Papers
Hadamard Wirtinger Flow for Sparse Phase Retrieval
Fan Wu, Patrick Rebeschini
Have We Learned to Explain?: How Interpretability Methods Can Learn to Encode Predictions in their Interpretations.
Neil Jethani, Mukund Sudarshan, Yindalon Aphinyanaphongs et al.
Hidden Cost of Randomized Smoothing
Jeet Mohapatra, Ching-Yun Ko, Lily Weng et al.
Hierarchical Clustering in General Metric Spaces using Approximate Nearest Neighbors
Benjamin Moseley, Sergei Vassilvtiskii, Yuyan Wang
Hierarchical Clustering via Sketches and Hierarchical Correlation Clustering
Danny Vainstein, Vaggos Chatziafratis, Gui Citovsky et al.
Hierarchical Inducing Point Gaussian Process for Inter-domian Observations
Luhuan Wu, Andrew Miller, Lauren Anderson et al.
High-Dimensional Feature Selection for Sample Efficient Treatment Effect Estimation
Kristjan Greenewald, Karthikeyan Shanmugam, Dmitriy Katz
High-Dimensional Multi-Task Averaging and Application to Kernel Mean Embedding
Hannah Marienwald, Jean-Baptiste Fermanian, Gilles Blanchard
Hindsight Expectation Maximization for Goal-conditioned Reinforcement Learning
Yunhao Tang, Alp Kucukelbir
Hogwild! over Distributed Local Data Sets with Linearly Increasing Mini-Batch Sizes
Nhuong Nguyen, Toan Nguyen, PHUONG HA NGUYEN et al.
Homeomorphic-Invariance of EM: Non-Asymptotic Convergence in KL Divergence for Exponential Families via Mirror Descent
Frederik Kunstner, Raunak Kumar, Mark Schmidt
Hyperbolic graph embedding with enhanced semi-implicit variational inference.
Ali Lotfi Rezaabad, Rahi Kalantari, Sriram Vishwanath et al.
Hyperparameter Transfer Learning with Adaptive Complexity
Samuel Horváth, Aaron Klein, Peter Richtarik et al.
Identification of Matrix Joint Block Diagonalization
Yunfeng Cai, Ping Li
Implicit Regularization via Neural Feature Alignment
Aristide Baratin, Thomas George, César Laurent et al.
Improved Complexity Bounds in Wasserstein Barycenter Problem
Darina Dvinskikh, Daniil Tiapkin
Improved Exploration in Factored Average-Reward MDPs
Mohammad Sadegh Talebi, Anders Jonsson, Odalric Maillard
Improving Adversarial Robustness via Unlabeled Out-of-Domain Data
Zhun Deng, Linjun Zhang, Amirata Ghorbani et al.
Improving Classifier Confidence using Lossy Label-Invariant Transformations
Sooyong Jang, Insup Lee, James Weimer
Improving KernelSHAP: Practical Shapley Value Estimation Using Linear Regression
Ian Covert, Su-In Lee
Improving predictions of Bayesian neural nets via local linearization
Alexander Immer, Maciej Korzepa, Matthias Bauer
Independent Innovation Analysis for Nonlinear Vector Autoregressive Process
Hiroshi Morioka, Hermanni Hälvä, Aapo Hyvarinen
Inductive Mutual Information Estimation: A Convex Maximum-Entropy Copula Approach
Yves-Laurent Kom Samo
Inference in Stochastic Epidemic Models via Multinomial Approximations
Nick Whiteley, Lorenzo Rimella
Influence Decompositions For Neural Network Attribution
Kyle Reing, Greg Ver Steeg, Aram Galstyan