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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 with Invariance via Linear Functionals on Reproducing Kernel Hilbert Space NIPS 2013
Real-Time Inference for a Gamma Process Model of Neural Spiking NIPS 2013
Direct 0-1 Loss Minimization and Margin Maximization with Boosting NIPS 2013
Marginals-to-Models Reducibility NIPS 2013
Sketching Structured Matrices for Faster Nonlinear Regression NIPS 2013
Variance Reduction for Stochastic Gradient Optimization NIPS 2013
On Decomposing the Proximal Map NIPS 2013
Documents as multiple overlapping windows into grids of counts NIPS 2013
Robust Sparse Principal Component Regression under the High Dimensional Elliptical Model NIPS 2013
Optimizing Instructional Policies NIPS 2013
Adaptive Market Making via Online Learning NIPS 2013
Learning Prices for Repeated Auctions with Strategic Buyers NIPS 2013
Multilinear Dynamical Systems for Tensor Time Series NIPS 2013
Computing the Stationary Distribution Locally NIPS 2013
Latent Maximum Margin Clustering NIPS 2013
Hierarchical Modular Optimization of Convolutional Networks Achieves Representations Similar to Macaque IT and Human Ventral Stream NIPS 2013
Online PCA for Contaminated Data NIPS 2013
Distributed Representations of Words and Phrases and their Compositionality NIPS 2013
Learning Multiple Models via Regularized Weighting NIPS 2013
Discriminative Transfer Learning with Tree-based Priors NIPS 2013
Machine Teaching for Bayesian Learners in the Exponential Family NIPS 2013
Online Learning with Switching Costs and Other Adaptive Adversaries NIPS 2013
From Bandits to Experts: A Tale of Domination and Independence NIPS 2013
Which Space Partitioning Tree to Use for Search? NIPS 2013
Small-Variance Asymptotics for Hidden Markov Models NIPS 2013