MAGELLAN: Metacognitive predictions of learning progress guide autotelic LLM agents in large goal spaces

Loris Gaven, Thomas Carta, Clément Romac et al.

Understanding the Training Speedup from Sampling with Approximate Losses

Rudrajit Das, Xi Chen, Bertram Ieong et al.

Listening to the noise: Blind Denoising with Gibbs Diffusion

David Heurtel-Depeiges, Charles Margossian, Ruben Ohana et al.

Chameleon: A Flexible Data-mixing Framework for Language Model Pretraining and Finetuning

Wanyun Xie, Francesco Tonin, Volkan Cevher

StackSight: Unveiling WebAssembly through Large Language Models and Neurosymbolic Chain-of-Thought Decompilation

Weike Fang, Zhejian Zhou, Junzhou He et al.

Learn Singularly Perturbed Solutions via Homotopy Dynamics

Chuqi CHEN, Yahong Yang, Yang Xiang et al.

Boosting Masked ECG-Text Auto-Encoders as Discriminative Learners

Hung Manh Pham, Aaqib Saeed, Dong Ma

Improving the Statistical Efficiency of Cross-Conformal Prediction

Learning Decision Trees and Forests with Algorithmic Recourse

Kentaro Kanamori, Takuya Takagi, Ken Kobayashi et al.

Conformal Prediction as Bayesian Quadrature

Jake Snell, Thomas Griffiths

Ferret: Federated Full-Parameter Tuning at Scale for Large Language Models

Yao Shu, Wenyang Hu, See-Kiong Ng et al.

Sable: a Performant, Efficient and Scalable Sequence Model for MARL

Omayma Mahjoub, Sasha Abramowitz, Ruan de Kock et al.

TRACE Back from the Future: A Probabilistic Reasoning Approach to Controllable Language Generation

Gwen Yidou-Weng, Benjie Wang, Guy Van den Broeck

On Understanding Attention-Based In-Context Learning for Categorical Data

Aaron Wang, William Convertino, Xiang Cheng et al.

A Field Guide for Pacing Budget and ROS Constraints

Santiago Balseiro, Kshipra Bhawalkar, Zhe Feng et al.

From Neurons to Neutrons: A Case Study in Interpretability

Ouail Kitouni, Niklas Nolte, Víctor Samuel Pérez-Díaz et al.

Efficient Error Certification for Physics-Informed Neural Networks

Francisco Eiras, Adel Bibi, Rudy Bunel et al.

Covered Forest: Fine-grained generalization analysis of graph neural networks

Antonis Vasileiou, Ben Finkelshtein, Floris Geerts et al.

Implicit Bias of Policy Gradient in Linear Quadratic Control: Extrapolation to Unseen Initial States

Noam Razin, Yotam Alexander, Edo Cohen-Karlik et al.

Decomposable Submodular Maximization in Federated Setting

Akbar Rafiey

MorphGrower: A Synchronized Layer-by-layer Growing Approach for Plausible Neuronal Morphology Generation

Nianzu Yang, Kaipeng Zeng, Haotian Lu et al.

Internal Causal Mechanisms Robustly Predict Language Model Out-of-Distribution Behaviors

Jing Huang, Junyi Tao, Thomas Icard et al.

R2-T2: Re-Routing in Test-Time for Multimodal Mixture-of-Experts

Zhongyang Li, Ziyue Li, Tianyi Zhou

Determining Layer-wise Sparsity for Large Language Models Through a Theoretical Perspective

Weizhong Huang, Yuxin Zhang, Xiawu Zheng et al.

Unveiling the Potential of AI for Nanomaterial Morphology Prediction

Ivan Dubrovsky, Andrei Dmitrenko, Aleksey Dmitrenko et al.

Near-Optimal Reinforcement Learning with Self-Play under Adaptivity Constraints

Dan Qiao, Yu-Xiang Wang

StealthInk: A Multi-bit and Stealthy Watermark for Large Language Models

Ya Jiang, Chuxiong Wu, Massieh Kordi Boroujeny et al.

Learning to Remove Cuts in Integer Linear Programming

Pol Puigdemont, EFSTRATIOS PANTELEIMON SKOULAKIS, Grigorios Chrysos et al.

Inductive Gradient Adjustment for Spectral Bias in Implicit Neural Representations

Kexuan Shi, Hai Chen, Leheng Zhang et al.

Going beyond Compositions, DDPMs Can Produce Zero-Shot Interpolations

Justin Deschenaux, Igor Krawczuk, Grigorios Chrysos et al.

Rethinking Time Encoding via Learnable Transformation Functions

Xi Chen, Yateng Tang, Jiarong Xu et al.

Locally Interdependent Multi-Agent MDP: Theoretical Framework for Decentralized Agents with Dynamic Dependencies

Alex DeWeese, Guannan Qu

Continuous Treatment Effects with Surrogate Outcomes

Zhenghao Zeng, David Arbour, Avi Feller et al.

FAB-PPI: Frequentist, Assisted by Bayes, Prediction-Powered Inference

Stefano Cortinovis, Francois Caron

Tensor Product Neural Networks for Functional ANOVA Model

Seokhun Park, Insung Kong, yongchan Choi et al.

Visual Abstraction: A Plug-and-Play Approach for Text-Visual Retrieval

Guofeng Ding, Yiding Lu, Peng Hu et al.

Distributional Bellman Operators over Mean Embeddings

Li Kevin Wenliang, Gregoire Deletang, Matthew Aitchison et al.

PhantomWiki: On-Demand Datasets for Reasoning and Retrieval Evaluation

Albert Gong, Kamilė Stankevičiūtė, Chao Wan et al.

Solving Hierarchical Information-Sharing Dec-POMDPs: An Extensive-Form Game Approach

Johan Peralez, Aurélien Delage, Olivier Buffet et al.

Flopping for FLOPs: Leveraging Equivariance for Computational Efficiency

Georg Bökman, David Nordström, Fredrik Kahl

Statistical Hypothesis Testing for Auditing Robustness in Language Models

Paulius Rauba, Qiyao Wei, Mihaela van der Schaar

How Flawed Is ECE? An Analysis via Logit Smoothing

Muthu Chidambaram, Holden Lee, Colin McSwiggen et al.

Lightspeed Geometric Dataset Distance via Sliced Optimal Transport

Khai Nguyen, Hai Nguyen, Tuan Pham et al.

LPGD: A General Framework for Backpropagation through Embedded Optimization Layers

Anselm Paulus, Georg Martius, Vit Musil

Learnable Spatial-Temporal Positional Encoding for Link Prediction

Katherine Tieu, Dongqi Fu, Zihao Li et al.

Hierarchical Planning for Complex Tasks with Knowledge Graph-RAG and Symbolic Verification

Flavio Petruzzellis, Cristina Cornelio, Pietro Lió

Making Old Things New: A Unified Algorithm for Differentially Private Clustering

Max Dupre la Tour, Monika Henzinger, David Saulpic

The Max-Min Formulation of Multi-Objective Reinforcement Learning: From Theory to a Model-Free Algorithm

Giseung Park, woohyeon Byeon, Seongmin Kim et al.

PriorBoost: An Adaptive Algorithm for Learning from Aggregate Responses

Adel Javanmard, Matthew Fahrbach, Vahab Mirrokni

Generalization Analysis for Supervised Contrastive Representation Learning under Non-IID Settings

Minh Hieu Nong, Antoine Ledent

The Panaceas for Improving Low-Rank Decomposition in Communication-Efficient Federated Learning

Shiwei Li, Xiandi Luo, Haozhao Wang et al.

Improved Communication-Privacy Trade-offs in $L_2$ Mean Estimation under Streaming Differential Privacy

Wei-Ning Chen, Berivan Isik, Peter Kairouz et al.

TraceGrad: a Framework Learning Expressive SO(3)-equivariant Non-linear Representations for Electronic-Structure Hamiltonian Prediction

Shi Yin, Xinyang Pan, fengyan wang et al.

Conformal Tail Risk Control for Large Language Model Alignment

Catherine Chen, Jingyan Shen, Xinyu Yang et al.

FastCAV: Efficient Computation of Concept Activation Vectors for Explaining Deep Neural Networks

Laines Schmalwasser, Niklas Penzel, Joachim Denzler et al.

Identifiability Matters: Revealing the Hidden Recoverable Condition in Unbiased Learning to Rank

Mouxiang Chen, Chenghao Liu, Zemin Liu et al.

Regression for the Mean: Auto-Evaluation and Inference with Few Labels through Post-hoc Regression

Benjamin Eyre, David Madras

Overcoming Non-monotonicity in Transducer-based Streaming Generation

Zhengrui Ma, Yang Feng, Min zhang

Semantic Shift Estimation via Dual-Projection and Classifier Reconstruction for Exemplar-Free Class-Incremental Learning

Run He, Di Fang, Yicheng Xu et al.

Enhancing Cross-Modal Fine-Tuning with Gradually Intermediate Modality Generation

Lincan Cai, Shuang Li, Wenxuan Ma et al.

SDP-CROWN: Efficient Bound Propagation for Neural Network Verification with Tightness of Semidefinite Programming

Hong-Ming Chiu, Hao Chen, Huan Zhang et al.

Projection-Free Variance Reduction Methods for Stochastic Constrained Multi-Level Compositional Optimization

Wei Jiang, Sifan Yang, Wenhao Yang et al.

Best of Both Worlds Guarantees for Smoothed Online Quadratic Optimization

Neelkamal Bhuyan, Debankur Mukherjee, Adam Wierman

Balancing Interference and Correlation in Spatial Experimental Designs: A Causal Graph Cut Approach

Jin Zhu, Jingyi Li, Hongyi Zhou et al.

Standardized Interpretable Fairness Measures for Continuous Risk Scores

Ann-Kristin Becker, Oana Dumitrasc, Klaus Broelemann

Upweighting Easy Samples in Fine-Tuning Mitigates Forgetting

Sunny Sanyal, Hayden Prairie, Rudrajit Das et al.

Counterfactual Metarules for Local and Global Recourse

Tom Bewley, Salim I. Amoukou, Saumitra Mishra et al.

SiBBlInGS: Similarity-driven Building-Block Inference using Graphs across States

Noga Mudrik, Gal Mishne, Adam Charles

MetaAgent: Automatically Constructing Multi-Agent Systems Based on Finite State Machines

Yaolun Zhang, Xiaogeng Liu, Chaowei Xiao

On Linear Convergence in Smooth Convex-Concave Bilinearly-Coupled Saddle-Point Optimization: Lower Bounds and Optimal Algorithms

Ekaterina Borodich, Alexander Gasnikov, Dmitry Kovalev

Learning curves theory for hierarchically compositional data with power-law distributed features

Francesco Cagnetta, Hyunmo Kang, Matthieu Wyart

Raptor: Scalable Train-Free Embeddings for 3D Medical Volumes Leveraging Pretrained 2D Foundation Models

Ulzee An, Moonseong Jeong, Simon Lee et al.

Exact risk curves of signSGD in High-Dimensions: quantifying preconditioning and noise-compression effects

Kevin Xiao, Noah Marshall, Atish Agarwala et al.

Feedforward Few-shot Species Range Estimation

Christian Lange, Max Hamilton, Elijah Cole et al.

Position: Scaling LLM Agents Requires Asymptotic Analysis with LLM Primitives

Elliot Meyerson, Xin Qiu

Projection Pursuit Density Ratio Estimation

Meilin Wang, Wei Huang, Mingming Gong et al.

Dynamical Modeling of Behaviorally Relevant Spatiotemporal Patterns in Neural Imaging Data

Mohammad Hosseini, Maryam Shanechi