Most Cited ICML "gradient conflict resolution" Papers

Bayesian Knowledge Distillation: A Bayesian Perspective of Distillation with Uncertainty Quantification

Luyang Fang, Yongkai Chen, Wenxuan Zhong et al.

Self-supervised Masked Graph Autoencoder via Structure-aware Curriculum

Haoyang Li, Xin Wang, Zeyang Zhang et al.

From Geometry to Causality- Ricci Curvature and the Reliability of Causal Inference on Networks

Amirhossein Farzam, Allen Tannenbaum, Guillermo Sapiro

Multinoulli Extension: A Lossless Yet Effective Probabilistic Framework for Subset Selection over Partition Constraints

Qixin Zhang, Wei Huang, Can Jin et al.

Multi-View Graph Clustering via Node-Guided Contrastive Encoding

Yazhou Ren, Junlong Ke, Zichen Wen et al.

Test-Time Selective Adaptation for Uni-Modal Distribution Shift in Multi-Modal Data

MingCai Chen, Baoming Zhang, Zongbo Han et al.

Pruning for GNNs: Lower Complexity with Comparable Expressiveness

Dun Ma, Jianguo Chen, Wenguo Yang et al.

EduLLM: Leveraging Large Language Models and Framelet-Based Signed Hypergraph Neural Networks for Student Performance Prediction

Ming Li, Yukang Cheng, Lu Bai et al.

Riemannian Diffusion Adaptation for Distributed Optimization on Manifolds

Xiuheng Wang, Ricardo Borsoi, Cédric Richard et al.

EGPlace: An Efficient Macro Placement Method via Evolutionary Search with Greedy Repositioning Guided Mutation

ji deng, Zhao Li, Ji Zhang et al.

Reservoir Computing for Short High-Dimensional Time Series: an Application to SARS-CoV-2 Hospitalization Forecast

Thomas Ferté, Dutartre Dan, Boris Hejblum et al.

Position: Relational Deep Learning - Graph Representation Learning on Relational Databases

Matthias Fey, Weihua Hu, Kexin Huang et al.

Graph Attention is Not Always Beneficial: A Theoretical Analysis of Graph Attention Mechanisms via Contextual Stochastic Block Models

Zhongtian Ma, Qiaosheng Zhang, Bocheng Zhou et al.

Neuroexplicit Diffusion Models for Inpainting of Optical Flow Fields

Tom Fischer, Pascal Peter, Joachim Weickert et al.

Inverse-Variance Weighting for Estimation of Heterogeneous Treatment Effects

Aaron Fisher

Compelling ReLU Networks to Exhibit Exponentially Many Linear Regions at Initialization and During Training

Max Milkert, David Hyde, Forrest Laine

Efficient Personalized Adaptation for Physiological Signal Foundation Model

Chenrui Wu, Haishuai Wang, Xiang Zhang et al.

Hierarchical Overlapping Clustering on Graphs: Cost Function, Algorithm and Scalability

Yicheng Pan, Renjie Chen, Pengyu Long et al.

Adversarial Robust Generalization of Graph Neural Networks

Chang Cao, Han Li, Yulong Wang et al.

CoPINN: Cognitive Physics-Informed Neural Networks

Siyuan Duan, Wenyuan Wu, Peng Hu et al.

PinNet: Pinpoint Instructive Information for Retrieval Augmented Code-to-Text Generation

Han Fu, Jian Tan, Pinhan Zhang et al.

Decision Mixer: Integrating Long-term and Local Dependencies via Dynamic Token Selection for Decision-Making

Hongling Zheng, Li Shen, Yong Luo et al.

Winner-takes-all for Multivariate Probabilistic Time Series Forecasting

Adrien Cortes, Remi Rehm, Victor Letzelter

Categorical Distributional Reinforcement Learning with Kullback-Leibler Divergence: Convergence and Asymptotics

Tyler Kastner, Mark Rowland, Yunhao Tang et al.

A Doubly Recursive Stochastic Compositional Gradient Descent Method for Federated Multi-Level Compositional Optimization

Hongchang Gao

AlphaQCM: Alpha Discovery in Finance with Distributional Reinforcement Learning

Zhoufan Zhu, Ke Zhu

SHARP-Distill: A 68× Faster Recommender System with Hypergraph Neural Networks and Language Models

Saman Forouzandeh, Parham Moradi, Mahdi Jalili

Provable Policy Gradient for Robust Average-Reward MDPs Beyond Rectangularity

Qiuhao Wang, Yuqi Zha, Chin Pang Ho et al.

Efficient LiDAR Reflectance Compression via Scanning Serialization

Jiahao Zhu, Kang You, Dandan Ding et al.

Near Optimal Best Arm Identification for Clustered Bandits

Yash Kheshwani, Avishek Ghosh, Nikhil Karamchandani

Adaptive-Gradient Policy Optimization: Enhancing Policy Learning in Non-Smooth Differentiable Simulations

Feng Gao, Liangzhi Shi, Shenao Zhang et al.

Is Kernel Prediction More Powerful than Gating in Convolutional Neural Networks?

Lorenz K. Muller

Causal Effect Identification in lvLiNGAM from Higher-Order Cumulants

Daniele Tramontano, Yaroslav Kivva, Saber Salehkaleybar et al.

Federated Node-Level Clustering Network with Cross-Subgraph Link Mending

Jingxin Liu, Renda Han, Wenxuan Tu et al.

Going Deeper into Locally Differentially Private Graph Neural Networks

Longzhu He, Chaozhuo Li, Peng Tang et al.

Safe and Robust Subgame Exploitation in Imperfect Information Games

Zhenxing Ge, Zheng Xu, Tianyu Ding et al.

Improving Reward Model Generalization from Adversarial Process Enhanced Preferences

Zhilong Zhang, Tian Xu, Xinghao Du et al.

KoopSTD: Reliable Similarity Analysis between Dynamical Systems via Approximating Koopman Spectrum with Timescale Decoupling

Shimin Zhang, Ziyuan Ye, Yinsong Yan et al.

Graph-Triggered Rising Bandits

Gianmarco Genalti, Marco Mussi, Nicola Gatti et al.

Reinforcement Learning within Tree Search for Fast Macro Placement

Zijie Geng, Jie Wang, Ziyan Liu et al.

Doubly Robust Fusion of Many Treatments for Policy Learning

Ke Zhu, Jianing Chu, Ilya Lipkovich et al.

Agnostic Learning of Mixed Linear Regressions with EM and AM Algorithms

Avishek Ghosh, Arya Mazumdar

Iterative Vectors: In-Context Gradient Steering without Backpropagation

Yiting Liu, Zhi-Hong Deng

Mutual Learning for SAM Adaptation: A Dual Collaborative Network Framework for Source-Free Domain Transfer

Yabo Liu, Waikeung Wong, Chengliang Liu et al.

Learning Configurations for Data-Driven Multi-Objective Optimization

Zhiyang Chen, Hailong Yao, Xia Yin

Does Label Smoothing Help Deep Partial Label Learning?

Xiuwen Gong, Nitin Bisht, Guandong Xu

Balancing Model Efficiency and Performance: Adaptive Pruner for Long-tailed Data

Zhe Zhao, HaiBin Wen, Pengkun Wang et al.

Evolution-Inspired Loss Functions for Protein Representation Learning

Chengyue Gong, Adam Klivans, James Loy et al.

E$^2$GAN: Efficient Training of Efficient GANs for Image-to-Image Translation

Yifan Gong, Zheng Zhan, Qing Jin et al.

Incorporating probabilistic domain knowledge into deep multiple instance learning

Ghadi S. Al Hajj, Aliaksandr Hubin, Chakravarthi Kanduri et al.

Fine-grained Classes and How to Find Them

Matej Grcic, Artyom Gadetsky, Maria Brbic

Kona: An Efficient Privacy-Preservation Framework for KNN Classification by Communication Optimization

Guopeng Lin, Ruisheng Zhou, Shuyu Chen et al.

Learning to Reuse Policies in State Evolvable Environments

Ziqian Zhang, Bohan Yang, Lihe Li et al.

EDISON: Enhanced Dictionary-Induced Tensorized Incomplete Multi-View Clustering with Gaussian Error Rank Minimization

Zhibin Gu, Zhendong Li, Songhe Feng

E-LDA: Toward Interpretable LDA Topic Models with Strong Guarantees in Logarithmic Parallel Time

Adam Breuer

Complete-Tree Space Favors Data-Efficient Link Prediction

Chi Gao, Lukai Li, Yancheng Zhou et al.

ACM-MILP: Adaptive Constraint Modification via Grouping and Selection for Hardness-Preserving MILP Instance Generation

Ziao Guo, Yang Li, Chang Liu et al.

Compressing Large Language Models by Joint Sparsification and Quantization

Jinyang Guo, Jianyu Wu, Zining Wang et al.

Enhancing Graph Invariant Learning from a Negative Inference Perspective

Kuo Yang, Zhengyang Zhou, Qihe Huang et al.

Federated Disentangled Tuning with Textual Prior Decoupling and Visual Dynamic Adaptation

Yihao Yang, Wenke Huang, Guancheng Wan et al.

Widening the Network Mitigates the Impact of Data Heterogeneity on FedAvg

Like Jian, Dong Liu

MITIGATING OVER-EXPLORATION IN LATENT SPACE OPTIMIZATION USING LES

Omer Ronen, Ahmed Imtiaz Humayun, Richard Baraniuk et al.

Analytical Construction on Geometric Architectures: Transitioning from Static to Temporal Link Prediction

Yadong Sun, Xiaofeng Cao, Ivor Tsang et al.

Socialized Coevolution: Advancing a Better World through Cross-Task Collaboration

Xinjie Yao, Yu Wang, Pengfei Zhu et al.

SIN: Selective and Interpretable Normalization for Long-Term Time Series Forecasting

Lu Han, Han-Jia Ye, De-Chuan Zhan

COKE: Core Kernel for More Efficient Approximation of Kernel Weights in Multiple Kernel Clustering

Weixuan Liang, Xinwang Liu, KE LIANG et al.

Binary Decomposition: A Problem Transformation Perspective for Open-Set Semi-Supervised Learning

Jun-Yi Hang, Min-Ling Zhang

Semi-Supervised Blind Quality Assessment with Confidence-quantifiable Pseudo-label Learning for Authentic Images

Yan Zhong, Chenxi Yang, Suyuan Zhao et al.

Tight and Fast Bounds for Multi-Label Learning

Yi-Fan Zhang, Min-Ling Zhang

Convergence Guarantees for the DeepWalk Embedding on Block Models

Christopher Harker, Aditya Bhaskara

Estimating the Permanent by Nesting Importance Sampling

Juha Harviainen, Mikko Koivisto

Position: $C^*$-Algebraic Machine Learning $-$ Moving in a New Direction

Yuka Hashimoto, Masahiro Ikeda, Hachem Kadri

Generalization Analysis for Controllable Learning

Yi-Fan Zhang, Xiao Zhang, Min-Ling Zhang

Neural Event-Triggered Control with Optimal Scheduling

Luan Yang, Jingdong Zhang, Qunxi Zhu et al.

Deep Neural Room Acoustics Primitive

Yuhang He, Anoop Cherian, Gordon Wichern et al.

Near-optimal Sketchy Natural Gradients for Physics-Informed Neural Networks

Maricela Best Mckay, Avleen Kaur, Chen Greif et al.

ReDiffuser: Reliable Decision-Making Using a Diffuser with Confidence Estimation

Nantian He, Shaohui Li, Zhi Li et al.

Domain-wise Data Acquisition to Improve Performance under Distribution Shift

Yue He, Dongbai Li, Pengfei Tian et al.

From Uncertain to Safe: Conformal Adaptation of Diffusion Models for Safe PDE Control

Peiyan Hu, Xiaowei Qian, Wenhao Deng et al.

Ambiguity-Aware Abductive Learning

Hao-Yuan He, Hui Sun, Zheng Xie et al.

Assessing Safety Risks and Quantization-aware Safety Patching for Quantized Large Language Models

Kejia Chen, Jiawen Zhang, Jiacong Hu et al.

Learning Surrogates for Offline Black-Box Optimization via Gradient Matching

Minh Hoang, Azza Fadhel, Aryan Deshwal et al.

Estimating Unknown Population Sizes Using the Hypergeometric Distribution

Liam Hodgson, Danilo Bzdok

AutoCATE: End-to-End, Automated Treatment Effect Estimation

Toon Vanderschueren, Tim Verdonck, Mihaela van der Schaar et al.

Enhancing Sufficient Dimension Reduction via Hellinger Correlation

Seungbeom Hong, Ilmun Kim, Jun Song

Maestro: Uncovering Low-Rank Structures via Trainable Decomposition

Samuel Horváth, Stefanos Laskaridis, Shashank Rajput et al.

Breaking the $n^{1.5}$ Additive Error Barrier for Private and Efficient Graph Sparsification via Private Expander Decomposition

Anders Aamand, Justin Chen, Mina Dalirrooyfard et al.

Task-aware Orthogonal Sparse Network for Exploring Shared Knowledge in Continual Learning

Yusong Hu, De Cheng, Dingwen Zhang et al.

Provable Benefit of Random Permutations over Uniform Sampling in Stochastic Coordinate Descent

Donghwa Kim, Jaewook Lee, Chulhee Yun

Guided Structural Inference: Leveraging Priors with Soft Gating Mechanisms

Aoran Wang, Xinnan Dai, Jun Pang

Pseudo-Calibration: Improving Predictive Uncertainty Estimation in Unsupervised Domain Adaptation

Dapeng Hu, Jian Liang, Xinchao Wang et al.

The Sparse-Plus-Low-Rank Quasi-Newton Method for Entropic-Regularized Optimal Transport

Chenrui Wang, Yixuan Qiu

High-Performance Temporal Reversible Spiking Neural Networks with $\mathcal{O}(L)$ Training Memory and $\mathcal{O}(1)$ Inference Cost

JiaKui Hu, Man Yao, Xuerui Qiu et al.

Auctionformer: A Unified Deep Learning Algorithm for Solving Equilibrium Strategies in Auction Games

Kexin Huang, Ziqian Chen, xue wang et al.

Optimal Auction Design in the Joint Advertising

Yang Li, Yuchao Ma, Qi Qi

Near-Linear Time Approximation Algorithms for k-means with Outliers

Junyu Huang, Qilong Feng, Ziyun Huang et al.

Generative Human Trajectory Recovery via Embedding-Space Conditional Diffusion

KAIJUN LIU, Sijie Ruan, Liang Zhang et al.

Attributes Shape the Embedding Space of Face Recognition Models

Pierrick Leroy, Antonio Mastropietro, Marco Nurisso et al.

InstructSpeech: Following Speech Editing Instructions via Large Language Models

Rongjie Huang, Ruofan Hu, Yongqi Wang et al.

HyperIV: Real-time Implied Volatility Smoothing

Yongxin Yang, Wenqi Chen, Chao Shu et al.

µnit Scaling: Simple and Scalable FP8 LLM Training

Saaketh Narayan, Abhay Gupta, Mansheej Paul et al.

MFTN: A Multi-scale Feature Transfer Network Based on IMatchFormer for Hyperspectral Image Super-Resolution

Shuying Huang, Mingyang Ren, Yong Yang et al.

On Which Nodes Does GCN Fail? Enhancing GCN From the Node Perspective

Jincheng Huang, Jialie SHEN, Xiaoshuang Shi et al.

Quasi-Monte Carlo Features for Kernel Approximation

ZHEN HUANG, Jiajin Sun, Yian Huang

Open Materials Generation with Stochastic Interpolants

Philipp Höllmer, Thomas Egg, Maya Martirossyan et al.

Interaction-based Retrieval-augmented Diffusion Models for Protein-specific 3D Molecule Generation

Zhilin Huang, Ling Yang, Xiangxin Zhou et al.

Reducing Item Discrepancy via Differentially Private Robust Embedding Alignment for Privacy-Preserving Cross Domain Recommendation

Weiming Liu, Xiaolin Zheng, Chaochao Chen et al.

Position: The Platonic Representation Hypothesis

Minyoung Huh, Brian Cheung, Tongzhou Wang et al.

Provably Cost-Sensitive Adversarial Defense via Randomized Smoothing

Yuan Xin, Dingfan Chen, Michael Backes et al.

Adapting Pretrained ViTs with Convolution Injector for Visuo-Motor Control

Dongyoon Hwang, Byungkun Lee, Hojoon Lee et al.

Asymmetric Decision-Making in Online Knowledge Distillation: Unifying Consensus and Divergence

zhaowei chen, Borui Zhao, Yuchen Ge et al.

A Machine Learning Approach to Duality in Statistical Physics

Prateek Gupta, Andrea Ferrari, Nabil Iqbal

Online Non-stochastic Control with Partial Feedback

Yu-Hu Yan, Peng Zhao, Zhi-Hua Zhou

Rethinking DP-SGD in Discrete Domain: Exploring Logistic Distribution in the Realm of signSGD

Jonggyu Jang, Seongjin Hwang, Hyun Jong Yang

The Price of Linear Time: Error Analysis of Structured Kernel Interpolation

Alexander Moreno, Justin Xiao, Jonathan Mei

The Devil Is in the Details: Tackling Unimodal Spurious Correlations for Generalizable Multimodal Reward Models

Zichao Li, Xueru Wen, Jie Lou et al.

Learning-Augmented Algorithms for MTS with Bandit Access to Multiple Predictors

Matei Gabriel Cosa, Marek Elias

ROME is Forged in Adversity: Robust Distilled Datasets via Information Bottleneck

Zheng Zhou, Wenquan Feng, Qiaosheng Zhang et al.

Advancing Dynamic Sparse Training by Exploring Optimization Opportunities

Jie Ji, Gen Li, Lu Yin et al.

ACE: Off-Policy Actor-Critic with Causality-Aware Entropy Regularization

Tianying Ji, Yongyuan Liang, Yan Zeng et al.

Enhancing the Influence of Labels on Unlabeled Nodes in Graph Convolutional Networks

Jincheng Huang, Yujie Mo, Xiaoshuang Shi et al.

Calibrating Video Watch-time Predictions with Credible Prototype Alignment

Chao, Shisong Tang, Fan Li et al.

Gradual Transition from Bellman Optimality Operator to Bellman Operator in Online Reinforcement Learning

Motoki Omura, Kazuki Ota, Takayuki Osa et al.

AtlasD: Automatic Local Symmetry Discovery

Manu Bhat, Jonghyun Park, Jianke Yang et al.

NDOT: Neuronal Dynamics-based Online Training for Spiking Neural Networks

Haiyan Jiang, Giulia De Masi, Huan Xiong et al.

Merge-Friendly Post-Training Quantization for Multi-Target Domain Adaptation

Juncheol Shin, Minsang Seok, Seonggon Kim et al.

SuDA: Support-based Domain Adaptation for Sim2Real Hinge Joint Tracking with Flexible Sensors

Fang Jiawei, Haishan Song, Chengxu Zuo et al.

Leveraging Diffusion Model as Pseudo-Anomalous Graph Generator for Graph-Level Anomaly Detection

Jinyu Cai, Yunhe Zhang, Fusheng Liu et al.

Flow-field inference from neural data using deep recurrent networks

Timothy Doyeon Kim, Thomas Luo, Tankut Can et al.

iN2V: Bringing Transductive Node Embeddings to Inductive Graphs

Nicolas Lell, Ansgar Scherp

Settling the Maximin Share Fairness for Scheduling among Groups of Machines

Bo Li, Fangxiao WANG, Xing Shiji

PASS: Private Attributes Protection with Stochastic Data Substitution

Yizhuo Chen, Chun-Fu (Richard) Chen, Hsiang Hsu et al.

Catching Two Birds with One Stone: Reward Shaping with Dual Random Networks for Balancing Exploration and Exploitation

Haozhe Ma, Fangling Li, Jing Lim et al.

TUMTraf VideoQA: Dataset and Benchmark for Unified Spatio-Temporal Video Understanding in Traffic Scenes

Xingcheng Zhou, Konstantinos Larintzakis, Hao Guo et al.

Is Epistemic Uncertainty Faithfully Represented by Evidential Deep Learning Methods?

Mira Juergens, Nis Meinert, Viktor Bengs et al.

Disentangling Invariant Subgraph via Variance Contrastive Estimation under Distribution Shifts

Haoyang Li, Xin Wang, Xueling Zhu et al.

Thickness-aware E(3)-Equivariant 3D Mesh Neural Networks

Sungwon Kim, Namkyeong Lee, Yunyoung Doh et al.

Reward Translation via Reward Machine in Semi-Alignable MDPs

Yun Hua, Haosheng Chen, Wenhao Li et al.

Think Before You Act: Decision Transformers with Working Memory

Jikun Kang, Romain Laroche, Xingdi Yuan et al.

Exact Upper and Lower Bounds for the Output Distribution of Neural Networks with Random Inputs

Andrey Kofnov, Daniel Kapla, Ezio Bartocci et al.

Neural Tangent Kernels for Axis-Aligned Tree Ensembles

Ryuichi Kanoh, Mahito Sugiyama

On the Generalization of Equivariant Graph Neural Networks

Rafał Karczewski, Amauri Souza, Vikas Garg

Solving Satisfiability Modulo Counting Exactly with Probabilistic Circuits

Jinzhao Li, Nan Jiang, Yexiang Xue

Maintaining Proportional Committees with Dynamic Candidate Sets

Chris Dong, Jannik Peters

Pluvial Flood Emulation with Hydraulics-informed Message Passing

Arnold Kazadi, James Doss-Gollin, Arlei Silva

Bayesian Neural Scaling Law Extrapolation with Prior-Data Fitted Networks

Dongwoo Lee, Dong Bok Lee, Steven Adriaensen et al.

A Universal Transfer Theorem for Convex Optimization Algorithms Using Inexact First-order Oracles

Phillip Kerger, Marco Molinaro, Hongyi Jiang et al.

Shifting Time: Time-series Forecasting with Khatri-Rao Neural Operators

Srinath Dama, Kevin L Course, Prasanth B Nair

Neural Tangent Kernels Motivate Cross-Covariance Graphs in Neural Networks

Shervin Khalafi, Saurabh Sihag, Alejandro Ribeiro

Non-Stationary Predictions May Be More Informative: Exploring Pseudo-Labels with a Two-Phase Pattern of Training Dynamics

Hongbin Pei, Jingxin Hai, Yu Li et al.

Off-policy Evaluation Beyond Overlap: Sharp Partial Identification Under Smoothness

Samir Khan, Martin Saveski, Johan Ugander

When Dynamic Data Selection Meets Data Augmentation: Achieving Enhanced Training Acceleration

Suorong Yang, Peng Ye, Furao Shen et al.

K$^2$IE: Kernel Method-based Kernel Intensity Estimators for Inhomogeneous Poisson Processes

Hideaki Kim, Tomoharu Iwata, Akinori Fujino

Achieving Lossless Gradient Sparsification via Mapping to Alternative Space in Federated Learning

Do-Yeon Kim, Dong-Jun Han, Jun Seo et al.

A Non-Asymptotic Convergent Analysis for Scored-Based Graph Generative Model via a System of Stochastic Differential Equations

Junwei Su, Chuan Wu

Learning Safe Control via On-the-Fly Bandit Exploration

Alexandre Capone, Ryan Cosner, Aaron Ames et al.

Synergistic Integration of Coordinate Network and Tensorial Feature for Improving Neural Radiance Fields from Sparse Inputs

Mingyu Kim, Kim Jun-Seong, Se-Young Yun et al.

Clustered Federated Learning via Gradient-based Partitioning

Heasung Kim, Hyeji Kim, Gustavo De Veciana

Unpaired Point Cloud Completion via Unbalanced Optimal Transport

Taekyung Lee, Jaemoo Choi, Jaewoong Choi et al.

Right Time to Learn: Promoting Generalization via Bio-inspired Spacing Effect in Knowledge Distillation

Guanglong Sun, Hongwei Yan, Liyuan Wang et al.

Risk-Sensitive Policy Optimization via Predictive CVaR Policy Gradient

Ju-Hyun Kim, Seungki Min

Privacy-Preserving Embedding via Look-up Table Evaluation with Fully Homomorphic Encryption

Jae-yun Kim, Saerom Park, Joohee Lee et al.

Advancing Personalized Learning with Neural Collapse for Long-Tail Challenge

Hanglei Hu, Yingying Guo, Zhikang Chen et al.

Discovering Features with Synergistic Interactions in Multiple Views

Chohee Kim, M van der Schaar, Changhee Lee

InfoSAM: Fine-Tuning the Segment Anything Model from An Information-Theoretic Perspective

Yuanhong Zhang, Muyao Yuan, Weizhan Zhang et al.

PF3plat: Pose-Free Feed-Forward 3D Gaussian Splatting for Novel View Synthesis

Sunghwan Hong, Jaewoo Jung, Heeseong Shin et al.

Expressive Score-Based Priors for Distribution Matching with Geometry-Preserving Regularization

Ziyu Gong, Jim Lim, David I. Inouye

Online Linear Classification with Massart Noise

Ilias Diakonikolas, Vasilis Kontonis, Christos Tzamos et al.

Reaction Graph: Towards Reaction-Level Modeling for Chemical Reactions with 3D Structures

Yingzhao Jian, Yue Zhang, Ying Wei et al.

Distributed Retraction-Free and Communication-Efficient Optimization on the Stiefel Manifold

Yilong Song, Peijin Li, Bin Gao et al.

The Computational Complexity of Finding Second-Order Stationary Points

Andreas Kontogiannis, Vasilis Pollatos, Sotiris Kanellopoulos et al.

convSeq: Fast and Scalable Method for Detecting Patterns in Spike Data

Roman Koshkin, Tomoki Fukai

A General Online Algorithm for Optimizing Complex Performance Metrics

Wojciech Kotlowski, Marek Wydmuch, Erik Schultheis et al.

Natural Perturbations for Black-box Training of Neural Networks by Zeroth-Order Optimization

Hiroshi Sawada, Kazuo Aoyama, Yuya Hikima

KISA: A Unified Keyframe Identifier and Skill Annotator for Long-Horizon Robotics Demonstrations

Longxin Kou, Fei Ni, Yan Zheng et al.

SAND: One-Shot Feature Selection with Additive Noise Distortion

Pedram Pad, Hadi Hammoud, Mohamad Dia et al.

Geometry-Aware Instrumental Variable Regression

Heiner Kremer, Bernhard Schölkopf

Sleeping Reinforcement Learning

Simone Drago, Marco Mussi, Alberto Maria Metelli

Trusted Multi-View Classification with Expert Knowledge Constraints

Xinyan Liang, Shijie Wang, Yuhua Qian et al.

One-Step Generalization Ratio Guided Optimization for Domain Generalization

Sumin Cho, Dongwon Kim, Kwangsu Kim

HyperNear: Unnoticeable Node Injection Attacks on Hypergraph Neural Networks

TSP: A Two-Sided Smoothed Primal-Dual Method for Nonconvex Bilevel Optimization

Songtao Lu

Adapting Precomputed Features for Efficient Graph Condensation

Yuan Li, Jun Hu, Zemin Liu et al.

Robust Inverse Graphics via Probabilistic Inference

Tuan Anh Le, Pavel Sountsov, Matthew Hoffman et al.

Knowledge Graphs Can be Learned with Just Intersection Features

Duy Le, Shaochen (Henry) Zhong, Zirui Liu et al.

Run-Time Task Composition with Safety Semantics

Kevin Leahy, Makai Mann, Zachary Serlin

Stationary Latent Weight Inference for Unreliable Observations from Online Test-Time Adaptation

Jae-Hong Lee, Joon Hyuk Chang

Locality Preserving Markovian Transition for Instance Retrieval

Jifei Luo, Wenzheng Wu, Hantao Yao et al.

Retrieval-Augmented Language Model for Knowledge-aware Protein Encoding

Zhang Jiasheng, Delvin Zhang, Shuang Liang et al.

Counterfactual Voting Adjustment for Quality Assessment and Fairer Voting in Online Platforms with Helpfulness Evaluation

Chang Liu, Yixin Wang, Moontae Lee

Supervised Matrix Factorization: Local Landscape Analysis and Applications

Joowon Lee, Hanbaek Lyu, Weixin Yao

Regret-Free Reinforcement Learning for Temporal Logic Specifications

R Majumdar, Mahmoud Salamati, Sadegh Soudjani

StrWAEs to Invariant Representations

Hyunjong Lee, Yedarm Seong, Sungdong Lee et al.

Training Greedy Policy for Proposal Batch Selection in Expensive Multi-Objective Combinatorial Optimization

Deokjae Lee, Hyun Oh Song, Kyunghyun Cho

DocKS-RAG: Optimizing Document-Level Relation Extraction through LLM-Enhanced Hybrid Prompt Tuning

Xiaolong Xu, Yibo Zhou, Haolong Xiang et al.

GTR: A General, Multi-View, and Dynamic Framework for Trajectory Representation Learning

Xiangheng Wang, Ziquan Fang, Chenglong Huang et al.

Customizing the Inductive Biases of Softmax Attention using Structured Matrices

Yilun Kuang, Noah Amsel, Sanae Lotfi et al.

DetKDS: Knowledge Distillation Search for Object Detectors

Lujun Li, Yufan Bao, Peijie Dong et al.

Purifying Quantization-conditioned Backdoors via Layer-wise Activation Correction with Distribution Approximation

Boheng Li, Yishuo Cai, Jisong Cai et al.

An Efficient Search-and-Score Algorithm for Ancestral Graphs using Multivariate Information Scores for Complex Non-linear and Categorical Data

Nikita Lagrange, Herve Isambert