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← Core Methods
Machine Learning
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Core Methods
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Classification
15,289 papers
Papers per year
2000: 2
2001: 14
2002: 21
2003: 28
2004: 28
2005: 26
2006: 94
2007: 93
2008: 90
2009: 93
2010: 134
2011: 112
2012: 160
2013: 290
2014: 239
2015: 258
2016: 456
2017: 682
2018: 1145
2019: 1500
2020: 1638
2021: 1667
2022: 1636
2023: 1685
2024: 1600
2025: 1313
2026: 285
Papers
bandicoot: a Python Toolbox for Mobile Phone Metadata
JMLR 2016
On the Consistency of the Likelihood Maximization Vertex Nomination Scheme: Bridging the Gap Between Maximum Likelihood Estimation and Graph Matching
JMLR 2016
Jointly Informative Feature Selection Made Tractable by Gaussian Modeling
JMLR 2016
Classification of Imbalanced Data with a Geometric Digraph Family
JMLR 2016
One-class classification of point patterns of extremes
JMLR 2016
Optimal Learning Rates for Localized SVMs
JMLR 2016
Bipartite Ranking: a Risk-Theoretic Perspective
JMLR 2016
Wavelet decompositions of Random Forests - smoothness analysis, sparse approximation and applications
JMLR 2016
Modelling Interactions in High-dimensional Data with Backtracking
JMLR 2016
Neyman-Pearson Classification under High-Dimensional Settings
JMLR 2016
Multi-scale Classification using Localized Spatial Depth
JMLR 2016
RLScore: Regularized Least-Squares Learners
JMLR 2016
Composite Multiclass Losses
JMLR 2016
GenSVM: A Generalized Multiclass Support Vector Machine
JMLR 2016
An Error Bound for L1-norm Support Vector Machine Coefficients in Ultra-high Dimension
JMLR 2016
Blending Learning and Inference in Conditional Random Fields
JMLR 2016
Using Kernel Methods and Model Selection for Prediction of Preterm Birth
MLHC 2016
Multi-task Learning with Weak Class Labels: Leveraging iEEG to Detect Cortical Lesions in Cryptogenic Epilepsy
MLHC 2016
Preterm Birth Prediction: Stable Selection of Interpretable Rules from High Dimensional Data
MLHC 2016
Mitochondria-based Renal Cell Carcinoma Subtyping: Learning from Deep vs. Flat Feature Representations
MLHC 2016
Clinical Tagging with Joint Probabilistic Models
MLHC 2016
Diagnostic Prediction Using Discomfort Drawings with IBTM
MLHC 2016
Directly Modeling Missing Data in Sequences with RNNs: Improved Classification of Clinical Time Series
MLHC 2016
Deep Convolutional Neural Networks for Microscopy-Based Point of Care Diagnostics
MLHC 2016
Doctor AI: Predicting Clinical Events via Recurrent Neural Networks
MLHC 2016
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