Papers
SVCCA: Singular Vector Canonical Correlation Analysis for Deep Learning Dynamics and Interpretability
Maithra Raghu, Justin Gilmer, Jason Yosinski et al.
Unsupervised Image-to-Image Translation Networks
Ming-Yu Liu, Thomas Breuel, Jan Kautz
DropoutNet: Addressing Cold Start in Recommender Systems
Maksims Volkovs, Guangwei Yu, Tomi Poutanen
Subspace Clustering via Tangent Cones
Amin Jalali, Rebecca Willett
Maxing and Ranking with Few Assumptions
Moein Falahatgar, Yi Hao, Alon Orlitsky et al.
Compression-aware Training of Deep Networks
Jose M Alvarez, Mathieu Salzmann
Clustering with Noisy Queries
Arya Mazumdar, Barna Saha
Structured Bayesian Pruning via Log-Normal Multiplicative Noise
Kirill Neklyudov, Dmitry Molchanov, Arsenii Ashukha et al.
Online Convex Optimization with Stochastic Constraints
Hao Yu, Michael Neely, Xiaohan Wei
Adaptive Classification for Prediction Under a Budget
Feng Nan, Venkatesh Saligrama
Resurrecting the sigmoid in deep learning through dynamical isometry: theory and practice
Jeffrey Pennington, Samuel Schoenholz, Surya Ganguli
Learning Combinatorial Optimization Algorithms over Graphs
Elias Khalil, Hanjun Dai, Yuyu Zhang et al.
Thinking Fast and Slow with Deep Learning and Tree Search
Thomas Anthony, Zheng Tian, David Barber
Approximation Bounds for Hierarchical Clustering: Average Linkage, Bisecting K-means, and Local Search
Benjamin Moseley, Joshua Wang
PointNet++: Deep Hierarchical Feature Learning on Point Sets in a Metric Space
Charles Ruizhongtai Qi, Li Yi, Hao Su et al.
Subset Selection under Noise
Chao Qian, Jing-Cheng Shi, Yang Yu et al.
Deep Reinforcement Learning from Human Preferences
Paul F Christiano, Jan Leike, Tom Brown et al.
Attend and Predict: Understanding Gene Regulation by Selective Attention on Chromatin
Ritambhara Singh, Jack Lanchantin, Arshdeep Sekhon et al.
Clustering Stable Instances of Euclidean k-means.
Aravindan Vijayaraghavan, Abhratanu Dutta, Alex Wang
Houdini: Fooling Deep Structured Visual and Speech Recognition Models with Adversarial Examples
Moustapha M Cisse, Yossi Adi, Natalia Neverova et al.
Semi-supervised Learning with GANs: Manifold Invariance with Improved Inference
Abhishek Kumar, Prasanna Sattigeri, Tom Fletcher
Welfare Guarantees from Data
Darrell Hoy, Denis Nekipelov, Vasilis Syrgkanis
Expectation Propagation with Stochastic Kinetic Model in Complex Interaction Systems
Le Fang, Fan Yang, Wen Dong et al.
Hunt For The Unique, Stable, Sparse And Fast Feature Learning On Graphs
Saurabh Verma, Zhi-Li Zhang
Neural Expectation Maximization
Klaus Greff, Sjoerd van Steenkiste, Jürgen Schmidhuber