Papers
Variance reduction for Random Coordinate Descent-Langevin Monte Carlo
ZHIYAN DING, Qin Li
Variance Reduction via Accelerated Dual Averaging for Finite-Sum Optimization
Chaobing Song, Yong Jiang, Yi Ma
Variational Amodal Object Completion
Huan Ling, David Acuna, Karsten Kreis et al.
Variational Bayesian Unlearning
Quoc Phong Nguyen, Bryan Kian Hsiang Low, Patrick Jaillet
Variational Inference for Graph Convolutional Networks in the Absence of Graph Data and Adversarial Settings
Pantelis Elinas, Edwin V. Bonilla, Louis Tiao
Variational Interaction Information Maximization for Cross-domain Disentanglement
HyeongJoo Hwang, Geon-Hyeong Kim, Seunghoon Hong et al.
Variational Policy Gradient Method for Reinforcement Learning with General Utilities
Junyu Zhang, Alec Koppel, Amrit Singh Bedi et al.
Video Frame Interpolation without Temporal Priors
Youjian Zhang, Chaoyue Wang, Dacheng Tao
Video Object Segmentation with Adaptive Feature Bank and Uncertain-Region Refinement
Yongqing Liang, Xin Li, Navid Jafari et al.
VIME: Extending the Success of Self- and Semi-supervised Learning to Tabular Domain
Jinsung Yoon, Yao Zhang, James Jordon et al.
Walking in the Shadow: A New Perspective on Descent Directions for Constrained Minimization
Hassan Mortagy, Swati Gupta, Sebastian Pokutta
Walsh-Hadamard Variational Inference for Bayesian Deep Learning
Simone Rossi, Sebastien Marmin, Maurizio Filippone
Wasserstein Distances for Stereo Disparity Estimation
Divyansh Garg, Yan Wang, Bharath Hariharan et al.
Watch out! Motion is Blurring the Vision of Your Deep Neural Networks
Qing Guo, Felix Juefei-Xu, Xiaofei Xie et al.
wav2vec 2.0: A Framework for Self-Supervised Learning of Speech Representations
Alexei Baevski, Yuhao Zhou, Abdelrahman Mohamed et al.
Wavelet Flow: Fast Training of High Resolution Normalizing Flows
Jason J. Yu, Konstantinos G. Derpanis, Marcus A Brubaker
Weak Form Generalized Hamiltonian Learning
Kevin Course, Trefor Evans, Prasanth Nair
Weakly Supervised Deep Functional Maps for Shape Matching
Abhishek Sharma, Maks Ovsjanikov
Weakly-Supervised Reinforcement Learning for Controllable Behavior
Lisa Lee, Ben Eysenbach, Ruslan Salakhutdinov et al.
Weighted QMIX: Expanding Monotonic Value Function Factorisation for Deep Multi-Agent Reinforcement Learning
Tabish Rashid, Gregory Farquhar, Bei Peng et al.
Weisfeiler and Leman go sparse: Towards scalable higher-order graph embeddings
Christopher Morris, Gaurav Rattan, Petra Mutzel
Weston-Watkins Hinge Loss and Ordered Partitions
Yutong Wang, Clayton Scott
What Did You Think Would Happen? Explaining Agent Behaviour through Intended Outcomes
Herman Yau, Chris Russell, Simon Hadfield
What Do Neural Networks Learn When Trained With Random Labels?
Hartmut Maennel, Ibrahim M Alabdulmohsin, Ilya O Tolstikhin et al.