ICML 2024 Spotlight Papers
186 papers found • Page 1 of 4
A Circuit Domain Generalization Framework for Efficient Logic Synthesis in Chip Design
Zhihai Wang, Lei Chen, Jie Wang 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.
Adapt and Diffuse: Sample-adaptive Reconstruction via Latent Diffusion Models
Zalan Fabian, Berk Tinaz, Mahdi Soltanolkotabi
Adaptive Online Experimental Design for Causal Discovery
Muhammad Qasim Elahi, Lai Wei, Murat Kocaoglu et al.
Adaptive Proximal Gradient Methods Are Universal Without Approximation
Konstantinos Oikonomidis, Emanuel Laude, Puya Latafat et al.
A Distributional Analogue to the Successor Representation
Harley Wiltzer, Jesse Farebrother, Arthur Gretton et al.
A Geometric Decomposition of Finite Games: Convergence vs. Recurrence under Exponential Weights
Davide Legacci, Panayotis Mertikopoulos, Bary Pradelski
Agnostic Sample Compression Schemes for Regression
Idan Attias, Steve Hanneke, Aryeh Kontorovich et al.
Allocation Requires Prediction Only if Inequality Is Low
Ali Shirali, Rediet Abebe, Moritz Hardt
An Efficient Maximal Ancestral Graph Listing Algorithm
Tian-Zuo Wang, Wen-Bo Du, Zhi-Hua Zhou
A Subquadratic Time Algorithm for Robust Sparse Mean Estimation
Ankit Pensia
Asymptotics of feature learning in two-layer networks after one gradient-step
Hugo Cui, Luca Pesce, Yatin Dandi et al.
A Tensor Decomposition Perspective on Second-order RNNs
Maude Lizaire, Michael Rizvi-Martel, Marawan Gamal et al.
A Theoretical Analysis of Backdoor Poisoning Attacks in Convolutional Neural Networks
Boqi Li, Weiwei Liu
A Theory of Fault-Tolerant Learning
Changlong Wu, Yifan Wang, Ananth Grama
Auto-Encoding Morph-Tokens for Multimodal LLM
Kaihang Pan, Siliang Tang, Juncheng Li et al.
Automating the Selection of Proxy Variables of Unmeasured Confounders
Feng Xie, Zhengming Chen, Shanshan Luo et al.
Batch and match: black-box variational inference with a score-based divergence
Diana Cai, Chirag Modi, Loucas Pillaud-Vivien et al.
BBox-Adapter: Lightweight Adapting for Black-Box Large Language Models
Haotian Sun, Yuchen Zhuang, Wei Wei et al.
Behavior Generation with Latent Actions
Seungjae Lee, Yibin Wang, Haritheja Etukuru et al.
Best Arm Identification for Stochastic Rising Bandits
Marco Mussi, Alessandro Montenegro, Francesco Trovò et al.
Beyond Implicit Bias: The Insignificance of SGD Noise in Online Learning
Nikhil Vyas, Depen Morwani, Rosie Zhao et al.
Beyond the Norms: Detecting Prediction Errors in Regression Models
Andres Altieri, Marco Romanelli, Georg Pichler et al.
Block Acceleration Without Momentum: On Optimal Stepsizes of Block Gradient Descent for Least-Squares
Liangzu Peng, Wotao Yin
Bridging Data Gaps in Diffusion Models with Adversarial Noise-Based Transfer Learning
Xiyu Wang, Baijiong Lin, Daochang Liu et al.
By Tying Embeddings You Are Assuming the Distributional Hypothesis
Bertolotti Francesco, Walter Cazzola
Closing the Gap: Achieving Global Convergence (Last Iterate) of Actor-Critic under Markovian Sampling with Neural Network Parametrization
Mudit Gaur, Amrit Singh Bedi, Di Wang et al.
Code as Reward: Empowering Reinforcement Learning with VLMs
David Venuto, Mohammad Sami Nur Islam, Martin Klissarov et al.
Concentration Inequalities for General Functions of Heavy-Tailed Random Variables
Shaojie Li, Yong Liu
Conformal prediction for multi-dimensional time series by ellipsoidal sets
Chen Xu, Hanyang Jiang, Yao Xie
Convergence of Some Convex Message Passing Algorithms to a Fixed Point
Václav Voráček, Tomáš Werner
Convex Relaxations of ReLU Neural Networks Approximate Global Optima in Polynomial Time
Sungyoon Kim, Mert Pilanci
Craftax: A Lightning-Fast Benchmark for Open-Ended Reinforcement Learning
Michael Matthews, Michael Beukman, Benjamin Ellis et al.
Decoding-time Realignment of Language Models
Tianlin Liu, Shangmin Guo, Leonardo Martins Bianco et al.
Defining Neural Network Architecture through Polytope Structures of Datasets
Sangmin Lee, Abbas Mammadov, Jong Chul YE
Designing Decision Support Systems using Counterfactual Prediction Sets
Eleni Straitouri, Manuel Gomez-Rodriguez
Differentially Private Synthetic Data via Foundation Model APIs 2: Text
Chulin Xie, Zinan Lin, Arturs Backurs et al.
Discrete Latent Perspective Learning for Segmentation and Detection
Deyi Ji, Feng Zhao, Lanyun Zhu et al.
DISCRET: Synthesizing Faithful Explanations For Treatment Effect Estimation
Yinjun Wu, Mayank Keoliya, Kan Chen et al.
Distributed High-Dimensional Quantile Regression: Estimation Efficiency and Support Recovery
Caixing Wang, Ziliang Shen
Domain Generalisation via Imprecise Learning
Anurag Singh, Siu Lun Chau, Shahine Bouabid et al.
Do Models Explain Themselves? Counterfactual Simulatability of Natural Language Explanations
Yanda Chen, Ruiqi Zhong, Narutatsu Ri et al.
Double Variance Reduction: A Smoothing Trick for Composite Optimization Problems without First-Order Gradient
Hao Di, Haishan Ye, Yueling Zhang et al.
DRCT: Diffusion Reconstruction Contrastive Training towards Universal Detection of Diffusion Generated Images
Baoying Chen, Jishen Zeng, Jianquan Yang et al.
DsDm: Model-Aware Dataset Selection with Datamodels
Logan Engstrom
Dynamic Correlation Clustering in Sublinear Update Time
Vincent Cohen-Addad, Silvio Lattanzi, Andreas Maggiori et al.
Dynamic Facility Location in High Dimensional Euclidean Spaces
Sayan Bhattacharya, Gramoz Goranci, Shaofeng Jiang et al.
Efficient Pareto Manifold Learning with Low-Rank Structure
Weiyu CHEN, James Kwok
Efficient Precision and Recall Metrics for Assessing Generative Models using Hubness-aware Sampling
Yuanbang Liang, Jing Wu, Yu-Kun Lai et al.
EfficientZero V2: Mastering Discrete and Continuous Control with Limited Data
Shengjie Wang, Shaohuai Liu, Weirui Ye et al.