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Core Methods

48,729 papers (8 classified directly here)

Subtopics

Representation Learning (20,822) Classification (15,805) Regression (5,004) Embedding Learning (3,753) Clustering (3,638) Metric Learning (2,854) Graph Neural Networks (1,141) Graphical Models (985) Feature Learning (860) Dimensionality Reduction (707) Kernel Methods (642) Interpretability (499) Feature Selection (479) Matrix Factorization (383) Ranking (283) Ensemble Methods (267) Anomaly Detection (267) Support Vector Machine (254) Sequence Modeling (237) Structured Prediction (205) Sequence Labeling (166) Topic Modeling (123) Sparse Coding (107) Matrix Completion (103) Retrieval (99) Neural Networks (79) Inference (21) Model Selection (19) Decision Tree (16) Prediction (15) Density Estimation (9) Estimation (8) Feature Extraction (7) Information Extraction (7)

Papers per year

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Papers (including subtopics)

Similarity Component Analysis NIPS 2013
Matrix Completion From any Given Set of Observations NIPS 2013
A Deep Architecture for Matching Short Texts NIPS 2013
Sensor Selection in High-Dimensional Gaussian Trees with Nuisances NIPS 2013
The Total Variation on Hypergraphs - Learning on Hypergraphs Revisited NIPS 2013
Lasso Screening Rules via Dual Polytope Projection NIPS 2013
Multiscale Dictionary Learning for Estimating Conditional Distributions NIPS 2013
Dirty Statistical Models NIPS 2013
Exact and Stable Recovery of Pairwise Interaction Tensors NIPS 2013
A* Lasso for Learning a Sparse Bayesian Network Structure for Continuous Variables NIPS 2013
High-Dimensional Gaussian Process Bandits NIPS 2013
Generalizing Analytic Shrinkage for Arbitrary Covariance Structures NIPS 2013
Online Robust PCA via Stochastic Optimization NIPS 2013
Compete to Compute NIPS 2013
Heterogeneous-Neighborhood-based Multi-Task Local Learning Algorithms NIPS 2013
More data speeds up training time in learning halfspaces over sparse vectors NIPS 2013
Polar Operators for Structured Sparse Estimation NIPS 2013
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
Sketching Structured Matrices for Faster Nonlinear Regression NIPS 2013
Variance Reduction for Stochastic Gradient Optimization 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
Multilinear Dynamical Systems for Tensor Time Series NIPS 2013