Co-occurring keywords · papers mentioning both
Papers
Bayesian Inference for Change Points in Dynamical Systems with Reusable States - a Chinese Restaurant Process Approach
AISTATS 2012
Coding efficiency and detectability of rate fluctuations with non-Poisson neuronal firing
NeurIPS 2012
Efficient Spike-Coding with Multiplicative Adaptation in a Spike Response Model
NeurIPS 2012
Interpreting prediction markets: a stochastic approach
NeurIPS 2012
Learning with Partially Absorbing Random Walks
NeurIPS 2012
Quilting Stochastic Kronecker Product Graphs to Generate Multiplicative Attribute Graphs
AISTATS 2012
Slice sampling normalized kernel-weighted completely random measure mixture models
NeurIPS 2012
Inference in continuous-time change-point models
NeurIPS 2011
Nonstandard Interpretations of Probabilistic Programs for Efficient Inference
NeurIPS 2011
On the Relation between Realizable and Nonrealizable Cases of the Sequence Prediction Problem
JMLR 2011
Statistical Optimization of Non-Negative Matrix Factorization
AISTATS 2011
The Indian Buffet Process: An Introduction and Review
JMLR 2011
Approximate parameter inference in a stochastic reaction-diffusion model
AISTATS 2010
Mean Field Variational Approximation for Continuous-Time Bayesian Networks
JMLR 2010
On Finding Predictors for Arbitrary Families of Processes
JMLR 2010
Risk Bounds for Levy Processes in the PAC-Learning Framework
AISTATS 2010
Stochastic Modeling of the Expected Time to Search for an Intermittent Signal Source Under a Limited Sensing Range
RSS 2010
Construction of Nonparametric Bayesian Models from Parametric Bayes Equations
NeurIPS 2009
Algorithms for Infinitely Many-Armed Bandits
NeurIPS 2008
Metastable Walking on Stochastically Rough Terrain
RSS 2008
Rademacher Complexity Bounds for Non-I.I.D. Processes
NeurIPS 2008
The Mondrian Process
NeurIPS 2008
Value Function Based Reinforcement Learning in Changing Markovian Environments
JMLR 2008
Discovering Weakly-Interacting Factors in a Complex Stochastic Process
NeurIPS 2007
Inferring Elapsed Time from Stochastic Neural Processes
NeurIPS 2007