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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)

Spectral Chinese Restaurant Processes: Nonparametric Clustering Based on Similarities AISTATS 2011
Kernel Belief Propagation AISTATS 2011
Machine Learning Markets AISTATS 2011
Empirical Risk Minimization of Graphical Model Parameters Given Approximate Inference, Decoding, and Model Structure AISTATS 2011
Estimating Probabilities in Recommendation Systems AISTATS 2011
Active Boosted Learning (ActBoost) AISTATS 2011
Online Variational Inference for the Hierarchical Dirichlet Process AISTATS 2011
Information Theoretical Clustering via Semidefinite Programming AISTATS 2011
Lightweight Implementations of Probabilistic Programming Languages Via Transformational Compilation AISTATS 2011
Relational Learning with One Network: An Asymptotic Analysis AISTATS 2011
Hierarchical Probabilistic Models for Group Anomaly Detection AISTATS 2011
Multicore Gibbs Sampling in Dense, Unstructured Graphs AISTATS 2011
Cross-Domain Object Matching with Model Selection AISTATS 2011
The Sample Complexity of Self-Verifying Bayesian Active Learning AISTATS 2011
Bridging the Language Gap: Topic Adaptation for Documents with Different Technicality AISTATS 2011
Efficient variable selection in support vector machines via the alternating direction method of multipliers AISTATS 2011
A Finite Newton Algorithm for Non-degenerate Piecewise Linear Systems AISTATS 2011
Generalization Bound for Infinitely Divisible Empirical Process AISTATS 2011
Multi-Label Output Codes using Canonical Correlation Analysis AISTATS 2011
Dependent Hierarchical Beta Process for Image Interpolation and Denoising AISTATS 2011
Semi-supervised Learning by Higher Order Regularization AISTATS 2011
Error Analysis of Laplacian Eigenmaps for Semi-supervised Learning AISTATS 2011
Two-Layer Multiple Kernel Learning AISTATS 2011
Regret Bounds for the Adaptive Control of Linear Quadratic Systems COLT 2011
Blackwell Approachability and No-Regret Learning are Equivalent COLT 2011