Papers
Unsupervised Learning of View-invariant Action Representations
Junnan Li, Yongkang Wong, Qi Zhao et al.
Inferring Networks From Random Walk-Based Node Similarities
Jeremy Hoskins, Cameron Musco, Christopher Musco et al.
Efficient Formal Safety Analysis of Neural Networks
Shiqi Wang, Kexin Pei, Justin Whitehouse et al.
The Price of Privacy for Low-rank Factorization
Jalaj Upadhyay
A Likelihood-Free Inference Framework for Population Genetic Data using Exchangeable Neural Networks
Jeffrey Chan, Valerio Perrone, Jeffrey Spence et al.
On preserving non-discrimination when combining expert advice
Avrim Blum, Suriya Gunasekar, Thodoris Lykouris et al.
Algorithms and Theory for Multiple-Source Adaptation
Judy Hoffman, Mehryar Mohri, Ningshan Zhang
Recurrent World Models Facilitate Policy Evolution
David Ha, Jürgen Schmidhuber
Lifelong Inverse Reinforcement Learning
Jorge Mendez, Shashank Shivkumar, Eric Eaton
A Smoothed Analysis of the Greedy Algorithm for the Linear Contextual Bandit Problem
Sampath Kannan, Jamie H Morgenstern, Aaron Roth et al.
Bayesian Control of Large MDPs with Unknown Dynamics in Data-Poor Environments
Mahdi Imani, Seyede Fatemeh Ghoreishi, Ulisses M. Braga-Neto
Wasserstein Variational Inference
Luca Ambrogioni, Umut Güçlü, Yağmur Güçlütürk et al.
Pipe-SGD: A Decentralized Pipelined SGD Framework for Distributed Deep Net Training
Youjie Li, Mingchao Yu, Songze Li et al.
Scalable Robust Matrix Factorization with Nonconvex Loss
Quanming Yao, James Kwok
Leveraged volume sampling for linear regression
Michal Derezinski, Manfred K. Warmuth, Daniel J. Hsu
Automating Bayesian optimization with Bayesian optimization
Gustavo Malkomes, Roman Garnett
Disconnected Manifold Learning for Generative Adversarial Networks
Mahyar Khayatkhoei, Maneesh K. Singh, Ahmed Elgammal
Learning Deep Disentangled Embeddings With the F-Statistic Loss
Karl Ridgeway, Michael Mozer
Deep Dynamical Modeling and Control of Unsteady Fluid Flows
Jeremy Morton, Antony Jameson, Mykel J Kochenderfer et al.
Multitask Boosting for Survival Analysis with Competing Risks
Alexis Bellot, Mihaela van der Schaar
Plug-in Estimation in High-Dimensional Linear Inverse Problems: A Rigorous Analysis
Alyson K. Fletcher, Parthe Pandit, Sundeep Rangan et al.
Understanding Regularized Spectral Clustering via Graph Conductance
Yilin Zhang, Karl Rohe
Supervised autoencoders: Improving generalization performance with unsupervised regularizers
Lei Le, Andrew Patterson, Martha White
DeepPINK: reproducible feature selection in deep neural networks
Yang Lu, Yingying Fan, Jinchi Lv et al.
Compact Representation of Uncertainty in Clustering
Craig Greenberg, Nicholas Monath, Ari Kobren et al.