ICML 2024

2,610 papers

Masked Face Recognition with Generative-to-Discriminative Representations

Shiming Ge, Weijia Guo, Chenyu Li, Zhang Junzheng, Yong Li

Position: Categorical Deep Learning is an Algebraic Theory of All Architectures

Bruno Gavranović, Paul Lessard, Andrew Joseph Dudzik, Tamara von Glehn, João Guilherme Madeira Araújo

Variance-reduced Zeroth-Order Methods for Fine-Tuning Language Models

Tanmay Gautam, Youngsuk Park, Hao Zhou, Parameswaran Raman, Wooseok Ha

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

Mudit Gaur, Amrit Bedi, Di Wang, Vaneet Aggarwal

Can Looped Transformers Learn to Implement Multi-step Gradient Descent for In-context Learning?

Khashayar Gatmiry, Nikunj Saunshi, Sashank J. Reddi, Stefanie Jegelka, Sanjiv Kumar

Simplicity Bias via Global Convergence of Sharpness Minimization

Khashayar Gatmiry, Zhiyuan Li, Sashank J. Reddi, Stefanie Jegelka

Memorization Through the Lens of Curvature of Loss Function Around Samples

Isha Garg, Deepak Ravikumar, Kaushik Roy

LLark: A Multimodal Instruction-Following Language Model for Music

Joshua P Gardner, Simon Durand, Daniel Stoller, Rachel M Bittner

DRED: Zero-Shot Transfer in Reinforcement Learning via Data-Regularised Environment Design

Samuel Garcin, James Doran, Shangmin Guo, Christopher G. Lucas, Stefano V Albrecht

Projection-Free Online Convex Optimization with Time-Varying Constraints

Dan Garber, Ben Kretzu

Distribution Alignment Optimization through Neural Collapse for Long-tailed Classification

Jintong Gao, He Zhao, Dan dan Guo, Hongyuan Zha

Prompt-based Visual Alignment for Zero-shot Policy Transfer

Haihan Gao, Rui Zhang, Qi Yi, Hantao Yao, Haochen Li

Causal Customer Churn Analysis with Low-rank Tensor Block Hazard Model

Chenyin Gao, Zhiming Zhang, Shu Yang

Fast-Slow Test-Time Adaptation for Online Vision-and-Language Navigation

Junyu Gao, Xuan Yao, Changsheng Xu

Parameter-Efficient Fine-Tuning with Discrete Fourier Transform

Ziqi Gao, Qichao Wang, Aochuan Chen, Zijing Liu, Bingzhe Wu

Decoupling Learning and Decision-Making: Breaking the O(√T) Barrier in Online Resource Allocation with First-Order Methods

Wenzhi Gao, Chunlin Sun, Chenyu Xue, Yinyu Ye

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

Feng Gao, Liangzhi Shi, Shenao Zhang, Zhaoran Wang, Yi Wu

Non-convex Stochastic Composite Optimization with Polyak Momentum

Yuan Gao, Anton Rodomanov, Sebastian U Stich

Rethinking Specificity in SBDD: Leveraging Delta Score and Energy-Guided Diffusion

Bowen Gao, Minsi Ren, Yuyan Ni, Yanwen Huang, Bo Qiang

Speech Self-Supervised Learning Using Diffusion Model Synthetic Data

Heting Gao, Kaizhi Qian, Junrui Ni, Chuang Gan, Mark A. Hasegawa-Johnson

Private Heterogeneous Federated Learning Without a Trusted Server Revisited: Error-Optimal and Communication-Efficient Algorithms for Convex Losses

Changyu Gao, Andrew Lowy, Xingyu Zhou, Stephen Wright

DMTG: One-Shot Differentiable Multi-Task Grouping

Yuan Gao, Shuguo Jiang, Moran Li, Jin-Gang Yu, Gui-Song Xia

Multi-Agent Reinforcement Learning Meets Leaf Sequencing in Radiotherapy

Riqiang Gao, Florin-Cristian Ghesu, Simon Arberet, Shahab Basiri, Esa Kuusela

Linear Alignment: A Closed-form Solution for Aligning Human Preferences without Tuning and Feedback

Songyang Gao, Qiming Ge, Wei Shen, Shihan Dou, Junjie Ye

A Graph is Worth K Words: Euclideanizing Graph using Pure Transformer

Zhangyang Gao, Daize Dong, Cheng Tan, Jun Xia, Bozhen Hu

Stochastic Weakly Convex Optimization beyond Lipschitz Continuity

Wenzhi Gao, Qi Deng

An Intrinsic Vector Heat Network

Alexander Gao, Maurice Chu, Mubbasir Kapadia, Ming Lin, Hsueh-Ti Derek Liu

Energy-based Backdoor Defense without Task-Specific Samples and Model Retraining

Yudong Gao, Honglong Chen, peng sun, Zhe Li, Junjian Li

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

Hongchang Gao

Testing the Feasibility of Linear Programs with Bandit Feedback

Aditya Gangrade, Aditya Gopalan, Venkatesh Saligrama, Clayton Scott

Confidence Aware Inverse Constrained Reinforcement Learning

Sriram Ganapathi Subramanian, Guiliang Liu, Mohammed Elmahgiubi, Kasra Rezaee, Pascal Poupart

Reflective Policy Optimization

Yaozhong Gan, Renye Yan, Zhe Wu, Junliang Xing

Erasing the Bias: Fine-Tuning Foundation Models for Semi-Supervised Learning

Kai Gan, Tong Wei

Leverage Class-Specific Accuracy to Guide Data Generation for Improving Image Classification

Jay Gala, Pengtao Xie

Bring Your Own (Non-Robust) Algorithm to Solve Robust MDPs by Estimating The Worst Kernel

Uri Gadot, KAIXIN WANG, Navdeep Kumar, Kfir Yehuda Levy, Shie Mannor

Let Go of Your Labels with Unsupervised Transfer

Artyom Gadetsky, Yulun Jiang, Maria Brbic

Positive Concave Deep Equilibrium Models

Mateusz Gabor, Tomasz Piotrowski, Renato L. G. Cavalcante

Beyond the ROC Curve: Classification Trees Using Cost-Optimal Curves, with Application to Imbalanced Datasets

Magzhan Gabidolla, Arman Zharmagambetov, Miguel Á. Carreira-Perpiñán

KernelSHAP-IQ: Weighted Least Square Optimization for Shapley Interactions

Fabian Fumagalli, Maximilian Muschalik, Patrick Kolpaczki, Eyke Hüllermeier, Barbara Hammer

Uncertainty for Active Learning on Graphs

Dominik Fuchsgruber, Tom Wollschläger, Bertrand Charpentier, Antonio Oroz, Stephan Günnemann

FuRL: Visual-Language Models as Fuzzy Rewards for Reinforcement Learning

Yuwei Fu, Haichao Zhang, Di Wu, Wei Xu, Benoit Boulet

Towards Theoretical Understandings of Self-Consuming Generative Models

Shi Fu, Sen Zhang, Yingjie Wang, Xinmei Tian, Dacheng Tao

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

Jingwen Fu, Tao Yang, Yuwang Wang, Yan Lu, Nanning Zheng

Mean-field Underdamped Langevin Dynamics and its Spacetime Discretization

Qiang Fu, Ashia Camage Wilson

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

Han Fu, Jian Tan, Pinhan Zhang, Feifei Li, Jianling Sun

Language-guided Skill Learning with Temporal Variational Inference

Haotian Fu, Pratyusha Sharma, Elias Stengel-Eskin, George Konidaris, Nicolas Le Roux

Data Engineering for Scaling Language Models to 128K Context

Yao Fu, Rameswar Panda, Xinyao Niu, Xiang Yue, Hannaneh Hajishirzi

Hyperbolic Geometric Latent Diffusion Model for Graph Generation

Xingcheng Fu, Yisen Gao, Yuecen Wei, Qingyun Sun, Hao Peng

A Touch, Vision, and Language Dataset for Multimodal Alignment

Letian Fu, Gaurav Datta, Huang Huang, William Chung-Ho Panitch, Jaimyn Drake

Break the Sequential Dependency of LLM Inference Using Lookahead Decoding

Yichao Fu, Peter Bailis, Ion Stoica, Hao Zhang

Interpretability Illusions in the Generalization of Simplified Models

Dan Friedman, Andrew Kyle Lampinen, Lucas Dixon, Danqi Chen, Asma Ghandeharioun

Trustworthy Actionable Perturbations

Jesse Friedbaum, Sudarshan Adiga, Ravi Tandon

Trust the Model Where It Trusts Itself - Model-Based Actor-Critic with Uncertainty-Aware Rollout Adaption

Bernd Frauenknecht, Artur Eisele, Devdutt Subhasish, Friedrich Solowjow, Sebastian Trimpe

Fair Off-Policy Learning from Observational Data

Dennis Frauen, Valentyn Melnychuk, Stefan Feuerriegel

Unsupervised Zero-Shot Reinforcement Learning via Functional Reward Encodings

Kevin Frans, Seohong Park, Pieter Abbeel, Sergey Levine

Weisfeiler-Leman at the margin: When more expressivity matters

Billy Joe Franks, Christopher Morris, Ameya Velingker, Floris Geerts

Hyperbolic Active Learning for Semantic Segmentation under Domain Shift

Luca Franco, Paolo Mandica, Konstantinos Kallidromitis, Devin Guillory, Yu-Teng Li

Explaining Probabilistic Models with Distributional Values

Luca Franceschi, Michele Donini, Cédric Archambeau, Matthias Seeger

Initial Guessing Bias: How Untrained Networks Favor Some Classes

Emanuele Francazi, Aurelien Lucchi, Marco Baity-Jesi

Federated Combinatorial Multi-Agent Multi-Armed Bandits

Fares Fourati, Mohamed-Slim Alouini, Vaneet Aggarwal

Stochastic Q-learning for Large Discrete Action Spaces

Fares Fourati, Vaneet Aggarwal, Mohamed-Slim Alouini

Inverse-Variance Weighting for Estimation of Heterogeneous Treatment Effects

Aaron Fisher

Neuroexplicit Diffusion Models for Inpainting of Optical Flow Fields

Tom Fischer, Pascal Peter, Joachim Weickert, Eddy Ilg

Critical feature learning in deep neural networks

Kirsten Fischer, Javed Lindner, David Dahmen, Zohar Ringel, Michael Krämer

Cooperative Graph Neural Networks

Ben Finkelshtein, Xingyue Huang, Michael M. Bronstein, İsmail İlkan Ceylan

On Statistical Learning Theory for Distributional Inputs

Christian Fiedler, Pierre-François Massiani, Friedrich Solowjow, Sebastian Trimpe

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

Matthias Fey, Weihua Hu, Kexin Huang, Jan Eric Lenssen, Rishabh Ranjan

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

Thomas Ferté, Dan Dutartre, Boris P Hejblum, Romain Griffier, Vianney Jouhet

Trained Random Forests Completely Reveal your Dataset

Julien Ferry, Ricardo Fukasawa, Timothée Pascal, Thibaut Vidal

Promptbreeder: Self-Referential Self-Improvement via Prompt Evolution

Chrisantha Fernando, Dylan Sunil Banarse, Henryk Michalewski, Simon Osindero, Tim Rocktäschel

Active Ranking and Matchmaking, with Perfect Matchings

Hafedh El Ferchichi, Matthieu Lerasle, Vianney Perchet

GenCO: Generating Diverse Designs with Combinatorial Constraints

Aaron M Ferber, Arman Zharmagambetov, Taoan Huang, Bistra Dilkina, Yuandong Tian

AquaLoRA: Toward White-box Protection for Customized Stable Diffusion Models via Watermark LoRA

Weitao Feng, Wenbo Zhou, Jiyan He, Jie Zhang, Tianyi Wei

Improving Sample Efficiency of Model-Free Algorithms for Zero-Sum Markov Games

Songtao Feng, Ming Yin, Yu-Xiang Wang, Jing Yang, Yingbin Liang

Memory Efficient Neural Processes via Constant Memory Attention Block

Leo Feng, Frederick Tung, Hossein Hajimirsadeghi, Yoshua Bengio, Mohamed Osama Ahmed

Privacy Backdoors: Stealing Data with Corrupted Pretrained Models

Shanglun Feng, Florian Tramer

Prediction Accuracy of Learning in Games : Follow-the-Regularized-Leader meets Heisenberg

Yi Feng, Georgios Piliouras, Xiao Wang

UniCorn: A Unified Contrastive Learning Approach for Multi-view Molecular Representation Learning

Shikun Feng, Yuyan Ni, Minghao Li, Yanwen Huang, Zhi-ming Ma

Keypoint-based Progressive Chain-of-Thought Distillation for LLMs

Kaituo Feng, Changsheng Li, Xiaolu Zhang, Jun Zhou, Ye Yuan

DSD-DA: Distillation-based Source Debiasing for Domain Adaptive Object Detection

Yongchao Feng, Shiwei Li, Yingjie Gao, Ziyue Huang, Yanan Zhang

Fast White-Box Adversarial Streaming Without a Random Oracle

Ying Feng, Aayush Jain, David Woodruff

Resisting Stochastic Risks in Diffusion Planners with the Trajectory Aggregation Tree

Lang Feng, Pengjie Gu, Bo An, Gang Pan

Auto-Linear Phenomenon in Subsurface Imaging

Yinan Feng, Yinpeng Chen, Peng Jin, Shihang Feng, Youzuo Lin

Bayesian Exploration Networks

Mattie Fellows, Brandon Gary Kaplowitz, Christian Schroeder de Witt, Shimon Whiteson

Video-of-Thought: Step-by-Step Video Reasoning from Perception to Cognition

Hao Fei, Shengqiong Wu, Wei Ji, Hanwang Zhang, Meishan Zhang

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

Amirhossein Farzam, Allen Tannenbaum, Guillermo Sapiro

Position: Cracking the Code of Cascading Disparity Towards Marginalized Communities

Golnoosh Farnadi, Mohammad Havaei, Negar Rostamzadeh

Stop Regressing: Training Value Functions via Classification for Scalable Deep RL

Jesse Farebrother, Jordi Orbay, Quan Vuong, Adrien Ali Taiga, Yevgen Chebotar

Accelerating Heterogeneous Federated Learning with Closed-form Classifiers

Eros Fanı̀, Raffaello Camoriano, Barbara Caputo, Marco Ciccone

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

Weike Fang, Zhejian Zhou, Junzhou He, Weihang Wang

BayOTIDE: Bayesian Online Multivariate Time Series Imputation with Functional Decomposition

Shikai Fang, Qingsong Wen, Yingtao Luo, Shandian Zhe, Liang Sun

INViT: A Generalizable Routing Problem Solver with Invariant Nested View Transformer

Han Fang, Zhihao Song, Paul Weng, Yutong Ban

Exploring Correlations of Self-Supervised Tasks for Graphs

Taoran Fang, Wei Chow, Yifei Sun, Kaiqiao Han, Lvbin Ma

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

Luyang Fang, Yongkai Chen, Wenxuan Zhong, Ping Ma

Path-Guided Particle-based Sampling

Mingzhou Fan, Ruida Zhou, Chao Tian, Xiaoning Qian

DOGE: Domain Reweighting with Generalization Estimation

Simin Fan, Matteo Pagliardini, Martin Jaggi

Revisit the Essence of Distilling Knowledge through Calibration

Wen-shu Fan, Su Lu, Xin-Chun Li, De-Chuan Zhan, Le Gan

Locally Estimated Global Perturbations are Better than Local Perturbations for Federated Sharpness-aware Minimization

Ziqing Fan, Shengchao Hu, Jiangchao Yao, Gang Niu, Ya Zhang

On the Convergence of Projected Bures-Wasserstein Gradient Descent under Euclidean Strong Convexity

Junyi Fan, Yuxuan Han, Zijian Liu, Jian-Feng CAI, Yang Wang

On the Recoverability of Causal Relations from Temporally Aggregated I.I.D. Data

Shunxing Fan, Mingming Gong, Kun Zhang