Papers
Strongly-Typed Agents are Guaranteed to Interact Safely
David Balduzzi
Strong NP-Hardness for Sparse Optimization with Concave Penalty Functions
Yichen Chen, Dongdong Ge, Mengdi Wang et al.
Sub-sampled Cubic Regularization for Non-convex Optimization
Jonas Moritz Kohler, Aurelien Lucchi
Tensor Balancing on Statistical Manifold
Mahito Sugiyama, Hiroyuki Nakahara, Koji Tsuda
Tensor Belief Propagation
Andrew Wrigley, Wee Sun Lee, Nan Ye
Tensor Decomposition via Simultaneous Power Iteration
Po-An Wang, Chi-Jen Lu
Tensor Decomposition with Smoothness
Masaaki Imaizumi, Kohei Hayashi
Tensor-Train Recurrent Neural Networks for Video Classification
Yinchong Yang, Denis Krompass, Volker Tresp
The Loss Surface of Deep and Wide Neural Networks
Quynh Nguyen, Matthias Hein
Theoretical Properties for Neural Networks with Weight Matrices of Low Displacement Rank
Liang Zhao, Siyu Liao, Yanzhi Wang et al.
The Predictron: End-To-End Learning and Planning
David Silver, Hado Hasselt, Matteo Hessel et al.
The Price of Differential Privacy for Online Learning
Naman Agarwal, Karan Singh
The Sample Complexity of Online One-Class Collaborative Filtering
Reinhard Heckel, Kannan Ramchandran
The Shattered Gradients Problem: If resnets are the answer, then what is the question?
David Balduzzi, Marcus Frean, Lennox Leary et al.
The Statistical Recurrent Unit
Junier B. Oliva, Barnabás Póczos, Jeff Schneider
Tight Bounds for Approximate Carathéodory and Beyond
Vahab Mirrokni, Renato Paes Leme, Adrian Vladu et al.
Toward Controlled Generation of Text
Zhiting Hu, Zichao Yang, Xiaodan Liang et al.
Toward Efficient and Accurate Covariance Matrix Estimation on Compressed Data
Xixian Chen, Michael R. Lyu, Irwin King
Towards K-means-friendly Spaces: Simultaneous Deep Learning and Clustering
Bo Yang, Xiao Fu, Nicholas D. Sidiropoulos et al.
Tunable Efficient Unitary Neural Networks (EUNN) and their application to RNNs
Li Jing, Yichen Shen, Tena Dubcek et al.
Uncertainty Assessment and False Discovery Rate Control in High-Dimensional Granger Causal Inference
Aditya Chaudhry, Pan Xu, Quanquan Gu
Uncorrelation and Evenness: a New Diversity-Promoting Regularizer
Pengtao Xie, Aarti Singh, Eric P. Xing
Uncovering Causality from Multivariate Hawkes Integrated Cumulants
Massil Achab, Emmanuel Bacry, Stéphane Gaı̈ffas et al.
Understanding Black-box Predictions via Influence Functions
Pang Wei Koh, Percy Liang
Understanding Synthetic Gradients and Decoupled Neural Interfaces
Wojciech Marian Czarnecki, Grzegorz Świrszcz, Max Jaderberg et al.