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Methodology
← Core Methods
Machine Learning
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Core Methods
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Regression
4964 directly classified papers
Papers per year
2000: 1
2001: 4
2002: 2
2003: 3
2004: 2
2005: 7
2006: 27
2007: 38
2008: 49
2009: 58
2010: 72
2011: 62
2012: 74
2013: 122
2014: 120
2015: 146
2016: 232
2017: 276
2018: 313
2019: 414
2020: 509
2021: 564
2022: 506
2023: 492
2024: 488
2025: 262
2026: 121
Papers
Probabilistic Low-Rank Matrix Completion with Adaptive Spectral Regularization Algorithms
NIPS 2013
Robust Matrix Factorization with Unknown Noise
ICCV 2013
It is all in the noise: Efficient multi-task Gaussian process inference with structured residuals
NIPS 2013
RNADE: The real-valued neural autoregressive density-estimator
NIPS 2013
Efficient Optimization for Sparse Gaussian Process Regression
NIPS 2013
New Subsampling Algorithms for Fast Least Squares Regression
NIPS 2013
Bayesian Inference and Learning in Gaussian Process State-Space Models with Particle MCMC
NIPS 2013
Adaptivity to Local Smoothness and Dimension in Kernel Regression
NIPS 2013
Low-Rank Matrix and Tensor Completion via Adaptive Sampling
NIPS 2013
On the Relationship Between Binary Classification, Bipartite Ranking, and Binary Class Probability Estimation
NIPS 2013
From Semi-supervised to Transfer Counting of Crowds
ICCV 2013
Shape Index Descriptors Applied to Texture-Based Galaxy Analysis
ICCV 2013
Class Generative Models Based on Feature Regression for Pose Estimation of Object Categories
CVPR 2013
Guaranteed Sparse Recovery under Linear Transformation
ICML 2013
Scaling Multidimensional Gaussian Processes using Projected Additive Approximations
ICML 2013
General Functional Matrix Factorization Using Gradient Boosting
ICML 2013
Optimal Geometric Fitting under the Truncated L2-Norm
CVPR 2013
Crossing the Line: Crowd Counting by Integer Programming with Local Features
CVPR 2013
Which Space Partitioning Tree to Use for Search?
NIPS 2013
Sparse Single-Index Model
JMLR 2013
A Framework for Evaluating Approximation Methods for Gaussian Process Regression
JMLR 2013
A Risk Comparison of Ordinary Least Squares vs Ridge Regression
JMLR 2013
Nonparametric Sparsity and Regularization
JMLR 2013
Random Walk Kernels and Learning Curves for Gaussian Process Regression on Random Graphs
JMLR 2013
Generalized Spike-and-Slab Priors for Bayesian Group Feature Selection Using Expectation Propagation
JMLR 2013
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