Papers
Solving graph compression via optimal transport
Vikas Garg, Tommi Jaakkola
Adapting Neural Networks for the Estimation of Treatment Effects
Claudia Shi, David Blei, Victor Veitch
Conformal Prediction Under Covariate Shift
Ryan J Tibshirani, Rina Foygel Barber, Emmanuel Candes et al.
Memory Efficient Adaptive Optimization
Rohan Anil, Vineet Gupta, Tomer Koren et al.
Heterogeneous Graph Learning for Visual Commonsense Reasoning
Weijiang Yu, Jingwen Zhou, Weihao Yu et al.
Exploiting Local and Global Structure for Point Cloud Semantic Segmentation with Contextual Point Representations
Xu Wang, Jingming He, Lin Ma
Selecting Optimal Decisions via Distributionally Robust Nearest-Neighbor Regression
Ruidi Chen, Ioannis Paschalidis
Estimating Entropy of Distributions in Constant Space
Jayadev Acharya, Sourbh Bhadane, Piotr Indyk et al.
NeurVPS: Neural Vanishing Point Scanning via Conic Convolution
Yichao Zhou, Haozhi Qi, Jingwei Huang et al.
Private Testing of Distributions via Sample Permutations
Maryam Aliakbarpour, Ilias Diakonikolas, Daniel Kane et al.
Saccader: Improving Accuracy of Hard Attention Models for Vision
Gamaleldin Elsayed, Simon Kornblith, Quoc V Le
Decentralized sketching of low rank matrices
Rakshith Sharma Srinivasa, Kiryung Lee, Marius Junge et al.
Noise-tolerant fair classification
Alex Lamy, Ziyuan Zhong, Aditya K Menon et al.
SySCD: A System-Aware Parallel Coordinate Descent Algorithm
Nikolas Ioannou, Celestine Mendler-Dünner, Thomas Parnell
Perceiving the arrow of time in autoregressive motion
Kristof Meding, Dominik Janzing, Bernhard Schölkopf et al.
Non-Asymptotic Pure Exploration by Solving Games
Rémy Degenne, Wouter M. Koolen, Pierre Ménard
The Parameterized Complexity of Cascading Portfolio Scheduling
Eduard Eiben, Robert Ganian, Iyad Kanj et al.
Robust Bi-Tempered Logistic Loss Based on Bregman Divergences
Ehsan Amid, Manfred K. Warmuth, Rohan Anil et al.
Sampling Networks and Aggregate Simulation for Online POMDP Planning
Hao(Jackson) Cui, Roni Khardon
Curvilinear Distance Metric Learning
Shuo Chen, Lei Luo, Jian Yang et al.
Beyond temperature scaling: Obtaining well-calibrated multi-class probabilities with Dirichlet calibration
Meelis Kull, Miquel Perello Nieto, Markus Kängsepp et al.
Triad Constraints for Learning Causal Structure of Latent Variables
Ruichu Cai, Feng Xie, Clark Glymour et al.
Efficient Meta Learning via Minibatch Proximal Update
Pan Zhou, Xiaotong Yuan, Huan Xu et al.
End to end learning and optimization on graphs
Bryan Wilder, Eric Ewing, Bistra Dilkina et al.
Sequential Experimental Design for Transductive Linear Bandits
Tanner Fiez, Lalit Jain, Kevin G. Jamieson et al.