ICML 2024 Papers
2,635 papers found • Page 6 of 53
Batch Singular Value Polarization and Weighted Semantic Augmentation for Universal Domain Adaptation
Ziqi Wang, Wei Wang, Chao Huang et al.
BAT: Learning to Reason about Spatial Sounds with Large Language Models
Zhisheng Zheng, Puyuan Peng, Ziyang Ma et al.
Bayesian Adaptation of Network Depth and Width for Continual Learning
Jeevan Thapa, Rui Li
Bayesian Design Principles for Offline-to-Online Reinforcement Learning
Hao Hu, yiqin yang, Jianing Ye et al.
Bayesian Exploration Networks
Mattie Fellows, Brandon Kaplowitz, Christian Schroeder de Witt et al.
Bayesian Knowledge Distillation: A Bayesian Perspective of Distillation with Uncertainty Quantification
Luyang Fang, Yongkai Chen, Wenxuan Zhong et al.
Bayesian Optimization of Function Networks with Partial Evaluations
Poompol Buathong, Jiayue Wan, Raul Astudillo et al.
Bayesian Power Steering: An Effective Approach for Domain Adaptation of Diffusion Models
Ding Huang, Ting Li, Jian Huang
Bayesian Program Learning by Decompiling Amortized Knowledge
Alessandro Palmarini, Christopher Lucas, Siddharth N
Bayesian Regret Minimization in Offline Bandits
Marek Petrik, Guy Tennenholtz, Mohammad Ghavamzadeh
Bayesian Uncertainty for Gradient Aggregation in Multi-Task Learning
Idan Achituve, Idit Diamant, Arnon Netzer et al.
BayOTIDE: Bayesian Online Multivariate Time Series Imputation with Functional Decomposition
Shikai Fang, Qingsong Wen, Yingtao Luo et al.
BBox-Adapter: Lightweight Adapting for Black-Box Large Language Models
Haotian Sun, Yuchen Zhuang, Wei Wei et al.
BECoTTA: Input-dependent Online Blending of Experts for Continual Test-time Adaptation
Daeun Lee, Jaehong Yoon, Sung Ju Hwang
Behavior Generation with Latent Actions
Seungjae Lee, Yibin Wang, Haritheja Etukuru et al.
BeigeMaps: Behavioral Eigenmaps for Reinforcement Learning from Images
Sandesh Adhikary, Anqi Li, Byron Boots
Benchmarking and Building Long-Context Retrieval Models with LoCo and M2-BERT
Jon Saad-Falcon, Daniel Y Fu, Simran Arora et al.
Benchmarking Deletion Metrics with the Principled Explanations
Yipei Wang, Xiaoqian Wang
Benign Overfitting in Adversarial Training of Neural Networks
Yunjuan Wang, Kaibo Zhang, Raman Arora
Benign Overfitting in Two-Layer ReLU Convolutional Neural Networks for XOR Data
Xuran Meng, Difan Zou, Yuan Cao
Bespoke Non-Stationary Solvers for Fast Sampling of Diffusion and Flow Models
Neta Shaul, Uriel Singer, Ricky T. Q. Chen et al.
Best Arm Identification for Stochastic Rising Bandits
Marco Mussi, Alessandro Montenegro, Francesco Trovò et al.
Best of Both Worlds Guarantees for Smoothed Online Quadratic Optimization
Neelkamal Bhuyan, Debankur Mukherjee, Adam Wierman
Better & Faster Large Language Models via Multi-token Prediction
Fabian Gloeckle, Badr Youbi Idrissi, Baptiste Roziere et al.
Better Locally Private Sparse Estimation Given Multiple Samples Per User
Yuheng Ma, Ke Jia, Hanfang Yang
Better Safe than Sorry: Pre-training CLIP against Targeted Data Poisoning and Backdoor Attacks
Wenhan Yang, Jingdong Gao, Baharan Mirzasoleiman
BetterV: Controlled Verilog Generation with Discriminative Guidance
Zehua Pei, Huiling Zhen, Mingxuan Yuan et al.
Beyond Chinchilla-Optimal: Accounting for Inference in Language Model Scaling Laws
Nikhil Sardana, Jacob Portes, Alexandre (Sasha) Doubov et al.
Beyond ELBOs: A Large-Scale Evaluation of Variational Methods for Sampling
Denis Blessing, Xiaogang Jia, Johannes Esslinger et al.
Beyond Implicit Bias: The Insignificance of SGD Noise in Online Learning
Nikhil Vyas, Depen Morwani, Rosie Zhao et al.
Beyond Individual Input for Deep Anomaly Detection on Tabular Data
Hugo Thimonier, Fabrice Popineau, Arpad Rimmel et al.
Beyond Point Prediction: Score Matching-based Pseudolikelihood Estimation of Neural Marked Spatio-Temporal Point Process
Zichong Li, Qunzhi Xu, Zhenghao Xu et al.
Beyond Regular Grids: Fourier-Based Neural Operators on Arbitrary Domains
Levi Lingsch, Mike Yan Michelis, Emmanuel de Bézenac et al.
Beyond Sole Strength: Customized Ensembles for Generalized Vision-Language Models
Zhihe Lu, Jiawang Bai, Xin Li et al.
Beyond the Calibration Point: Mechanism Comparison in Differential Privacy
Georgios Kaissis, Stefan Kolek, Borja de Balle Pigem et al.
Beyond the Federation: Topology-aware Federated Learning for Generalization to Unseen Clients
Mengmeng Ma, Tang Li, Xi Peng
Beyond the Norms: Detecting Prediction Errors in Regression Models
Andres Altieri, Marco Romanelli, Georg Pichler et al.
Beyond the ROC Curve: Classification Trees Using Cost-Optimal Curves, with Application to Imbalanced Datasets
Magzhan Gabidolla, Arman Zharmagambetov, Miguel Carreira-Perpinan
Be Your Own Neighborhood: Detecting Adversarial Examples by the Neighborhood Relations Built on Self-Supervised Learning
Zhiyuan He, Yijun Yang, Pin-Yu Chen et al.
Bias of Stochastic Gradient Descent or the Architecture: Disentangling the Effects of Overparameterization of Neural Networks
Amit Peleg, Matthias Hein
Bidirectional Reciprocative Information Communication for Few-Shot Semantic Segmentation
Yuanwei Liu, Junwei Han, Xiwen Yao et al.
BiE: Bi-Exponent Block Floating-Point for Large Language Models Quantization
Lancheng Zou, Wenqian Zhao, Shuo Yin et al.
Bifurcated Attention for Single-Context Large-Batch Sampling
Ben Athiwaratkun, Sujan Kumar Gonugondla, Sanjay Krishna Gouda et al.
Biharmonic Distance of Graphs and its Higher-Order Variants: Theoretical Properties with Applications to Centrality and Clustering
Mitchell Black, Lucy Lin, Weng-Keen Wong et al.
BiLLM: Pushing the Limit of Post-Training Quantization for LLMs
Wei Huang, Yangdong Liu, Haotong Qin et al.
Binary Decomposition: A Problem Transformation Perspective for Open-Set Semi-Supervised Learning
Jun-Yi Hang, Min-Ling Zhang
Binning as a Pretext Task: Improving Self-Supervised Learning in Tabular Domains
Kyungeun Lee, Ye Seul Sim, Hye-Seung Cho et al.
Bipartite Matching in Massive Graphs: A Tight Analysis of EDCS
Amir Azarmehr, Soheil Behnezhad, Mohammad Roghani
BiSHop: Bi-Directional Cellular Learning for Tabular Data with Generalized Sparse Modern Hopfield Model
Chenwei Xu, Yu-Chao Huang, Jerry Yao-Chieh Hu et al.
Bivariate Causal Discovery using Bayesian Model Selection
Anish Dhir, Samuel Power, Mark van der Wilk