Papers
Two-way Sparse Network Inference for Count Data
Sijia Li, Martı́n López-Garcı́a, Neil D. Lawrence et al.
Uncertainty Quantification for Bayesian Optimization
Rui Tuo, Wenjia Wang
Uncertainty Quantification for Low-Rank Matrix Completion with Heterogeneous and Sub-Exponential Noise
Vivek Farias, Andrew A. Li, Tianyi Peng
Unlabeled Data Help: Minimax Analysis and Adversarial Robustness
Yue Xing, Qifan Song, Guang Cheng
Using time-series privileged information for provably efficient learning of prediction models
Rickard K.A. Karlsson, Martin Willbo, Zeshan M. Hussain et al.
Vanishing Curvature in Randomly Initialized Deep ReLU Networks
Antonio Orvieto, Jonas Kohler, Dario Pavllo et al.
Variance Minimization in the Wasserstein Space for Invariant Causal Prediction
Guillaume G. Martinet, Alexander Strzalkowski, Barbara Engelhardt
Variational Autoencoders: A Harmonic Perspective
Alexander Camuto, Matthew Willetts
Variational Continual Proxy-Anchor for Deep Metric Learning
Minyoung Kim, Ricardo Guerrero, Hai X. Pham et al.
Variational Gaussian Processes: A Functional Analysis View
George Wynne, Veit Wild
Variational Marginal Particle Filters
Jinlin Lai, Justin Domke, Daniel Sheldon
VFDS: Variational Foresight Dynamic Selection in Bayesian Neural Networks for Efficient Human Activity Recognition
Randy Ardywibowo, Shahin Boluki, Zhangyang Wang et al.
Warping Layer: Representation Learning for Label Structures in Weakly Supervised Learning
Yingyi Ma, Xinhua Zhang
Weak Separation in Mixture Models and Implications for Principal Stratification
Nhat Ho, Avi Feller, Evan Greif et al.
Weighted Gaussian Process Bandits for Non-stationary Environments
Yuntian Deng, Xingyu Zhou, Baekjin Kim et al.
Wide Mean-Field Bayesian Neural Networks Ignore the Data
Beau Coker, Wessel P. Bruinsma, David R. Burt et al.
Zeroth-Order Methods for Convex-Concave Min-max Problems: Applications to Decision-Dependent Risk Minimization
Chinmay Maheshwari, Chih-Yuan Chiu, Eric Mazumdar et al.
A Bayesian nonparametric approach to count-min sketch under power-law data streams
Emanuele Dolera, Stefano Favaro, Stefano Peluchetti
Abstract Value Iteration for Hierarchical Reinforcement Learning
Kishor Jothimurugan, Osbert Bastani, Rajeev Alur
Accelerating Metropolis-Hastings with Lightweight Inference Compilation
Feynman Liang, Nimar Arora, Nazanin Tehrani et al.
A Change of Variables Method For Rectangular Matrix-Vector Products
Edmond Cunningham, Madalina Fiterau
A comparative study on sampling with replacement vs Poisson sampling in optimal subsampling
HaiYing Wang, Jiahui Zou
A constrained risk inequality for general losses
John Duchi, Feng Ruan