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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)

Learning Multiple Tasks using Manifold Regularization NIPS 2010
Group Sparse Coding with a Laplacian Scale Mixture Prior NIPS 2010
Fractionally Predictive Spiking Neurons NIPS 2010
Stability Approach to Regularization Selection (StARS) for High Dimensional Graphical Models NIPS 2010
More data means less inference: A pseudo-max approach to structured learning NIPS 2010
Lifted Inference Seen from the Other Side : The Tractable Features NIPS 2010
Predictive State Temporal Difference Learning NIPS 2010
Identifying Dendritic Processing NIPS 2010
On a Connection between Importance Sampling and the Likelihood Ratio Policy Gradient NIPS 2010
Multi-View Active Learning in the Non-Realizable Case NIPS 2010
Over-complete representations on recurrent neural networks can support persistent percepts NIPS 2010
Non-Stochastic Bandit Slate Problems NIPS 2010
Large Margin Learning of Upstream Scene Understanding Models NIPS 2010
Switched Latent Force Models for Movement Segmentation NIPS 2010
Adaptive Multi-Task Lasso: with Application to eQTL Detection NIPS 2010
Categories and Functional Units: An Infinite Hierarchical Model for Brain Activations NIPS 2010
Random Projection Trees Revisited NIPS 2010
Joint Analysis of Time-Evolving Binary Matrices and Associated Documents NIPS 2010
Discriminative Clustering by Regularized Information Maximization NIPS 2010
Dynamic Infinite Relational Model for Time-varying Relational Data Analysis NIPS 2010
Exact learning curves for Gaussian process regression on large random graphs NIPS 2010
Sparse Instrumental Variables (SPIV) for Genome-Wide Studies NIPS 2010
Natural Policy Gradient Methods with Parameter-based Exploration for Control Tasks NIPS 2010
Kernel Descriptors for Visual Recognition NIPS 2010
Computing Marginal Distributions over Continuous Markov Networks for Statistical Relational Learning NIPS 2010