Papers
Variational Open-Domain Question Answering
Valentin Liévin, Andreas Geert Motzfeldt, Ida Riis Jensen et al.
Variational Sparse Inverse Cholesky Approximation for Latent Gaussian Processes via Double Kullback-Leibler Minimization
Jian Cao, Myeongjong Kang, Felix Jimenez et al.
VectorMapNet: End-to-end Vectorized HD Map Learning
Yicheng Liu, Tianyuan Yuan, Yue Wang et al.
Vector Quantized Wasserstein Auto-Encoder
Long Tung Vuong, Trung Le, He Zhao et al.
Vector-Valued Control Variates
Zhuo Sun, Alessandro Barp, Francois-Xavier Briol
Vertical Federated Graph Neural Network for Recommender System
Peihua Mai, Yan Pang
VIMA: Robot Manipulation with Multimodal Prompts
Yunfan Jiang, Agrim Gupta, Zichen Zhang et al.
Von Mises Mixture Distributions for Molecular Conformation Generation
Kirk Swanson, Jake Lawrence Williams, Eric M Jonas
Warm-Start Actor-Critic: From Approximation Error to Sub-optimality Gap
Hang Wang, Sen Lin, Junshan Zhang
Wasserstein Barycenter Matching for Graph Size Generalization of Message Passing Neural Networks
Xu Chu, Yujie Jin, Xin Wang et al.
Weakly Supervised Regression with Interval Targets
Xin Cheng, Yuzhou Cao, Ximing Li et al.
Weak Proxies are Sufficient and Preferable for Fairness with Missing Sensitive Attributes
Zhaowei Zhu, Yuanshun Yao, Jiankai Sun et al.
Weighted Flow Diffusion for Local Graph Clustering with Node Attributes: an Algorithm and Statistical Guarantees
Shenghao Yang, Kimon Fountoulakis
Weighted Sampling without Replacement for Deep Top-$k$ Classification
Dieqiao Feng, Yuanqi Du, Carla P Gomes et al.
Weighted Tallying Bandits: Overcoming Intractability via Repeated Exposure Optimality
Dhruv Malik, Conor Igoe, Yuanzhi Li et al.
What Can Be Learnt With Wide Convolutional Neural Networks?
Francesco Cagnetta, Alessandro Favero, Matthieu Wyart
What can online reinforcement learning with function approximation benefit from general coverage conditions?
Fanghui Liu, Luca Viano, Volkan Cevher
What do CNNs Learn in the First Layer and Why? A Linear Systems Perspective
Rhea Chowers, Yair Weiss
What is Essential for Unseen Goal Generalization of Offline Goal-conditioned RL?
Rui Yang, Lin Yong, Xiaoteng Ma et al.
What Makes Entities Similar? A Similarity Flooding Perspective for Multi-sourced Knowledge Graph Embeddings
Zequn Sun, Jiacheng Huang, Xiaozhou Xu et al.
When and How Does Known Class Help Discover Unknown Ones? Provable Understanding Through Spectral Analysis
Yiyou Sun, Zhenmei Shi, Yingyu Liang et al.
When does Privileged information Explain Away Label Noise?
Guillermo Ortiz-Jimenez, Mark Collier, Anant Nawalgaria et al.
When do Minimax-fair Learning and Empirical Risk Minimization Coincide?
Harvineet Singh, Matthäus Kleindessner, Volkan Cevher et al.
When Personalization Harms Performance: Reconsidering the Use of Group Attributes in Prediction
Vinith Menon Suriyakumar, Marzyeh Ghassemi, Berk Ustun