Papers
Training Very Deep Networks
Rupesh K Srivastava, Klaus Greff, Jürgen Schmidhuber
Probabilistic Curve Learning: Coulomb Repulsion and the Electrostatic Gaussian Process
Ye Wang, David B Dunson
Combinatorial Cascading Bandits
Branislav Kveton, Zheng Wen, Azin Ashkan et al.
Optimal Testing for Properties of Distributions
Jayadev Acharya, Constantinos Daskalakis, Gautam Kamath
Randomized Block Krylov Methods for Stronger and Faster Approximate Singular Value Decomposition
Cameron Musco, Christopher Musco
Spectral Norm Regularization of Orthonormal Representations for Graph Transduction
Rakesh Shivanna, Bibaswan K Chatterjee, Raman Sankaran et al.
b-bit Marginal Regression
Martin Slawski, Ping Li
Robust Regression via Hard Thresholding
Kush Bhatia, Prateek Jain, Purushottam Kar
Adaptive Online Learning
Dylan J Foster, Alexander Rakhlin, Karthik Sridharan
Fast Classification Rates for High-dimensional Gaussian Generative Models
Tianyang Li, Adarsh Prasad, Pradeep K Ravikumar
Learning spatiotemporal trajectories from manifold-valued longitudinal data
Jean-Baptiste SCHIRATTI, Stéphanie ALLASSONNIERE, Olivier Colliot et al.
Expressing an Image Stream with a Sequence of Natural Sentences
Cesc C Park, Gunhee Kim
Closed-form Estimators for High-dimensional Generalized Linear Models
Eunho Yang, Aurelie C. Lozano, Pradeep K Ravikumar
A class of network models recoverable by spectral clustering
Yali Wan, Marina Meila
Sampling from Probabilistic Submodular Models
Alkis Gotovos, Hamed Hassani, Andreas Krause
Learning with Incremental Iterative Regularization
Lorenzo Rosasco, Silvia Villa
Efficient Non-greedy Optimization of Decision Trees
Mohammad Norouzi, Maxwell Collins, Matthew A Johnson et al.
Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks
Shaoqing Ren, Kaiming He, Ross Girshick et al.
Learning Continuous Control Policies by Stochastic Value Gradients
Nicolas Heess, Gregory Wayne, David Silver et al.
High Dimensional EM Algorithm: Statistical Optimization and Asymptotic Normality
Zhaoran Wang, Quanquan Gu, Yang Ning et al.
Training Restricted Boltzmann Machine via the Thouless-Anderson-Palmer free energy
Marylou Gabrie, Eric W Tramel, Florent Krzakala
Local Expectation Gradients for Black Box Variational Inference
Michalis Titsias RC AUEB, Miguel Lázaro-Gredilla
Time-Sensitive Recommendation From Recurrent User Activities
Nan Du, Yichen Wang, Niao He et al.
Efficient and Robust Automated Machine Learning
Matthias Feurer, Aaron Klein, Katharina Eggensperger et al.