Papers
Particle-based Variational Inference for Continuous Systems
Andrew Frank, Padhraic Smyth, Alexander T. Ihler
Inter-domain Gaussian Processes for Sparse Inference using Inducing Features
Miguel Lázaro-Gredilla, Aníbal Figueiras-Vidal
Learning with Compressible Priors
Volkan Cevher
Heterogeneous multitask learning with joint sparsity constraints
Xiaolin Yang, Seyoung Kim, Eric P. Xing
Optimal context separation of spiking haptic signals by second-order somatosensory neurons
Romain Brasselet, Roland Johansson, Angelo Arleo
Kernel Methods for Deep Learning
Youngmin Cho, Lawrence K. Saul
Modelling Relational Data using Bayesian Clustered Tensor Factorization
Ilya Sutskever, Joshua B. Tenenbaum, Ruslan Salakhutdinov
Solving Stochastic Games
Liam M. Dermed, Charles L. Isbell
Noisy Generalized Binary Search
Robert Nowak
Sequential effects reflect parallel learning of multiple environmental regularities
Matthew Wilder, Matt Jones, Michael Mozer
Help or Hinder: Bayesian Models of Social Goal Inference
Tomer Ullman, Chris Baker, Owen Macindoe et al.
Streaming k-means approximation
Nir Ailon, Ragesh Jaiswal, Claire Monteleoni
Correlation Coefficients are Insufficient for Analyzing Spike Count Dependencies
Arno Onken, Steffen Grünewälder, Klaus Obermayer
Bayesian Nonparametric Models on Decomposable Graphs
Francois Caron, Arnaud Doucet
Clustering sequence sets for motif discovery
Jong K. Kim, Seungjin Choi
Efficient Match Kernel between Sets of Features for Visual Recognition
Liefeng Bo, Cristian Sminchisescu
Efficient Recovery of Jointly Sparse Vectors
Liang Sun, Jun Liu, Jianhui Chen et al.
The Wisdom of Crowds in the Recollection of Order Information
Mark Steyvers, Brent Miller, Pernille Hemmer et al.
Sharing Features among Dynamical Systems with Beta Processes
Emily B. Fox, Michael I. Jordan, Erik B. Sudderth et al.
Lattice Regression
Eric Garcia, Maya Gupta
Variational Gaussian-process factor analysis for modeling spatio-temporal data
Jaakko Luttinen, Alexander Ilin
Asymptotically Optimal Regularization in Smooth Parametric Models
Percy Liang, Guillaume Bouchard, Francis R. Bach et al.
Nonparametric Latent Feature Models for Link Prediction
Kurt Miller, Michael I. Jordan, Thomas L. Griffiths
Measuring Invariances in Deep Networks
Ian Goodfellow, Honglak Lee, Quoc V. Le et al.
AUC optimization and the two-sample problem
Nicolas Vayatis, Marine Depecker, Stéphan J. Clémençcon