Papers
SOLAR: Deep Structured Representations for Model-Based Reinforcement Learning
Marvin Zhang, Sharad Vikram, Laura Smith et al.
Co-Representation Network for Generalized Zero-Shot Learning
Fei Zhang, Guangming Shi
Random Function Priors for Correlation Modeling
Aonan Zhang, John Paisley
Adaptive Regret of Convex and Smooth Functions
Lijun Zhang, Tie-Yan Liu, Zhi-Hua Zhou
Bridging Theory and Algorithm for Domain Adaptation
Yuchen Zhang, Tianle Liu, Mingsheng Long et al.
Incremental Randomized Sketching for Online Kernel Learning
Xiao Zhang, Shizhong Liao
Neural Collaborative Subspace Clustering
Tong Zhang, Pan Ji, Mehrtash Harandi et al.
LatentGNN: Learning Efficient Non-local Relations for Visual Recognition
Songyang Zhang, Xuming He, Shipeng Yan
Circuit-GNN: Graph Neural Networks for Distributed Circuit Design
Guo Zhang, Hao He, Dina Katabi
Self-Attention Generative Adversarial Networks
Han Zhang, Ian Goodfellow, Dimitris Metaxas et al.
When Samples Are Strategically Selected
Hanrui Zhang, Yu Cheng, Vincent Conitzer
Warm-starting Contextual Bandits: Robustly Combining Supervised and Bandit Feedback
Chicheng Zhang, Alekh Agarwal, Hal Daumé Iii et al.
Making Convolutional Networks Shift-Invariant Again
Richard Zhang
Global Convergence of Block Coordinate Descent in Deep Learning
Jinshan Zeng, Tim Tsz-Kit Lau, Shaobo Lin et al.
Tighter Problem-Dependent Regret Bounds in Reinforcement Learning without Domain Knowledge using Value Function Bounds
Andrea Zanette, Emma Brunskill
Context-Aware Zero-Shot Learning for Object Recognition
Eloi Zablocki, Patrick Bordes, Laure Soulier et al.
Conditional Gradient Methods via Stochastic Path-Integrated Differential Estimator
Alp Yurtsever, Suvrit Sra, Volkan Cevher
A Conditional-Gradient-Based Augmented Lagrangian Framework
Alp Yurtsever, Olivier Fercoq, Volkan Cevher
Dirichlet Simplex Nest and Geometric Inference
Mikhail Yurochkin, Aritra Guha, Yuekai Sun et al.
Bayesian Nonparametric Federated Learning of Neural Networks
Mikhail Yurochkin, Mayank Agarwal, Soumya Ghosh et al.
Trimming the ℓ_1 Regularizer: Statistical Analysis, Optimization, and Applications to Deep Learning
Jihun Yun, Peng Zheng, Eunho Yang et al.
Differential Inclusions for Modeling Nonsmooth ADMM Variants: A Continuous Limit Theory
Huizhuo Yuan, Yuren Zhou, Chris Junchi Li et al.
Generative Modeling of Infinite Occluded Objects for Compositional Scene Representation
Jinyang Yuan, Bin Li, Xiangyang Xue
Online Adaptive Principal Component Analysis and Its extensions
Jianjun Yuan, Andrew Lamperski
Distributed Learning over Unreliable Networks
Chen Yu, Hanlin Tang, Cedric Renggli et al.