Papers
Continuous Deep Q-Learning with Model-based Acceleration
Shixiang Gu, Timothy Lillicrap, Ilya Sutskever et al.
Tensor Decomposition via Joint Matrix Schur Decomposition
Nicolo Colombo, Nikos Vlassis
Bayesian Poisson Tucker Decomposition for Learning the Structure of International Relations
Aaron Schein, Mingyuan Zhou, David Blei et al.
The Label Complexity of Mixed-Initiative Classifier Training
Jina Suh, Xiaojin Zhu, Saleema Amershi
Control of Memory, Active Perception, and Action in Minecraft
Junhyuk Oh, Valliappa Chockalingam, Satinder et al.
Conditional Dependence via Shannon Capacity: Axioms, Estimators and Applications
Weihao Gao, Sreeram Kannan, Sewoong Oh et al.
ADIOS: Architectures Deep In Output Space
Moustapha Cisse, Maruan Al-Shedivat, Samy Bengio
Model-Free Imitation Learning with Policy Optimization
Jonathan Ho, Jayesh Gupta, Stefano Ermon
Algorithms for Optimizing the Ratio of Submodular Functions
Wenruo Bai, Rishabh Iyer, Kai Wei et al.
Efficient Algorithms for Large-scale Generalized Eigenvector Computation and Canonical Correlation Analysis
Rong Ge, Chi Jin, Sham et al.
Clustering High Dimensional Categorical Data via Topographical Features
Chao Chen, Novi Quadrianto
Training Neural Networks Without Gradients: A Scalable ADMM Approach
Gavin Taylor, Ryan Burmeister, Zheng Xu et al.
Robust Random Cut Forest Based Anomaly Detection on Streams
Sudipto Guha, Nina Mishra, Gourav Roy et al.
Discriminative Embeddings of Latent Variable Models for Structured Data
Hanjun Dai, Bo Dai, Le Song
Meta–Gradient Boosted Decision Tree Model for Weight and Target Learning
Yury Ustinovskiy, Valentina Fedorova, Gleb Gusev et al.
The Segmented iHMM: A Simple, Efficient Hierarchical Infinite HMM
Ardavan Saeedi, Matthew Hoffman, Matthew Johnson et al.
Robust Monte Carlo Sampling using Riemannian Nosé-Poincaré Hamiltonian Dynamics
Anirban Roychowdhury, Brian Kulis, Srinivasan Parthasarathy
Gromov-Wasserstein Averaging of Kernel and Distance Matrices
Gabriel Peyré, Marco Cuturi, Justin Solomon
Computationally Efficient Nyström Approximation using Fast Transforms
Si Si, Cho-Jui Hsieh, Inderjit Dhillon
Efficient Learning with a Family of Nonconvex Regularizers by Redistributing Nonconvexity
Quanming Yao, James Kwok
A Theory of Generative ConvNet
Jianwen Xie, Yang Lu, Song-Chun Zhu et al.
Faster Eigenvector Computation via Shift-and-Invert Preconditioning
Dan Garber, Elad Hazan, Chi Jin et al.
Interacting Particle Markov Chain Monte Carlo
Tom Rainforth, Christian Naesseth, Fredrik Lindsten et al.
A Kernel Test of Goodness of Fit
Kacper Chwialkowski, Heiko Strathmann, Arthur Gretton
A Superlinearly-Convergent Proximal Newton-type Method for the Optimization of Finite Sums
Anton Rodomanov, Dmitry Kropotov