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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)

Strong Coresets for Hard and Soft Bregman Clustering with Applications to Exponential Family Mixtures AISTATS 2016
A Robust-Equitable Copula Dependence Measure for Feature Selection AISTATS 2016
Random Forest for the Contextual Bandit Problem AISTATS 2016
Learning Sparse Additive Models with Interactions in High Dimensions AISTATS 2016
Bipartite Correlation Clustering: Maximizing Agreements AISTATS 2016
Maximum Likelihood for Variance Estimation in High-Dimensional Linear Models AISTATS 2016
Precision Matrix Estimation in High Dimensional Gaussian Graphical Models with Faster Rates AISTATS 2016
Fast Convergence of Online Pairwise Learning Algorithms AISTATS 2016
Tensor vs. Matrix Methods: Robust Tensor Decomposition under Block Sparse Perturbations AISTATS 2016
Online Learning to Rank with Feedback at the Top AISTATS 2016
Survey Propagation beyond Constraint Satisfaction Problems AISTATS 2016
CRAFT: ClusteR-specific Assorted Feature selecTion AISTATS 2016
Bayesian Markov Blanket Estimation AISTATS 2016
Unsupervised Ensemble Learning with Dependent Classifiers AISTATS 2016
Deep Kernel Learning AISTATS 2016
Nearly Optimal Classification for Semimetrics AISTATS 2016
A Lasso-based Sparse Knowledge Gradient Policy for Sequential Optimal Learning AISTATS 2016
Simple and Scalable Constrained Clustering: a Generalized Spectral Method AISTATS 2016
Geometry Aware Mappings for High Dimensional Sparse Factors AISTATS 2016
Rivalry of Two Families of Algorithms for Memory-Restricted Streaming PCA AISTATS 2016
Quantization based Fast Inner Product Search AISTATS 2016
Learning Structured Low-Rank Representation via Matrix Factorization AISTATS 2016
Large-Scale Optimization Algorithms for Sparse Conditional Gaussian Graphical Models AISTATS 2016
Graph Connectivity in Noisy Sparse Subspace Clustering AISTATS 2016
Enumerating Equivalence Classes of Bayesian Networks using EC Graphs AISTATS 2016