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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)

Robust Regression via Hard Thresholding NIPS 2015
b-bit Marginal Regression NIPS 2015
Spectral Norm Regularization of Orthonormal Representations for Graph Transduction NIPS 2015
Randomized Block Krylov Methods for Stronger and Faster Approximate Singular Value Decomposition NIPS 2015
Probabilistic Curve Learning: Coulomb Repulsion and the Electrostatic Gaussian Process NIPS 2015
Training Very Deep Networks NIPS 2015
Fast and Memory Optimal Low-Rank Matrix Approximation NIPS 2015
Inferring Algorithmic Patterns with Stack-Augmented Recurrent Nets NIPS 2015
Practical and Optimal LSH for Angular Distance NIPS 2015
A Framework for Individualizing Predictions of Disease Trajectories by Exploiting Multi-Resolution Structure NIPS 2015
Pointer Networks NIPS 2015
Fast and Accurate Inference of Plackett–Luce Models NIPS 2015
Learning Bayesian Networks with Thousands of Variables NIPS 2015
Sparse PCA via Bipartite Matchings NIPS 2015
LASSO with Non-linear Measurements is Equivalent to One With Linear Measurements NIPS 2015
Natural Neural Networks NIPS 2015
Regressive Virtual Metric Learning NIPS 2015
Halting in Random Walk Kernels NIPS 2015
Precision-Recall-Gain Curves: PR Analysis Done Right NIPS 2015
Planar Ultrametrics for Image Segmentation NIPS 2015
Sparse Local Embeddings for Extreme Multi-label Classification NIPS 2015
Tree-Guided MCMC Inference for Normalized Random Measure Mixture Models NIPS 2015
The Self-Normalized Estimator for Counterfactual Learning NIPS 2015
Multi-class SVMs: From Tighter Data-Dependent Generalization Bounds to Novel Algorithms NIPS 2015
Scalable Inference for Gaussian Process Models with Black-Box Likelihoods NIPS 2015