Papers
Neuronal Adaptation for Sampling-Based Probabilistic Inference in Perceptual Bistability
David P. Reichert, Peggy Series, Amos J. Storkey
Spike and Slab Variational Inference for Multi-Task and Multiple Kernel Learning
Michalis K. Titsias, Miguel Lázaro-Gredilla
Sparse Features for PCA-Like Linear Regression
Christos Boutsidis, Petros Drineas, Malik Magdon-Ismail
A Machine Learning Approach to Predict Chemical Reactions
Matthew A. Kayala, Pierre F. Baldi
Statistical Performance of Convex Tensor Decomposition
Ryota Tomioka, Taiji Suzuki, Kohei Hayashi et al.
Statistical Tests for Optimization Efficiency
Levi Boyles, Anoop Korattikara, Deva Ramanan et al.
Variational Gaussian Process Dynamical Systems
Andreas Damianou, Michalis K. Titsias, Neil D. Lawrence
Generalized Beta Mixtures of Gaussians
Artin Armagan, Merlise Clyde, David B. Dunson
Hierarchical Multitask Structured Output Learning for Large-scale Sequence Segmentation
Nico Goernitz, Christian K. Widmer, Georg Zeller et al.
Greedy Model Averaging
Dong Dai, Tong Zhang
High-dimensional regression with noisy and missing data: Provable guarantees with non-convexity
Po-ling Loh, Martin J. Wainwright
Speedy Q-Learning
Mohammad Ghavamzadeh, Hilbert J. Kappen, Mohammad G. Azar et al.
On the Universality of Online Mirror Descent
Nati Srebro, Karthik Sridharan, Ambuj Tewari
Gaussian Process Training with Input Noise
Andrew Mchutchon, Carl E. Rasmussen
Structural equations and divisive normalization for energy-dependent component analysis
Jun-ichiro Hirayama, Aapo Hyvärinen
Confidence Sets for Network Structure
David S. Choi, Patrick J. Wolfe, Edoardo M. Airoldi
Efficient inference in matrix-variate Gaussian models with \iid observation noise
Oliver Stegle, Christoph Lippert, Joris M. Mooij et al.
Learning person-object interactions for action recognition in still images
Vincent Delaitre, Josef Sivic, Ivan Laptev
On Learning Discrete Graphical Models using Greedy Methods
Ali Jalali, Christopher C. Johnson, Pradeep K. Ravikumar
Clustered Multi-Task Learning Via Alternating Structure Optimization
Jiayu Zhou, Jianhui Chen, Jieping Ye
Select and Sample - A Model of Efficient Neural Inference and Learning
Jacquelyn A. Shelton, Abdul S. Sheikh, Pietro Berkes et al.
Robust Lasso with missing and grossly corrupted observations
Nasser M. Nasrabadi, Trac D. Tran, Nam Nguyen
On U-processes and clustering performance
Stéphan J. Clémençcon