Papers
Hallucinations in Charles Bonnet Syndrome Induced by Homeostasis: a Deep Boltzmann Machine Model
Peggy Series, David P. Reichert, Amos J. Storkey
Gaussian sampling by local perturbations
George Papandreou, Alan L. Yuille
Global seismic monitoring as probabilistic inference
Nimar Arora, Stuart Russell, Paul Kidwell et al.
On the Convexity of Latent Social Network Inference
Seth Myers, Jure Leskovec
Individualized ROI Optimization via Maximization of Group-wise Consistency of Structural and Functional Profiles
Kaiming Li, Lei Guo, Carlos Faraco et al.
Avoiding False Positive in Multi-Instance Learning
Yanjun Han, Qing Tao, Jue Wang
Latent Variable Models for Predicting File Dependencies in Large-Scale Software Development
Diane Hu, Laurens Maaten, Youngmin Cho et al.
Variational Inference over Combinatorial Spaces
Alexandre Bouchard-côté, Michael I. Jordan
Direct Loss Minimization for Structured Prediction
Tamir Hazan, Joseph Keshet, David A. McAllester
Learning from Candidate Labeling Sets
Jie Luo, Francesco Orabona
Two-Layer Generalization Analysis for Ranking Using Rademacher Average
Wei Chen, Tie-yan Liu, Zhi-ming Ma
Probabilistic latent variable models for distinguishing between cause and effect
Oliver Stegle, Dominik Janzing, Kun Zhang et al.
Accounting for network effects in neuronal responses using L1 regularized point process models
Ryan Kelly, Matthew Smith, Robert Kass et al.
On the Theory of Learnining with Privileged Information
Dmitry Pechyony, Vladimir Vapnik
Nonparametric Bayesian Policy Priors for Reinforcement Learning
Finale Doshi-velez, David Wingate, Nicholas Roy et al.
A Novel Kernel for Learning a Neuron Model from Spike Train Data
Nicholas Fisher, Arunava Banerjee
Basis Construction from Power Series Expansions of Value Functions
Sridhar Mahadevan, Bo Liu
Parametric Bandits: The Generalized Linear Case
Sarah Filippi, Olivier Cappe, Aurélien Garivier et al.
Learning from Logged Implicit Exploration Data
Alex Strehl, John Langford, Lihong Li et al.
Efficient Relational Learning with Hidden Variable Detection
Ni Lao, Jun Zhu, Liu Liu et al.
Reverse Multi-Label Learning
James Petterson, Tibério S. Caetano
Block Variable Selection in Multivariate Regression and High-dimensional Causal Inference
Vikas Sindhwani, Aurelie C. Lozano
Sparse Coding for Learning Interpretable Spatio-Temporal Primitives
Taehwan Kim, Gregory Shakhnarovich, Raquel Urtasun
Phone Recognition with the Mean-Covariance Restricted Boltzmann Machine
George Dahl, Marc'aurelio Ranzato, Abdel-rahman Mohamed et al.
An Approximate Inference Approach to Temporal Optimization in Optimal Control
Konrad Rawlik, Marc Toussaint, Sethu Vijayakumar