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Machine Learning

121,146 papers (10 classified directly here)

Subtopics

Learning Types (52,936) Core Methods (48,729) Optimization & Theory (36,874) Application Areas (31,658) Bayesian & Probabilistic (3,963) Learning Paradigms (2,054)

Papers per year

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Papers (including subtopics)

SpeedBoost: Anytime Prediction with Uniform Near-Optimality AISTATS 2012
Bayesian regularization of non-homogeneous dynamic Bayesian networks by globally coupling interaction parameters AISTATS 2012
Locality Preserving Feature Learning AISTATS 2012
Evaluation of marginal likelihoods via the density of states AISTATS 2012
Information Theoretic Model Validation for Spectral Clustering AISTATS 2012
Exchangeability Characterizes Optimality of Sequential Normalized Maximum Likelihood and Bayesian Prediction with Jeffreys Prior AISTATS 2012
Kernel Topic Models AISTATS 2012
Maximum Margin Temporal Clustering AISTATS 2012
Stochastic Bandit Based on Empirical Moments AISTATS 2012
Variable Selection for Gaussian Graphical Models AISTATS 2012
Subset Infinite Relational Models AISTATS 2012
A Variance Minimization Criterion to Active Learning on Graphs AISTATS 2012
High-dimensional Sparse Inverse Covariance Estimation using Greedy Methods AISTATS 2012
Random Feature Maps for Dot Product Kernels AISTATS 2012
On Bayesian Upper Confidence Bounds for Bandit Problems AISTATS 2012
Online Clustering of Processes AISTATS 2012
A Stick-Breaking Likelihood for Categorical Data Analysis with Latent Gaussian Models AISTATS 2012
Bayesian Classifier Combination AISTATS 2012
Regression for sets of polynomial equations AISTATS 2012
Multiple Texture Boltzmann Machines AISTATS 2012
Marginal Regression For Multitask Learning AISTATS 2012
Bayesian Comparison of Machine Learning Algorithms on Single and Multiple Datasets AISTATS 2012
Efficient Hypergraph Clustering AISTATS 2012
Data dependent kernels in nearly-linear time AISTATS 2012
Efficient Sampling from Combinatorial Space via Bridging AISTATS 2012