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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)

A Spike and Slab Restricted Boltzmann Machine AISTATS 2011
Bagged Structure Learning of Bayesian Network AISTATS 2011
Active Clustering: Robust and Efficient Hierarchical Clustering using Adaptively Selected Similarities AISTATS 2011
A novel greedy algorithm for Nyström approximation AISTATS 2011
Revisiting MAP Estimation, Message Passing and Perfect Graphs AISTATS 2011
A Dynamic Relational Infinite Feature Model for Longitudinal Social Networks AISTATS 2011
Learning from positive and unlabeled examples by enforcing statistical significance AISTATS 2011
Deep Sparse Rectifier Neural Networks AISTATS 2011
Multiscale Community Blockmodel for Network Exploration AISTATS 2011
Evolving Cluster Mixed-Membership Blockmodel for Time-Evolving Networks AISTATS 2011
Fast $b$-matching via Sufficient Selection Belief Propagation AISTATS 2011
Improved Loss Bounds For Multiple Kernel Learning AISTATS 2011
On Learning Discrete Graphical Models using Group-Sparse Regularization AISTATS 2011
Robust Bayesian Matrix Factorisation AISTATS 2011
Confidence Weighted Mean Reversion Strategy for On-Line Portfolio Selection AISTATS 2011
Bayesian Hierarchical Cross-Clustering AISTATS 2011
Group Orthogonal Matching Pursuit for Logistic Regression AISTATS 2011
Learning Class-relevant Features and Class-irrelevant Features via a Hybrid third-order RBM AISTATS 2011
Hidden-Unit Conditional Random Fields AISTATS 2011
CAKE: Convex Adaptive Kernel Density Estimation AISTATS 2011
Online Learning of Structured Predictors with Multiple Kernels AISTATS 2011
TopicFlow Model: Unsupervised Learning of Topic-specific Influences of Hyperlinked Documents AISTATS 2011
Dimensionality Reduction for Spectral Clustering AISTATS 2011
Maximum Volume Clustering AISTATS 2011
A Reduction of Imitation Learning and Structured Prediction to No-Regret Online Learning AISTATS 2011