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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)

Fast and Accurate k-means For Large Datasets NIPS 2011
Message-Passing for Approximate MAP Inference with Latent Variables NIPS 2011
A More Powerful Two-Sample Test in High Dimensions using Random Projection NIPS 2011
Kernel Bayes' Rule NIPS 2011
ShareBoost: Efficient multiclass learning with feature sharing NIPS 2011
Heavy-tailed Distances for Gradient Based Image Descriptors NIPS 2011
An Application of Tree-Structured Expectation Propagation for Channel Decoding NIPS 2011
PAC-Bayesian Analysis of Contextual Bandits NIPS 2011
Fast and Balanced: Efficient Label Tree Learning for Large Scale Object Recognition NIPS 2011
Divide-and-Conquer Matrix Factorization NIPS 2011
Non-conjugate Variational Message Passing for Multinomial and Binary Regression NIPS 2011
Im2Text: Describing Images Using 1 Million Captioned Photographs NIPS 2011
Modelling Genetic Variations using Fragmentation-Coagulation Processes NIPS 2011
Uniqueness of Belief Propagation on Signed Graphs NIPS 2011
Improving Topic Coherence with Regularized Topic Models NIPS 2011
Beating SGD: Learning SVMs in Sublinear Time NIPS 2011
Inferring spike-timing-dependent plasticity from spike train data NIPS 2011
Bayesian Spike-Triggered Covariance Analysis NIPS 2011
Adaptive Hedge NIPS 2011
Matrix Completion for Multi-label Image Classification NIPS 2011
Continuous-Time Regression Models for Longitudinal Networks NIPS 2011
Stochastic convex optimization with bandit feedback NIPS 2011
Online Learning: Stochastic, Constrained, and Smoothed Adversaries NIPS 2011
Similarity-based Learning via Data Driven Embeddings NIPS 2011
Maximum Margin Multi-Label Structured Prediction NIPS 2011