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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)

Sparse Estimation Using General Likelihoods and Non-Factorial Priors NIPS 2009
Modeling the spacing effect in sequential category learning NIPS 2009
An Infinite Factor Model Hierarchy Via a Noisy-Or Mechanism NIPS 2009
Large Scale Nonparametric Bayesian Inference: Data Parallelisation in the Indian Buffet Process NIPS 2009
Matrix Completion from Power-Law Distributed Samples NIPS 2009
Filtering Abstract Senses From Image Search Results NIPS 2009
Heavy-Tailed Symmetric Stochastic Neighbor Embedding NIPS 2009
Which graphical models are difficult to learn? NIPS 2009
Information-theoretic lower bounds on the oracle complexity of convex optimization NIPS 2009
Linear-time Algorithms for Pairwise Statistical Problems NIPS 2009
From PAC-Bayes Bounds to KL Regularization NIPS 2009
On Stochastic and Worst-case Models for Investing NIPS 2009
Structured output regression for detection with partial truncation NIPS 2009
On Invariance in Hierarchical Models NIPS 2009
Submanifold density estimation NIPS 2009
Nonlinear Learning using Local Coordinate Coding NIPS 2009
No evidence for active sparsification in the visual cortex NIPS 2009
Distribution Matching for Transduction NIPS 2009
Canonical Time Warping for Alignment of Human Behavior NIPS 2009
A Parameter-free Hedging Algorithm NIPS 2009
Learning Bregman Distance Functions and Its Application for Semi-Supervised Clustering NIPS 2009
Ranking Measures and Loss Functions in Learning to Rank NIPS 2009
Constructing Topological Maps using Markov Random Fields and Loop-Closure Detection NIPS 2009
Replicated Softmax: an Undirected Topic Model NIPS 2009
Fast, smooth and adaptive regression in metric spaces NIPS 2009