Co-occurring keywords · papers mentioning both
Papers
Meta-Gaussian Information Bottleneck
NeurIPS 2012
Optimal Neural Tuning Curves for Arbitrary Stimulus Distributions: Discrimax, Infomax and Minimum L_p Loss
NeurIPS 2012
Computationally Efficient Sufficient Dimension Reduction via Squared-Loss Mutual Information
ACML 2011
How biased are maximum entropy models?
NeurIPS 2011
Information Theoretical Clustering via Semidefinite Programming
AISTATS 2011
On the Estimation of α-Divergences
AISTATS 2011
PAC-Bayesian Analysis of Contextual Bandits
NeurIPS 2011
Query-Aware MCMC
NeurIPS 2011
Active Instance Sampling via Matrix Partition
NeurIPS 2010
Estimation of Rényi Entropy and Mutual Information Based on Generalized Nearest-Neighbor Graphs
NeurIPS 2010
Implicit encoding of prior probabilities in optimal neural populations
NeurIPS 2010
Infinite Relational Modeling of Functional Connectivity in Resting State fMRI
NeurIPS 2010
Information Theoretic Measures for Clusterings Comparison: Variants, Properties, Normalization and Correction for Chance
JMLR 2010
Multitask Learning without Label Correspondences
NeurIPS 2010
Sufficient Dimension Reduction via Squared-loss Mutual Information Estimation
AISTATS 2010
Unsupervised Kernel Dimension Reduction
NeurIPS 2010
Adaptive Design Optimization in Experiments with People
NeurIPS 2009
A Rate Distortion Approach for Semi-Supervised Conditional Random Fields
NeurIPS 2009
Entropy Inference and the James-Stein Estimator, with Application to Nonlinear Gene Association Networks
JMLR 2009
Exploring Functional Connectivities of the Human Brain using Multivariate Information Analysis
NeurIPS 2009
Nonextensive Information Theoretic Kernels on Measures
JMLR 2009
Estimation of Information Theoretic Measures for Continuous Random Variables
NeurIPS 2008
ICA based on a Smooth Estimation of the Differential Entropy
NeurIPS 2008
Near-Optimal Sensor Placements in Gaussian Processes: Theory, Efficient Algorithms and Empirical Studies
JMLR 2008
Better than least squares: comparison of objective functions for estimating linear-nonlinear models
NeurIPS 2007