Papers
Weight Uncertainty in Neural Network
Charles Blundell, Julien Cornebise, Koray Kavukcuoglu et al.
Long Short-Term Memory Over Recursive Structures
Xiaodan Zhu, Parinaz Sobihani, Hongyu Guo
An Empirical Study of Stochastic Variational Inference Algorithms for the Beta Bernoulli Process
Amar Shah, David Knowles, Zoubin Ghahramani
Geometric Conditions for Subspace-Sparse Recovery
Chong You, Rene Vidal
Entropy evaluation based on confidence intervals of frequency estimates : Application to the learning of decision trees
Mathieu Serrurier, Henri Prade
Non-Stationary Approximate Modified Policy Iteration
Boris Lesner, Bruno Scherrer
K-hyperplane Hinge-Minimax Classifier
Margarita Osadchy, Tamir Hazan, Daniel Keren
Convex Learning of Multiple Tasks and their Structure
Carlo Ciliberto, Youssef Mroueh, Tomaso Poggio et al.
Controversy in mechanistic modelling with Gaussian processes
Benn Macdonald, Catherine Higham, Dirk Husmeier
Variational Inference with Normalizing Flows
Danilo Rezende, Shakir Mohamed
On the Rate of Convergence and Error Bounds for LSTD(λ)
Manel Tagorti, Bruno Scherrer
Consistent estimation of dynamic and multi-layer block models
Qiuyi Han, Kevin Xu, Edoardo Airoldi
\ell_1,p-Norm Regularization: Error Bounds and Convergence Rate Analysis of First-Order Methods
Zirui Zhou, Qi Zhang, Anthony Man-Cho So
Guaranteed Tensor Decomposition: A Moment Approach
Gongguo Tang, Parikshit Shah
Distributed Gaussian Processes
Marc Deisenroth, Jun Wei Ng
Multiview Triplet Embedding: Learning Attributes in Multiple Maps
Ehsan Amid, Antti Ukkonen
DRAW: A Recurrent Neural Network For Image Generation
Karol Gregor, Ivo Danihelka, Alex Graves et al.
Towards a Learning Theory of Cause-Effect Inference
David Lopez-Paz, Krikamol Muandet, Bernhard Schölkopf et al.
Risk and Regret of Hierarchical Bayesian Learners
Jonathan Huggins, Josh Tenenbaum
MRA-based Statistical Learning from Incomplete Rankings
Eric Sibony, Stéphan Clemençon, Jérémie Jakubowicz
A Deterministic Analysis of Noisy Sparse Subspace Clustering for Dimensionality-reduced Data
Yining Wang, Yu-Xiang Wang, Aarti Singh
CUR Algorithm for Partially Observed Matrices
Miao Xu, Rong Jin, Zhi-Hua Zhou
Strongly Adaptive Online Learning
Amit Daniely, Alon Gonen, Shai Shalev-Shwartz
Threshold Influence Model for Allocating Advertising Budgets
Atsushi Miyauchi, Yuni Iwamasa, Takuro Fukunaga et al.
Convex Formulation for Learning from Positive and Unlabeled Data
Marthinus Du Plessis, Gang Niu, Masashi Sugiyama