ICML 2024 Papers
2,635 papers found • Page 1 of 53
$\bf{\Phi}_\textrm{Flow}$: Differentiable Simulations for PyTorch, TensorFlow and Jax
Philipp Holl, Nils Thuerey
$f$-Divergence Based Classification: Beyond the Use of Cross-Entropy
Nicola Novello, Andrea Tonello
$H$-Consistency Guarantees for Regression
Anqi Mao, Mehryar Mohri, Yutao Zhong
$\mathtt{VITS}$ : Variational Inference Thompson Sampling for contextual bandits
Pierre Clavier, Tom Huix, Alain Oliviero Durmus
${\rm E}(3)$-Equivariant Actor-Critic Methods for Cooperative Multi-Agent Reinforcement Learning
Dingyang Chen, Qi Zhang
$S^2$IP-LLM: Semantic Space Informed Prompt Learning with LLM for Time Series Forecasting
Zijie Pan, Yushan Jiang, Sahil Garg et al.
$\texttt{MoE-RBench}$: Towards Building Reliable Language Models with Sparse Mixture-of-Experts
Guanjie Chen, Xinyu Zhao, Tianlong Chen et al.
3D Geometric Shape Assembly via Efficient Point Cloud Matching
Nahyuk Lee, Juhong Min, Junha Lee et al.
3D-VLA: A 3D Vision-Language-Action Generative World Model
Haoyu Zhen, Xiaowen Qiu, Peihao Chen et al.
A2Q+: Improving Accumulator-Aware Weight Quantization
Ian Colbert, Alessandro Pappalardo, Jakoba Petri-Koenig et al.
A3S: A General Active Clustering Method with Pairwise Constraints
Xun Deng, Junlong Liu, Han Zhong et al.
A Bayesian Approach to Online Planning
Nir Greshler, David Ben Eli, Carmel Rabinovitz et al.
A Bias-Variance-Covariance Decomposition of Kernel Scores for Generative Models
Sebastian Gregor Gruber, Florian Buettner
Absolute Policy Optimization: Enhancing Lower Probability Bound of Performance with High Confidence
Weiye Zhao, Feihan Li, Yifan Sun et al.
Accelerated Algorithms for Constrained Nonconvex-Nonconcave Min-Max Optimization and Comonotone Inclusion
Yang Cai, Argyris Oikonomou, Weiqiang Zheng
Accelerated Policy Gradient for s-rectangular Robust MDPs with Large State Spaces
Ziyi Chen, Heng Huang
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.
Accelerated Speculative Sampling Based on Tree Monte Carlo
Zhengmian Hu, Heng Huang
Accelerating Convergence in Bayesian Few-Shot Classification
Tianjun Ke, Haoqun Cao, Feng Zhou
Accelerating Convergence of Score-Based Diffusion Models, Provably
Gen Li, Yu Huang, Timofey Efimov et al.
Accelerating Federated Learning with Quick Distributed Mean Estimation
Ran Ben Basat, Shay Vargaftik, Amit Portnoy et al.
Accelerating Heterogeneous Federated Learning with Closed-form Classifiers
Eros Fanì, Raffaello Camoriano, Barbara Caputo et al.
Accelerating Iterative Retrieval-augmented Language Model Serving with Speculation
Zhihao Zhang, Alan Zhu, Lijie Yang et al.
Accelerating Legacy Numerical Solvers by Non-intrusive Gradient-based Meta-solving
Sohei Arisaka, Qianxiao Li
Accelerating Look-ahead in Bayesian Optimization: Multilevel Monte Carlo is All you Need
Shangda Yang, Vitaly Zankin, Maximilian Balandat et al.
Accelerating Parallel Sampling of Diffusion Models
Zhiwei Tang, Jiasheng Tang, Hao Luo et al.
Accelerating PDE Data Generation via Differential Operator Action in Solution Space
huanshuo dong, Hong Wang, Haoyang Liu et al.
Accelerating Transformer Pre-training with 2:4 Sparsity
Yuezhou Hu, Kang Zhao, Weiyu Huang et al.
Accurate LoRA-Finetuning Quantization of LLMs via Information Retention
Haotong Qin, Xudong Ma, Xingyu Zheng et al.
ACE: Off-Policy Actor-Critic with Causality-Aware Entropy Regularization
Tianying Ji, Yongyuan Liang, Yan Zeng et al.
Achieving Lossless Gradient Sparsification via Mapping to Alternative Space in Federated Learning
Do-Yeon Kim, Dong-Jun Han, Jun Seo et al.
Achieving Margin Maximization Exponentially Fast via Progressive Norm Rescaling
Mingze Wang, Zeping Min, Lei Wu
A Circuit Domain Generalization Framework for Efficient Logic Synthesis in Chip Design
Zhihai Wang, Lei Chen, Jie Wang et al.
A Closer Look at the Limitations of Instruction Tuning
Sreyan Ghosh, Chandra Kiran Evuru, Sonal Kumar 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.
A Computational Framework for Solving Wasserstein Lagrangian Flows
Kirill Neklyudov, Rob Brekelmans, Alexander Tong et al.
A connection between Tempering and Entropic Mirror Descent
Nicolas Chopin, Francesca R Crucinio, Anna Korba
A Contextual Combinatorial Bandit Approach to Negotiation
Yexin Li, Zhancun Mu, Siyuan Qi
ACPO: A Policy Optimization Algorithm for Average MDPs with Constraints
Akhil Agnihotri, Rahul Jain, Haipeng Luo
Acquiring Diverse Skills using Curriculum Reinforcement Learning with Mixture of Experts
Onur Celik, Aleksandar Taranovic, Gerhard Neumann
Acquisition Conditioned Oracle for Nongreedy Active Feature Acquisition
Michael Valancius, Maxwell Lennon, Junier Oliva
Actions Speak Louder than Words: Trillion-Parameter Sequential Transducers for Generative Recommendations
Jiaqi Zhai, Yunxing Liao, Xing Liu et al.
Activation-Descent Regularization for Input Optimization of ReLU Networks
Hongzhan Yu, Sicun Gao
Active Adaptive Experimental Design for Treatment Effect Estimation with Covariate Choice
Masahiro Kato, Oga Akihiro, Wataru Komatsubara et al.
Active Label Correction for Semantic Segmentation with Foundation Models
Hoyoung Kim, SEHYUN HWANG, Suha Kwak et al.
Active Preference Learning for Large Language Models
William Muldrew, Peter Hayes, Mingtian Zhang et al.
Active Ranking and Matchmaking, with Perfect Matchings
Hafedh El Ferchichi, Matthieu LERASLE, Vianney Perchet
Active Statistical Inference
Tijana Zrnic, Emmanuel J Candes
AD3: Implicit Action is the Key for World Models to Distinguish the Diverse Visual Distractors
Yucen Wang, Shenghua Wan, Le Gan et al.
Adapt and Diffuse: Sample-adaptive Reconstruction via Latent Diffusion Models
Zalan Fabian, Berk Tinaz, Mahdi Soltanolkotabi