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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)

Low-Rank and Sparse Structure Pursuit via Alternating Minimization AISTATS 2016
NuC-MKL: A Convex Approach to Non Linear Multiple Kernel Learning AISTATS 2016
Fast Dictionary Learning with a Smoothed Wasserstein Loss AISTATS 2016
Nonparametric Budgeted Stochastic Gradient Descent AISTATS 2016
Learning Relationships between Data Obtained Independently AISTATS 2016
Fast and Scalable Structural SVM with Slack Rescaling AISTATS 2016
Probabilistic Approximate Least-Squares AISTATS 2016
Sequential Inference for Deep Gaussian Process AISTATS 2016
Non-Stationary Gaussian Process Regression with Hamiltonian Monte Carlo AISTATS 2016
A Deep Generative Deconvolutional Image Model AISTATS 2016
Distributed Multi-Task Learning AISTATS 2016
Stochastic Variational Inference for the HDP-HMM AISTATS 2016
Stochastic Neural Networks with Monotonic Activation Functions AISTATS 2016
Scalable geometric density estimation AISTATS 2016
Model-based Co-clustering for High Dimensional Sparse Data AISTATS 2016
How to Learn a Graph from Smooth Signals AISTATS 2016
Ordered Weighted L1 Regularized Regression with Strongly Correlated Covariates: Theoretical Aspects AISTATS 2016
Sketching, Embedding and Dimensionality Reduction in Information Theoretic Spaces AISTATS 2016
Exponential Stochastic Cellular Automata for Massively Parallel Inference AISTATS 2016
Globally Sparse Probabilistic PCA AISTATS 2016
Unsupervised Feature Selection by Preserving Stochastic Neighbors AISTATS 2016
A Convex Surrogate Operator for General Non-Modular Loss Functions AISTATS 2016
Fitting Spectral Decay with the k-Support Norm AISTATS 2016
Bayesian Nonparametric Kernel-Learning AISTATS 2016
Tight Variational Bounds via Random Projections and I-Projections AISTATS 2016