Most Cited ICML "conditional independence assumption" Papers
5,975 papers found • Page 4 of 30
Conference
On the Provable Separation of Scales in Maximal Update Parameterization
Letong Hong, Zhangyang “Atlas” Wang
Position: A Theory of Deep Learning Must Include Compositional Sparsity
David A. Danhofer, Davide DAscenzo, Rafael Dubach et al.
Stochastic Poisson Surface Reconstruction with One Solve using Geometric Gaussian Processes
Sidhanth Holalkere, David S Bindel, Silvia Sellán et al.
Robust Reward Alignment via Hypothesis Space Batch Cutting
Zhixian Xie, Haode Zhang, Yizhe Feng et al.
From Jack of All Trades to Master of One: Specializing LLM-based Autoraters to a Test Set
Mara Finkelstein, Daniel Deutsch, Parker Riley et al.
Calibrated Physics-Informed Uncertainty Quantification
Vignesh Gopakumar, Ander Gray, Lorenzo Zanisi et al.
A Unified Theoretical Analysis of Private and Robust Offline Alignment: from RLHF to DPO
Xingyu Zhou, Yulian Wu, Francesco Orabona
Representation Surgery in Model Merging with Probabilistic Modeling
Qi Wei, Shuo He, Enneng Yang et al.
CLOVER: Cross-Layer Orthogonal Vectors Pruning
Fanxu Meng, Pingzhi Tang, Fan Jiang et al.
A Meta-learner for Heterogeneous Effects in Difference-in-Differences
Hui Lan, Chang, Eleanor W Dillon et al.
Vision-Language Model Selection and Reuse for Downstream Adaptation
Hao-Zhe Tan, Zhi Zhou, Yu-Feng Li et al.
Function-Space Learning Rates
Edward Milsom, Ben Anson, Laurence Aitchison
TS-SNN: Temporal Shift Module for Spiking Neural Networks
Kairong Yu, Tianqing Zhang, Qi Xu et al.
A Variational Perspective on Generative Protein Fitness Optimization
Lea Bogensperger, Dominik Narnhofer, Ahmed Allam et al.
DragSolver: A Multi-Scale Transformer for Real-World Automotive Drag Coefficient Estimation
Ye Liu, Yuntian Chen
CMoS: Rethinking Time Series Prediction Through the Lens of Chunk-wise Spatial Correlations
Haotian Si, Changhua Pei, Jianhui LI et al.
On the Query Complexity of Verifier-Assisted Language Generation
Edoardo Botta, Yuchen Li, Aashay Mehta et al.
QuanONet: Quantum Neural Operator with Application to Differential Equation
Ruocheng Wang, Zhuo Xia, Ge Yan et al.
A Square Peg in a Square Hole: Meta-Expert for Long-Tailed Semi-Supervised Learning
Yaxin Hou, Yuheng Jia
Differentiable Quadratic Optimization For the Maximum Independent Set Problem
Ismail Alkhouri, Cedric Le Denmat, Yingjie Li et al.
Learning multivariate Gaussians with imperfect advice
Arnab Bhattacharyya, Davin Choo, Philips George John et al.
Generalization in Federated Learning: A Conditional Mutual Information Framework
Ziqiao Wang, Cheng Long, Yongyi Mao
LaMAGIC2: Advanced Circuit Formulations for Language Model-Based Analog Topology Generation
Chen-Chia Chang, Wan-Hsuan Lin, Yikang Shen et al.
Arbitrarily-Conditioned Multi-Functional Diffusion for Multi-Physics Emulation
Da Long, Zhitong Xu, Guang Yang et al.
Preference Learning for AI Alignment: a Causal Perspective
Katarzyna Kobalczyk, Mihaela van der Schaar
BOOD: Boundary-based Out-Of-Distribution Data Generation
Qilin Liao, Shuo Yang, Bo Zhao et al.
PIGDreamer: Privileged Information Guided World Models for Safe Partially Observable Reinforcement Learning
Dongchi Huang, Jiaqi WANG, Yang Li et al.
Exact Recovery of Sparse Binary Vectors from Generalized Linear Measurements
Arya Mazumdar, Neha Sangwan
MoRAgent: Parameter Efficient Agent Tuning with Mixture-of-Roles
Jing Han, Binwei Yan, Tianyu Guo et al.
Efficient Long Context Fine-tuning with Chunk Flow
Xiulong Yuan, Hongtao Xu, Wenting Shen et al.
Empirical Privacy Variance
Yuzheng Hu, Fan Wu, Ruicheng Xian et al.
Prompt-based Visual Alignment for Zero-shot Policy Transfer
Haihan Gao, Rui Zhang, Qi Yi et al.
Rethinking the Bias of Foundation Model under Long-tailed Distribution
Jiahao Chen, Bin Qin, Jiangmeng Li et al.
Stable Offline Value Function Learning with Bisimulation-based Representations
Brahma Pavse, Yudong Chen, Qiaomin Xie et al.
Feature learning from non-Gaussian inputs: the case of Independent Component Analysis in high dimensions
Fabiola Ricci, Lorenzo Bardone, Sebastian Goldt
unMORE: Unsupervised Multi-Object Segmentation via Center-Boundary Reasoning
Yafei YANG, Zihui Zhang, Bo Yang
SpikeVideoFormer: An Efficient Spike-Driven Video Transformer with Hamming Attention and $\mathcal{O}(T)$ Complexity
Shihao Zou, Qingfeng Li, Wei Ji et al.
Neural Graph Matching Improves Retrieval Augmented Generation in Molecular Machine Learning
Runzhong Wang, Rui-Xi Wang, Mrunali Manjrekar et al.
Convex Markov Games: A New Frontier for Multi-Agent Reinforcement Learning
Ian Gemp, Andreas Haupt, Luke Marris et al.
BiMaCoSR: Binary One-Step Diffusion Model Leveraging Flexible Matrix Compression for Real Super-Resolution
Kai Liu, Kaicheng Yang, Zheng Chen et al.
FlexiClip: Locality-Preserving Free-Form Character Animation
Anant Khandelwal
Learning Mixtures of Experts with EM: A Mirror Descent Perspective
Quentin Fruytier, Aryan Mokhtari, Sujay Sanghavi
CtrlSynth: Controllable Image Text Synthesis for Data-Efficient Multimodal Learning
Qingqing Cao, Mahyar Najibi, Sachin Mehta
High Dynamic Range Novel View Synthesis with Single Exposure
Kaixuan Zhang, HuWang, Minxian Li et al.
Breaking the Quadratic Barrier: Robust Cardinality Sketches for Adaptive Queries
Edith Cohen, Mihir Singhal, Uri Stemmer
Information Bottleneck-guided MLPs for Robust Spatial-temporal Forecasting
Min Chen, Guansong Pang, Wenjun Wang et al.
Evolving Prompts In-Context: An Open-ended, Self-replicating Perspective
Jianyu Wang, Zhiqiang Hu, Lidong Bing
$S^2$FGL: Spatial Spectral Federated Graph Learning
Zihan Tan, Suyuan Huang, Guancheng Wan et al.
Concentration Distribution Learning from Label Distributions
Jiawei Tang, Yuheng Jia
Learning Dynamics under Environmental Constraints via Measurement-Induced Bundle Structures
Dongzhe Zheng, Wenjie Mei
EvoControl: Multi-Frequency Bi-Level Control for High-Frequency Continuous Control
Samuel Holt, Todor Davchev, Dhruva Tirumala et al.
You Always Recognize Me (YARM): Robust Texture Synthesis Against Multi-View Corruption
Weihang Ran, Wei Yuan, Yinqiang Zheng
Permutation Equivariant Neural Networks for Symmetric Tensors
Edward Pearce-Crump
Splitting with Importance-aware Updating for Heterogeneous Federated Learning with Large Language Models
Yangxu Liao, Wenke Huang, Guancheng Wan et al.
Learning Survival Distributions with the Asymmetric Laplace Distribution
Deming Sheng, Ricardo Henao
Incremental Gradient Descent with Small Epoch Counts is Surprisingly Slow on Ill-Conditioned Problems
Yujun Kim, Jaeyoung Cha, Chulhee Yun
Enforcing Idempotency in Neural Networks
Nikolaj Jensen, Jamie Vicary
Prediction via Shapley Value Regression
Amr Alkhatib, Roman Bresson, Henrik Boström et al.
Tracking The Best Expert Privately
Hilal Asi, Vinod Raman, Aadirupa Saha
Learning Curves of Stochastic Gradient Descent in Kernel Regression
Haihan Zhang, Weicheng Lin, Yuanshi Liu et al.
Consensus Based Stochastic Optimal Control
Liyao Lyu, Jingrun Chen
Fairness on Principal Stratum: A New Perspective on Counterfactual Fairness
Haoxuan Li, Zeyu Tang, Zhichao Jiang et al.
KEA: Keeping Exploration Alive by Proactively Coordinating Exploration Strategies
Shih-Min Yang, Martin Magnusson, Johannes Stork et al.
Broadband Ground Motion Synthesis by Diffusion Model with Minimal Condition
Jaeheun Jung, Jaehyuk Lee, ChangHae Jung et al.
Compositional Scene Understanding through Inverse Generative Modeling
Yanbo Wang, Justin Dauwels, Yilun Du
Generative Modeling Reinvents Supervised Learning: Label Repurposing with Predictive Consistency Learning
Yang Li, Jiale Ma, Yebin Yang et al.
Zero-Inflated Bandits
Haoyu Wei, Runzhe Wan, Lei Shi et al.
FactTest: Factuality Testing in Large Language Models with Finite-Sample and Distribution-Free Guarantees
Fan Nie, Xiaotian Hou, Shuhang Lin et al.
Arrow: Accelerator for Time Series Causal Discovery with Time Weaving
Yuanyuan Yao, Yuan Dong, Lu Chen et al.
CateKV: On Sequential Consistency for Long-Context LLM Inference Acceleration
Haoyun Jiang, Haolin li, jianwei zhang et al.
TCP-Diffusion: A Multi-modal Diffusion Model for Global Tropical Cyclone Precipitation Forecasting with Change Awareness
Cheng Huang, Pan Mu, Cong Bai et al.
Targeted control of fast prototyping through domain-specific interface
Yu-Zhe Shi, Mingchen Liu, Hanlu Ma et al.
Multiple-policy Evaluation via Density Estimation
Yilei Chen, Aldo Pacchiano, Ioannis Paschalidis
COGNATE: Acceleration of Sparse Tensor Programs on Emerging Hardware using Transfer Learning
Chamika Sudusinghe, Gerasimos Gerogiannis, Damitha Lenadora et al.
Open Your Eyes: Vision Enhances Message Passing Neural Networks in Link Prediction
Yanbin Wei, Xuehao Wang, Zhan Zhuang et al.
Exploring Invariance in Images through One-way Wave Equations
Yinpeng Chen, Dongdong Chen, Xiyang Dai et al.
PEINR: A Physics-enhanced Implicit Neural Representation for High-Fidelity Flow Field Reconstruction
Liming Shen, Liang Deng, Chongke Bi et al.
Understanding Fixed Predictions via Confined Regions
Connor Lawless, Lily Weng, Berk Ustun et al.
The Empirical Mean is Minimax Optimal for Local Glivenko-Cantelli
Doron Cohen, Aryeh Kontorovich, Roi Weiss
Quantifying Memory Utilization with Effective State-Size
Rom N. Parnichkun, Neehal Tumma, Armin Thomas et al.
Test-time Correlation Alignment
Linjing You, Jiabao Lu, Xiayuan Huang
Targeted Unlearning with Single Layer Unlearning Gradient
Zikui Cai, Yaoteng Tan, M. Salman Asif
Model Uncertainty Quantification by Conformal Prediction in Continual Learning
Rui Gao, Weiwei Liu
Boost-and-Skip: A Simple Guidance-Free Diffusion for Minority Generation
Soobin Um, Beomsu Kim, Jong Chul YE
MetaAgent: Automatically Constructing Multi-Agent Systems Based on Finite State Machines
Yaolun Zhang, Xiaogeng Liu, Chaowei Xiao
An Augmentation-Aware Theory for Self-Supervised Contrastive Learning
Jingyi Cui, Hongwei Wen, Yisen Wang
Efficient Motion Prompt Learning for Robust Visual Tracking
Jie Zhao, Xin Chen, Yongsheng Yuan et al.
LV-XAttn: Distributed Cross-Attention for Long Visual Inputs in Multimodal Large Language Models
Tzu-Tao (Tommy) Chang, Shivaram Venkataraman
Behavioral Exploration: Learning to Explore via In-Context Adaptation
Andrew Wagenmaker, Zhiyuan Zhou, Sergey Levine
A Unified View on Learning Unnormalized Distributions via Noise-Contrastive Estimation
Jongha (Jon) Ryu, Abhin Shah, Gregory Wornell
The Four Color Theorem for Cell Instance Segmentation
Ye Zhang, Yu Zhou, Yifeng Wang et al.
Exploiting Similarity for Computation and Communication-Efficient Decentralized Optimization
Yuki Takezawa, Xiaowen Jiang, Anton Rodomanov et al.
LAST SToP for Modeling Asynchronous Time Series
Shubham Gupta, Thibaut Durand, Graham Taylor et al.
Subgroups Matter for Robust Bias Mitigation
Anissa Alloula, Charles Jones, Ben Glocker et al.
Learning to Generate Projections for Reducing Dimensionality of Heterogeneous Linear Programming Problems
Tomoharu Iwata, Shinsaku Sakaue
Identifying biological perturbation targets through causal differential networks
Menghua Wu, Umesh Padia, Sean Murphy et al.
Test-Time Adaptation for Online Vision-Language Navigation with Feedback-based Reinforcement Learning
Sung June Kim, Gyeongrok Oh, Heeju Ko et al.
Tackling Dimensional Collapse toward Comprehensive Universal Domain Adaptation
Hung-Chieh Fang, Po-Yi Lu, Hsuan-Tien (Tien) Lin
Reconstructing Cell Lineage Trees from Phenotypic Features with Metric Learning
Da Kuang, GuanWen Qiu, Junhyong Kim
Explaining the role of Intrinsic Dimensionality in Adversarial Training
Enes Altinisik, Safa Messaoud, Husrev Taha Sencar et al.
Does One-shot Give the Best Shot? Mitigating Model Inconsistency in One-shot Federated Learning
Hui Zeng, Wenke Huang, Tongqing Zhou et al.
Transfer Learning for Nonparametric Contextual Dynamic Pricing
Fan Wang, Feiyu Jiang, Zifeng Zhao et al.
Wolfpack Adversarial Attack for Robust Multi-Agent Reinforcement Learning
Sunwoo Lee, Jaebak Hwang, Yonghyeon Jo et al.
Leveraging Per-Instance Privacy for Machine Unlearning
Naz Sepahvand, Anvith Thudi, Berivan Isik et al.
Oracle-MoE: Locality-preserving Routing in the Oracle Space for Memory-constrained Large Language Model Inference
Jixian Zhou, Fang DONG(董方), Ruijun Huang et al.
Positional Encoding meets Persistent Homology on Graphs
Yogesh Verma, Amauri Souza, Vikas Garg
Efficient Skill Discovery via Regret-Aware Optimization
He ZHANG, Ming Zhou, shaopeng zhai et al.
Partition First, Embed Later: Laplacian-Based Feature Partitioning for Refined Embedding and Visualization of High-Dimensional Data
Erez Peterfreund, Ofir Lindenbaum, Yuval Kluger et al.
The Synergy of LLMs & RL Unlocks Offline Learning of Generalizable Language-Conditioned Policies with Low-fidelity Data
Thomas Pouplin, Katarzyna Kobalczyk, Hao Sun et al.
TMetaNet: Topological Meta-Learning Framework for Dynamic Link Prediction
Hao Li, Hao Wan, Yuzhou Chen et al.
Ab Initio Nonparametric Variable Selection for Scalable Symbolic Regression with Large $p$
Shengbin Ye, Meng Li
Provable Length Generalization in Sequence Prediction via Spectral Filtering
Annie Marsden, Evan Dogariu, Naman Agarwal et al.
Validating Mechanistic Interpretations: An Axiomatic Approach
Nils Palumbo, Ravi Mangal, Zifan Wang et al.
Visual Graph Arena: Evaluating Visual Conceptualization of Vision and Multimodal Large Language Models
Zahra Babaiee, Peyman M. Kiasari, Daniela Rus et al.
Can We Predict Performance of Large Models across Vision-Language Tasks?
Qinyu Zhao, Ming Xu, Kartik Gupta et al.
SAH-Drive: A Scenario-Aware Hybrid Planner for Closed-Loop Vehicle Trajectory Generation
Yuqi Fan, Zhiyong Cui, Zhenning Li et al.
Distribution-aware Fairness Learning in Medical Image Segmentation From A Control-Theoretic Perspective
Yujin Oh, Pengfei Jin, Sangjoon Park et al.
From Feature Interaction to Feature Generation: A Generative Paradigm of CTR Prediction Models
MINGJIA YIN, Junwei Pan, Hao Wang et al.
Statistical Query Hardness of Multiclass Linear Classification with Random Classification Noise
Ilias Diakonikolas, Mingchen Ma, Lisheng Ren et al.
Uncertainty Estimation for Heterophilic Graphs Through the Lens of Information Theory
Dominik Fuchsgruber, Tom Wollschläger, Johannes Bordne et al.
Differentially Private Boxplots
Kelly Ramsay, Jairo Diaz-Rodriguez
From Pixels to Perception: Interpretable Predictions via Instance-wise Grouped Feature Selection
Moritz Vandenhirtz, Julia Vogt
Inverse Flow and Consistency Models
Yuchen Zhang, Jian Zhou
Info-Coevolution: An Efficient Framework for Data Model Coevolution
Ziheng Qin, Hailun Xu, Wei Yew et al.
Active Learning of Deep Neural Networks via Gradient-Free Cutting Planes
Erica Zhang, Fangzhao Zhang, Mert Pilanci
Concurrent Reinforcement Learning with Aggregated States via Randomized Least Squares Value Iteration
Yan Chen, Jerry Bai, Yiteng Zhang et al.
FuseUNet: A Multi-Scale Feature Fusion Method for U-like Networks
Quansong He, Xiangde Min, Kaishen Wang et al.
The Importance of Being Lazy: Scaling Limits of Continual Learning
Jacopo Graldi, Alessandro Breccia, Giulia Lanzillotta et al.
Binary Hypothesis Testing for Softmax Models and Leverage Score Models
Yuzhou Gu, Zhao Song, Junze Yin
Graph-Supported Dynamic Algorithm Configuration for Multi-Objective Combinatorial Optimization
Robbert Reijnen, Yaoxin Wu, Zaharah Bukhsh et al.
Sparse Training from Random Initialization: Aligning Lottery Ticket Masks using Weight Symmetry
Mohammed Adnan, Rohan Jain, Ekansh Sharma et al.
Smooth Interpolation for Improved Discrete Graph Generative Models
Yuxuan Song, Juntong Shi, Jingjing Gong et al.
Action-Dependent Optimality-Preserving Reward Shaping
Grant Forbes, Jianxun Wang, Leonardo Villalobos-Arias et al.
Suitability Filter: A Statistical Framework for Classifier Evaluation in Real-World Deployment Settings
Angéline Pouget, Mohammad Yaghini, Stephan Rabanser et al.
Leveraging Randomness in Model and Data Partitioning for Privacy Amplification
Andy Dong, Wei-Ning Chen, Ayfer Ozgur
Enhancing Cooperative Multi-Agent Reinforcement Learning with State Modelling and Adversarial Exploration
Andreas Kontogiannis, Konstantinos Papathanasiou, Yi Shen et al.
Tightening Causal Bounds via Covariate-Aware Optimal Transport
Sirui Lin, Zijun Gao, Jose Blanchet et al.
UniSim: A Unified Simulator for Time-Coarsened Dynamics of Biomolecules
Ziyang Yu, Wenbing Huang, Yang Liu
Layer-wise Quantization for Quantized Optimistic Dual Averaging
Anh Duc Nguyen, Ilia Markov, Zhengqing Wu et al.
Test-Time Adaptation with Binary Feedback
Taeckyung Lee, Sorn Chottananurak, Junsu Kim et al.
Permutation-based Rank Test in the Presence of Discretization and Application in Causal Discovery with Mixed Data
Xinshuai Dong, Ignavier Ng, Boyang Sun et al.
OrthoRank: Token Selection via Sink Token Orthogonality for Efficient LLM inference
Seungjun Shin, Jaehoon Oh, Dokwan Oh
PIPA: Preference Alignment as Prior-Informed Statistical Estimation
Junbo Li, Zhangyang “Atlas” Wang, qiang liu
EmoGrowth: Incremental Multi-label Emotion Decoding with Augmented Emotional Relation Graph
Kaicheng Fu, Changde Du, Jie Peng et al.
A Near-Optimal Single-Loop Stochastic Algorithm for Convex Finite-Sum Coupled Compositional Optimization
Bokun Wang, Tianbao Yang
On the Duality between Gradient Transformations and Adapters
Lucas Torroba Hennigen, Hunter Lang, Han Guo et al.
Learning to Trust Bellman Updates: Selective State-Adaptive Regularization for Offline RL
Qin-Wen Luo, Ming-Kun Xie, Ye-Wen Wang et al.
Adversarial Perturbations Are Formed by Iteratively Learning Linear Combinations of the Right Singular Vectors of the Adversarial Jacobian
Thomas Paniagua, Chinmay Savadikar, Tianfu Wu
PyTDC: A multimodal machine learning training, evaluation, and inference platform for biomedical foundation models
Alex Velez-Arce, Marinka Zitnik
Privacy Amplification Through Synthetic Data: Insights from Linear Regression
Clément Pierquin, Aurélien Bellet, Marc Tommasi et al.
Learning Likelihood-Free Reference Priors
Nick Bishop, Daniel Jarne Ornia, Joel Dyer et al.
Learning State-Based Node Representations from a Class Hierarchy for Fine-Grained Open-Set Detection
Spandan Pyakurel, Qi Yu
Contextures: Representations from Contexts
Runtian Zhai, Kai Yang, Burak VARICI et al.
Sample Complexity of Correlation Detection in the Gaussian Wigner Model
Dong Huang, Pengkun Yang
Towards scientific discovery with dictionary learning: Extracting biological concepts from microscopy foundation models
Konstantin Donhauser, Kristina Ulicna, Gemma Moran et al.
Sharp Generalization for Nonparametric Regression by Over-Parameterized Neural Networks: A Distribution-Free Analysis in Spherical Covariate
Yingzhen Yang
Primphormer: Efficient Graph Transformers with Primal Representations
Mingzhen He, Ruikai Yang, Hanling Tian et al.
Unisoma: A Unified Transformer-based Solver for Multi-Solid Systems
Shilong Tao, Zhe Feng, Haonan Sun et al.
PoisonBench: Assessing Language Model Vulnerability to Poisoned Preference Data
Tingchen Fu, Mrinank Sharma, Phil Torr et al.
Privacy Amplification by Structured Subsampling for Deep Differentially Private Time Series Forecasting
Jan Schuchardt, Mina Dalirrooyfard, Jed Guzelkabaagac et al.
Causal Abstraction Inference under Lossy Representations
Kevin Xia, Elias Bareinboim
Leveraging Offline Data in Linear Latent Contextual Bandits
Chinmaya Kausik, Kevin Tan, Ambuj Tewari
TextCenGen: Attention-Guided Text-Centric Background Adaptation for Text-to-Image Generation
Tianyi Liang, Jiangqi Liu, Yifei Huang et al.
Fusing Reward and Dueling Feedback in Stochastic Bandits
Xuchuang Wang, Qirun Zeng, Jinhang Zuo et al.
LLM Data Selection and Utilization via Dynamic Bi-level Optimization
Yang Yu, Kai Han, Hang Zhou et al.
Learning Representations of Instruments for Partial Identification of Treatment Effects
Jonas Schweisthal, Dennis Frauen, Maresa Schröder et al.
Position: Solve Layerwise Linear Models First to Understand Neural Dynamical Phenomena (Neural Collapse, Emergence, Lazy/Rich Regime, and Grokking)
Yoonsoo Nam, Seok Hyeong Lee, Clémentine Dominé et al.
Rank-One Modified Value Iteration
Arman Sharifi Kolarijani, Tolga Ok, Peyman Mohajerin Esfahani et al.
N2GON: Neural Networks for Graph-of-Net with Position Awareness
Yejiang Wang, Yuhai Zhao, Zhengkui Wang et al.
RATE: Causal Explainability of Reward Models with Imperfect Counterfactuals
David Reber, Sean Richardson, Todd Nief et al.
L3A: Label-Augmented Analytic Adaptation for Multi-Label Class Incremental Learning
Xiang Zhang, Run He, Chen Jiao et al.
Deep Unsupervised Hashing via External Guidance
Qihong Song, XitingLiu, Hongyuan Zhu et al.
Fraud-Proof Revenue Division on Subscription Platforms
Abheek Ghosh, Tzeh Yuan Neoh, Nicholas Teh et al.
On the Dynamic Regret of Following the Regularized Leader: Optimism with History Pruning
Naram Mhaisen, George Iosifidis
Machine Learning meets Algebraic Combinatorics: A Suite of Datasets Capturing Research-level Conjecturing Ability in Pure Mathematics
Herman Chau, Helen Jenne, Davis Brown et al.
Physics-Informed DeepONets for drift-diffusion on metric graphs: simulation and parameter identification
Jan Blechschmidt, Tom-Christian Riemer, Max Winkler et al.
Optimization for Neural Operators can Benefit from Width
Pedro Cisneros-Velarde, Bhavesh Shrimali, Arindam Banerjee
Understanding Complexity in VideoQA via Visual Program Generation
Cristobal Eyzaguirre, Igor Vasiljevic, Achal Dave et al.
Position: Political Neutrality in AI Is Impossible — But Here Is How to Approximate It
Jillian Fisher, Ruth Elisabeth Appel, Chan Young Park et al.
Position: Certified Robustness Does Not (Yet) Imply Model Security
Andrew C. Cullen, Paul MONTAGUE, Sarah Erfani et al.
Efficiently Vectorized MCMC on Modern Accelerators
Hugh Dance, Pierre Glaser, Peter Orbanz et al.
Position: Societal Impacts Research Requires Benchmarks for Creative Composition Tasks
Judy Hanwen Shen
Position: AI Agents Need Authenticated Delegation
Tobin South, Samuele Marro, Thomas Hardjono et al.
Self-Supervised Transformers as Iterative Solution Improvers for Constraint Satisfaction
Yudong W Xu, Wenhao Li, Scott Sanner et al.
Discrete Neural Algorithmic Reasoning
Gleb Rodionov, Liudmila Prokhorenkova
Position: Evaluating Generative AI Systems Is a Social Science Measurement Challenge
Hanna Wallach, Meera Desai, A. Feder Cooper et al.
Sortformer: A Novel Approach for Permutation-Resolved Speaker Supervision in Speech-to-Text Systems
Taejin Park, Ivan Medennikov, Kunal Dhawan et al.
In-Context Adaptation to Concept Drift for Learned Database Operations
Jiaqi Zhu, Shaofeng Cai, Shen et al.
Solving Probabilistic Verification Problems of Neural Networks using Branch and Bound
David Boetius, Stefan Leue, Tobias Sutter
Counterfactual Graphical Models: Constraints and Inference
Juan Correa, Elias Bareinboim
Not All Wrong is Bad: Using Adversarial Examples for Unlearning
Ali Ebrahimpour-Boroojeny, Hari Sundaram, Varun Chandrasekaran
Sample-Optimal Agnostic Boosting with Unlabeled Data
Udaya Ghai, Karan Singh
Dimension-Independent Rates for Structured Neural Density Estimation
Vandermeulen, Wai Ming Tai, Bryon Aragam
Investigating the Overlooked Hessian Structure: From CNNs to LLMs
Qian-Yuan Tang, Yufei Gu, Yunfeng Cai et al.
TabFlex: Scaling Tabular Learning to Millions with Linear Attention
Yuchen Zeng, Tuan Dinh, Wonjun Kang et al.
What can large language models do for sustainable food?
Anna Thomas, Adam Yee, Andrew Mayne et al.
Multi-Marginal Stochastic Flow Matching for High-Dimensional Snapshot Data at Irregular Time Points
Justin Lee, Behnaz Moradi-Jamei, Heman Shakeri
Geometry Informed Tokenization of Molecules for Language Model Generation
Xiner Li, Limei Wang, Youzhi Luo et al.
Graph4MM: Weaving Multimodal Learning with Structural Information
Xuying Ning, Dongqi Fu, Tianxin Wei et al.
UltraTWD: Optimizing Ultrametric Trees for Tree-Wasserstein Distance
Fangchen Yu, Yanzhen Chen, Jiaxing Wei et al.