Papers
Realistic Evaluation of Deep Semi-Supervised Learning Algorithms
Avital Oliver, Augustus Odena, Colin A Raffel et al.
Online Learning of Quantum States
Scott Aaronson, Xinyi Chen, Elad Hazan et al.
Ex ante coordination and collusion in zero-sum multi-player extensive-form games
Gabriele Farina, Andrea Celli, Nicola Gatti et al.
Scalar Posterior Sampling with Applications
Georgios Theocharous, Zheng Wen, Yasin Abbasi Yadkori et al.
Structural Causal Bandits: Where to Intervene?
Sanghack Lee, Elias Bareinboim
Training deep learning based denoisers without ground truth data
Shakarim Soltanayev, Se Young Chun
Self-Erasing Network for Integral Object Attention
Qibin Hou, PengTao Jiang, Yunchao Wei et al.
Wavelet regression and additive models for irregularly spaced data
Asad Haris, Ali Shojaie, Noah Simon
Understanding the Role of Adaptivity in Machine Teaching: The Case of Version Space Learners
Yuxin Chen, Adish Singla, Oisin Mac Aodha et al.
Can We Gain More from Orthogonality Regularizations in Training Deep Networks?
Nitin Bansal, Xiaohan Chen, Zhangyang Wang
Lifted Weighted Mini-Bucket
Nicholas Gallo, Alex Ihler
A Unified View of Piecewise Linear Neural Network Verification
Rudy R Bunel, Ilker Turkaslan, Philip Torr et al.
Fairness Behind a Veil of Ignorance: A Welfare Analysis for Automated Decision Making
Hoda Heidari, Claudio Ferrari, Krishna Gummadi et al.
Loss Surfaces, Mode Connectivity, and Fast Ensembling of DNNs
Timur Garipov, Pavel Izmailov, Dmitrii Podoprikhin et al.
Transfer Learning with Neural AutoML
Catherine Wong, Neil Houlsby, Yifeng Lu et al.
Binary Classification from Positive-Confidence Data
Takashi Ishida, Gang Niu, Masashi Sugiyama
Algebraic tests of general Gaussian latent tree models
Dennis Leung, Mathias Drton
Near-Optimal Time and Sample Complexities for Solving Markov Decision Processes with a Generative Model
Aaron Sidford, Mengdi Wang, Xian Wu et al.
Zeroth-Order Stochastic Variance Reduction for Nonconvex Optimization
Sijia Liu, Bhavya Kailkhura, Pin-Yu Chen et al.
Differentiable MPC for End-to-end Planning and Control
Brandon Amos, Ivan Jimenez, Jacob Sacks et al.
Reinforcement Learning with Multiple Experts: A Bayesian Model Combination Approach
Michael Gimelfarb, Scott Sanner, Chi-Guhn Lee
Experimental Design for Cost-Aware Learning of Causal Graphs
Erik Lindgren, Murat Kocaoglu, Alexandros G Dimakis et al.
Recurrent Relational Networks
Rasmus Palm, Ulrich Paquet, Ole Winther
Learning To Learn Around A Common Mean
Giulia Denevi, Carlo Ciliberto, Dimitris Stamos et al.
Attacks Meet Interpretability: Attribute-steered Detection of Adversarial Samples
Guanhong Tao, Shiqing Ma, Yingqi Liu et al.