Papers
Learning Structured Decision Problems with Unawareness
Craig Innes, Alex Lascarides
Overcoming Mean-Field Approximations in Recurrent Gaussian Process Models
Alessandro Davide Ialongo, Mark Van Der Wilk, James Hensman et al.
HexaGAN: Generative Adversarial Nets for Real World Classification
Uiwon Hwang, Dahuin Jung, Sungroh Yoon
Composing Entropic Policies using Divergence Correction
Jonathan Hunt, Andre Barreto, Timothy Lillicrap et al.
Causal Discovery and Forecasting in Nonstationary Environments with State-Space Models
Biwei Huang, Kun Zhang, Mingming Gong et al.
Addressing the Loss-Metric Mismatch with Adaptive Loss Alignment
Chen Huang, Shuangfei Zhai, Walter Talbott et al.
Stable and Fair Classification
Lingxiao Huang, Nisheeth Vishnoi
Hierarchical Importance Weighted Autoencoders
Chin-Wei Huang, Kris Sankaran, Eeshan Dhekane et al.
Unsupervised Deep Learning by Neighbourhood Discovery
Jiabo Huang, Qi Dong, Shaogang Gong et al.
Faster Stochastic Alternating Direction Method of Multipliers for Nonconvex Optimization
Feihu Huang, Songcan Chen, Heng Huang
Bayesian Deconditional Kernel Mean Embeddings
Kelvin Hsu, Fabio Ramos
Classification from Positive, Unlabeled and Biased Negative Data
Yu-Guan Hsieh, Gang Niu, Masashi Sugiyama
Finding Mixed Nash Equilibria of Generative Adversarial Networks
Ya-Ping Hsieh, Chen Liu, Volkan Cevher
Stay With Me: Lifetime Maximization Through Heteroscedastic Linear Bandits With Reneging
Ping-Chun Hsieh, Xi Liu, Anirban Bhattacharya et al.
Parameter-Efficient Transfer Learning for NLP
Neil Houlsby, Andrei Giurgiu, Stanislaw Jastrzebski et al.
Nonconvex Variance Reduced Optimization with Arbitrary Sampling
Samuel Horváth, Peter Richtarik
Emerging Convolutions for Generative Normalizing Flows
Emiel Hoogeboom, Rianne Van Den Berg, Max Welling
Better generalization with less data using robust gradient descent
Matthew Holland, Kazushi Ikeda
Connectivity-Optimized Representation Learning via Persistent Homology
Christoph Hofer, Roland Kwitt, Marc Niethammer et al.
Collective Model Fusion for Multiple Black-Box Experts
Minh Hoang, Nghia Hoang, Bryan Kian Hsiang Low et al.
Population Based Augmentation: Efficient Learning of Augmentation Policy Schedules
Daniel Ho, Eric Liang, Xi Chen et al.
Flow++: Improving Flow-Based Generative Models with Variational Dequantization and Architecture Design
Jonathan Ho, Xi Chen, Aravind Srinivas et al.
Using Pre-Training Can Improve Model Robustness and Uncertainty
Dan Hendrycks, Kimin Lee, Mantas Mazeika
Graph Resistance and Learning from Pairwise Comparisons
Julien Hendrickx, Alexander Olshevsky, Venkatesh Saligrama