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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)

Gaussian Process Preference Elicitation NIPS 2010
A Theory of Multiclass Boosting NIPS 2010
Hashing Hyperplane Queries to Near Points with Applications to Large-Scale Active Learning NIPS 2010
Bootstrapping Apprenticeship Learning NIPS 2010
Co-regularization Based Semi-supervised Domain Adaptation NIPS 2010
Structured sparsity-inducing norms through submodular functions NIPS 2010
Slice sampling covariance hyperparameters of latent Gaussian models NIPS 2010
Efficient Optimization for Discriminative Latent Class Models NIPS 2010
Universal Kernels on Non-Standard Input Spaces NIPS 2010
Worst-Case Linear Discriminant Analysis NIPS 2010
Learning Multiple Tasks with a Sparse Matrix-Normal Penalty NIPS 2010
Network Flow Algorithms for Structured Sparsity NIPS 2010
Active Learning by Querying Informative and Representative Examples NIPS 2010
Optimal Bayesian Recommendation Sets and Myopically Optimal Choice Query Sets NIPS 2010
Semi-Supervised Learning with Adversarially Missing Label Information NIPS 2010
Gated Softmax Classification NIPS 2010
Estimation of Rényi Entropy and Mutual Information Based on Generalized Nearest-Neighbor Graphs NIPS 2010
Causal discovery in multiple models from different experiments NIPS 2010
Learning Bounds for Importance Weighting NIPS 2010
A Reduction from Apprenticeship Learning to Classification NIPS 2010
Extensions of Generalized Binary Search to Group Identification and Exponential Costs NIPS 2010
Feature Set Embedding for Incomplete Data NIPS 2010
Improving Human Judgments by Decontaminating Sequential Dependencies NIPS 2010
Scrambled Objects for Least-Squares Regression NIPS 2010
Subgraph Detection Using Eigenvector L1 Norms NIPS 2010