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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)

Adaptive dropout for training deep neural networks NIPS 2013
On the Representational Efficiency of Restricted Boltzmann Machines NIPS 2013
Robust Spatial Filtering with Beta Divergence NIPS 2013
DeViSE: A Deep Visual-Semantic Embedding Model NIPS 2013
Symbolic Opportunistic Policy Iteration for Factored-Action MDPs NIPS 2013
Least Informative Dimensions NIPS 2013
A memory frontier for complex synapses NIPS 2013
Data-driven Distributionally Robust Polynomial Optimization NIPS 2013
Learning Stochastic Inverses NIPS 2013
Stochastic Ratio Matching of RBMs for Sparse High-Dimensional Inputs NIPS 2013
Distributed $k$-means and $k$-median Clustering on General Topologies NIPS 2013
Non-strongly-convex smooth stochastic approximation with convergence rate O(1/n) NIPS 2013
Predicting Parameters in Deep Learning NIPS 2013
Estimation Bias in Multi-Armed Bandit Algorithms for Search Advertising NIPS 2013
Learning Efficient Random Maximum A-Posteriori Predictors with Non-Decomposable Loss Functions NIPS 2013
q-OCSVM: A q-Quantile Estimator for High-Dimensional Distributions NIPS 2013
Fantope Projection and Selection: A near-optimal convex relaxation of sparse PCA NIPS 2013
Fast Template Evaluation with Vector Quantization NIPS 2013
Sparse Additive Text Models with Low Rank Background NIPS 2013
Correlated random features for fast semi-supervised learning NIPS 2013
Variational Planning for Graph-based MDPs NIPS 2013
Adaptive Anonymity via $b$-Matching NIPS 2013
Statistical Active Learning Algorithms NIPS 2013
The Power of Asymmetry in Binary Hashing NIPS 2013
Bayesian Mixture Modelling and Inference based Thompson Sampling in Monte-Carlo Tree Search NIPS 2013