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Probabilistic Modeling

363 directly classified papers

Papers per year

Papers

A Variational Approach to Path Estimation and Parameter Inference of Hidden Diffusion Processes JMLR 2016
Data Programming: Creating Large Training Sets, Quickly NIPS 2016
Memory-Bounded Left-Corner Unsupervised Grammar Induction on Child-Directed Input COLING 2016
Semantic Annotation Aggregation with Conditional Crowdsourcing Models and Word Embeddings COLING 2016
A Distribution-based Model to Learn Bilingual Word Embeddings COLING 2016
An Expectation Maximization Approach to Joint Modeling of Multidimensional Ratings Derived from Multiple Annotators INTERSPEECH 2016
Analysis of Speaker Recognition Systems in Realistic Scenarios of the SITW 2016 Challenge INTERSPEECH 2016
Simulation and Calibration of a Fully Bayesian Marked Multidimensional Hawkes Process with Dissimilar Decays ACML 2016
Uprooting and Rerooting Graphical Models ICML 2016
Learning Granger Causality for Hawkes Processes ICML 2016
Nonlinear Statistical Learning with Truncated Gaussian Graphical Models ICML 2016
Isotonic Hawkes Processes ICML 2016
Learning Mixtures of Plackett-Luce Models ICML 2016
Grammar induction from (lots of) words alone COLING 2016
Structural Maxent Models ICML 2015
Message Passing for Collective Graphical Models ICML 2015
Inference in a Partially Observed Queuing Model with Applications in Ecology ICML 2015
Model Selection for Topic Models via Spectral Decomposition AISTATS 2015
Stochastic Spectral Descent for Restricted Boltzmann Machines AISTATS 2015
Large-scale probabilistic predictors with and without guarantees of validity NIPS 2015
Estimating Mixture Models via Mixtures of Polynomials NIPS 2015
Efficient Second-Order Gradient Boosting for Conditional Random Fields AISTATS 2015
Automatic Discovery of Cognitive Skills to Improve the Prediction of Student Learning NIPS 2014
On Sparse Gaussian Chain Graph Models NIPS 2014
New Rules for Domain Independent Lifted MAP Inference NIPS 2014