Papers
Understanding the Evolution of Linear Regions in Deep Reinforcement Learning
Setareh Cohan, Nam Hee Kim, David Rolnick et al.
Understanding the Failure of Batch Normalization for Transformers in NLP
Jiaxi Wang, Ji Wu, Lei Huang
Understanding the Generalization Benefit of Normalization Layers: Sharpness Reduction
Kaifeng Lyu, Zhiyuan Li, Sanjeev Arora
UnfoldML: Cost-Aware and Uncertainty-Based Dynamic 2D Prediction for Multi-Stage Classification
Yanbo Xu, Alind Khare, Glenn Matlin et al.
UniCLIP: Unified Framework for Contrastive Language-Image Pre-training
Janghyeon Lee, Jongsuk Kim, Hyounguk Shon et al.
Unified Optimal Transport Framework for Universal Domain Adaptation
Wanxing Chang, Ye Shi, Hoang Tuan et al.
Unifying and Boosting Gradient-Based Training-Free Neural Architecture Search
YAO SHU, Zhongxiang Dai, Zhaoxuan Wu et al.
Unifying Voxel-based Representation with Transformer for 3D Object Detection
Yanwei Li, Yilun Chen, Xiaojuan Qi et al.
UniGAN: Reducing Mode Collapse in GANs using a Uniform Generator
Ziqi Pan, Li Niu, Liqing Zhang
Uni[MASK]: Unified Inference in Sequential Decision Problems
Micah Carroll, Orr Paradise, Jessy Lin et al.
Uni-Perceiver-MoE: Learning Sparse Generalist Models with Conditional MoEs
Jinguo Zhu, Xizhou Zhu, Wenhai Wang et al.
Universality of Group Convolutional Neural Networks Based on Ridgelet Analysis on Groups
Sho Sonoda, Isao Ishikawa, Masahiro Ikeda
Universally Expressive Communication in Multi-Agent Reinforcement Learning
Matthew Morris, Thomas D Barrett, Arnu Pretorius
Universal Rates for Interactive Learning
Steve Hanneke, Amin Karbasi, Shay Moran et al.
Unknown-Aware Domain Adversarial Learning for Open-Set Domain Adaptation
JoonHo Jang, Byeonghu Na, Dong Hyeok Shin et al.
Unlabelled Sample Compression Schemes for Intersection-Closed Classes and Extremal Classes
Joachim Rubinstein, Benjamin I. Rubinstein
Unpacking Reward Shaping: Understanding the Benefits of Reward Engineering on Sample Complexity
Abhishek Gupta, Aldo Pacchiano, Yuexiang Zhai et al.
Unravelling the Performance of Physics-informed Graph Neural Networks for Dynamical Systems
Abishek Thangamuthu, Gunjan Kumar, Suresh Bishnoi et al.
Unsupervised Adaptation from Repeated Traversals for Autonomous Driving
Yurong You, Cheng Perng Phoo, Katie Luo et al.
Unsupervised Causal Generative Understanding of Images
Titas Anciukevicius, Patrick Fox-Roberts, Edward Rosten et al.
Unsupervised Cross-Task Generalization via Retrieval Augmentation
Bill Yuchen Lin, Kangmin Tan, Chris Miller et al.
Unsupervised Domain Adaptation for Semantic Segmentation using Depth Distribution
Quanliang Wu, Huajun Liu
Unsupervised Image-to-Image Translation with Density Changing Regularization
Shaoan Xie, Qirong Ho, Kun Zhang
Unsupervised Learning for Combinatorial Optimization with Principled Objective Relaxation
Haoyu Peter Wang, Nan Wu, Hang Yang et al.
Unsupervised Learning From Incomplete Measurements for Inverse Problems
Julián Tachella, Dongdong Chen, Mike Davies