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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)

Confidence Sets for Network Structure NIPS 2011
Structural equations and divisive normalization for energy-dependent component analysis NIPS 2011
Gaussian Process Training with Input Noise NIPS 2011
Unifying Framework for Fast Learning Rate of Non-Sparse Multiple Kernel Learning NIPS 2011
High-dimensional regression with noisy and missing data: Provable guarantees with non-convexity NIPS 2011
Greedy Model Averaging NIPS 2011
Hierarchical Multitask Structured Output Learning for Large-scale Sequence Segmentation NIPS 2011
Variational Gaussian Process Dynamical Systems NIPS 2011
Statistical Performance of Convex Tensor Decomposition NIPS 2011
A Machine Learning Approach to Predict Chemical Reactions NIPS 2011
Sparse Features for PCA-Like Linear Regression NIPS 2011
Spike and Slab Variational Inference for Multi-Task and Multiple Kernel Learning NIPS 2011
Generalizing from Several Related Classification Tasks to a New Unlabeled Sample NIPS 2011
Global Solution of Fully-Observed Variational Bayesian Matrix Factorization is Column-Wise Independent NIPS 2011
Algorithms and hardness results for parallel large margin learning NIPS 2011
Semi-supervised Regression via Parallel Field Regularization NIPS 2011
Thinning Measurement Models and Questionnaire Design NIPS 2011
Active dendrites: adaptation to spike-based communication NIPS 2011
Shaping Level Sets with Submodular Functions NIPS 2011
EigenNet: A Bayesian hybrid of generative and conditional models for sparse learning NIPS 2011
Iterative Learning for Reliable Crowdsourcing Systems NIPS 2011
Minimax Localization of Structural Information in Large Noisy Matrices NIPS 2011
Crowdclustering NIPS 2011
Comparative Analysis of Viterbi Training and Maximum Likelihood Estimation for HMMs NIPS 2011
A Model for Temporal Dependencies in Event Streams NIPS 2011