Papers
Differentially Private Chi-Squared Hypothesis Testing: Goodness of Fit and Independence Testing
Marco Gaboardi, Hyun Lim, Ryan Rogers et al.
How to Fake Multiply by a Gaussian Matrix
Michael Kapralov, Vamsi Potluru, David Woodruff
A Convolutional Attention Network for Extreme Summarization of Source Code
Miltiadis Allamanis, Hao Peng, Charles Sutton
Interactive Bayesian Hierarchical Clustering
Sharad Vikram, Sanjoy Dasgupta
Complex Embeddings for Simple Link Prediction
Théo Trouillon, Johannes Welbl, Sebastian Riedel et al.
Fast DPP Sampling for Nystrom with Application to Kernel Methods
Chengtao Li, Stefanie Jegelka, Suvrit Sra
Mixture Proportion Estimation via Kernel Embeddings of Distributions
Harish Ramaswamy, Clayton Scott, Ambuj Tewari
The Arrow of Time in Multivariate Time Series
Stefan Bauer, Bernhard Schölkopf, Jonas Peters
Recurrent Orthogonal Networks and Long-Memory Tasks
Mikael Henaff, Arthur Szlam, Yann LeCun
Persistent RNNs: Stashing Recurrent Weights On-Chip
Greg Diamos, Shubho Sengupta, Bryan Catanzaro et al.
Learning Convolutional Neural Networks for Graphs
Mathias Niepert, Mohamed Ahmed, Konstantin Kutzkov
Persistence weighted Gaussian kernel for topological data analysis
Genki Kusano, Yasuaki Hiraoka, Kenji Fukumizu
Dueling Network Architectures for Deep Reinforcement Learning
Ziyu Wang, Tom Schaul, Matteo Hessel et al.
Associative Long Short-Term Memory
Ivo Danihelka, Greg Wayne, Benigno Uria et al.
BISTRO: An Efficient Relaxation-Based Method for Contextual Bandits
Alexander Rakhlin, Karthik Sridharan
Nonparametric Canonical Correlation Analysis
Tomer Michaeli, Weiran Wang, Karen Livescu
Barron and Cover’s Theory in Supervised Learning and its Application to Lasso
Masanori Kawakita, Jun’ichi Takeuchi
Nonlinear Statistical Learning with Truncated Gaussian Graphical Models
Qinliang Su, Xuejun Liao, Changyou Chen et al.
A Simple and Strongly-Local Flow-Based Method for Cut Improvement
Nate Veldt, David Gleich, Michael Mahoney
Asynchronous Methods for Deep Reinforcement Learning
Volodymyr Mnih, Adria Puigdomenech Badia, Mehdi Mirza et al.
Pareto Frontier Learning with Expensive Correlated Objectives
Amar Shah, Zoubin Ghahramani
The Sum-Product Theorem: A Foundation for Learning Tractable Models
Abram Friesen, Pedro Domingos
Graying the black box: Understanding DQNs
Tom Zahavy, Nir Ben-Zrihem, Shie Mannor
Exploiting Cyclic Symmetry in Convolutional Neural Networks
Sander Dieleman, Jeffrey De Fauw, Koray Kavukcuoglu
Differential Geometric Regularization for Supervised Learning of Classifiers
Qinxun Bai, Steven Rosenberg, Zheng Wu et al.