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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)

Regret based Robust Solutions for Uncertain Markov Decision Processes NIPS 2013
Understanding variable importances in forests of randomized trees NIPS 2013
Linear decision rule as aspiration for simple decision heuristics NIPS 2013
Probabilistic Movement Primitives NIPS 2013
Speedup Matrix Completion with Side Information: Application to Multi-Label Learning NIPS 2013
Message Passing Inference with Chemical Reaction Networks NIPS 2013
Binary to Bushy: Bayesian Hierarchical Clustering with the Beta Coalescent NIPS 2013
A Stability-based Validation Procedure for Differentially Private Machine Learning NIPS 2013
Unsupervised Spectral Learning of Finite State Transducers NIPS 2013
One-shot learning and big data with n=2 NIPS 2013
Mapping paradigm ontologies to and from the brain NIPS 2013
Density estimation from unweighted k-nearest neighbor graphs: a roadmap NIPS 2013
Actor-Critic Algorithms for Risk-Sensitive MDPs NIPS 2013
Probabilistic Principal Geodesic Analysis NIPS 2013
k-Prototype Learning for 3D Rigid Structures NIPS 2013
Learning Adaptive Value of Information for Structured Prediction NIPS 2013
Spike train entropy-rate estimation using hierarchical Dirichlet process priors NIPS 2013
Regularized M-estimators with nonconvexity: Statistical and algorithmic theory for local optima NIPS 2013
Robust Data-Driven Dynamic Programming NIPS 2013
Provable Subspace Clustering: When LRR meets SSC NIPS 2013
Optimization, Learning, and Games with Predictable Sequences NIPS 2013
Firing rate predictions in optimal balanced networks NIPS 2013
Multi-Task Bayesian Optimization NIPS 2013
Using multiple samples to learn mixture models NIPS 2013
First-order Decomposition Trees NIPS 2013