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Methodology
← Core Methods
Machine Learning
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Optimization
1184 directly classified papers
Papers per year
2001: 2
2002: 1
2003: 1
2004: 2
2005: 3
2006: 12
2007: 12
2008: 20
2009: 10
2010: 15
2011: 15
2012: 36
2013: 76
2014: 59
2015: 48
2016: 45
2017: 58
2018: 61
2019: 72
2020: 82
2021: 95
2022: 111
2023: 101
2024: 144
2025: 100
2026: 3
Papers
A Dual Ascent Framework for Lagrangean Decomposition of Combinatorial Problems
CVPR 2017
Efficient Distributed Learning with Sparsity
ICML 2017
Robust Kernel Estimation With Outliers Handling for Image Deblurring
CVPR 2016
Gradient-Domain Image Reconstruction Framework With Intensity-Range and Base-Structure Constraints
CVPR 2016
Shortlist Selection With Residual-Aware Distance Estimator for K-Nearest Neighbor Search
CVPR 2016
Optimal Relative Pose With Unknown Correspondences
CVPR 2016
A Differential Equation for Modeling Nesterov's Accelerated Gradient Method: Theory and Insights
JMLR 2016
New Perspectives on k-Support and Cluster Norms
JMLR 2016
Robust Optical Flow Estimation of Double-Layer Images Under Transparency or Reflection
CVPR 2016
Soft-Segmentation Guided Object Motion Deblurring
CVPR 2016
Progressive Feature Matching With Alternate Descriptor Selection and Correspondence Enrichment
CVPR 2016
Optimal Estimation and Completion of Matrices with Biclustering Structures
JMLR 2016
Learning Sparse Combinatorial Representations via Two-stage Submodular Maximization
ICML 2016
Training Deep Neural Networks via Direct Loss Minimization
ICML 2016
How to Fake Multiply by a Gaussian Matrix
ICML 2016
Non-Uniform Boosted MCE Training of Deep Neural Networks for Keyword Spotting
INTERSPEECH 2016
Joint Enhancement and Coding of Speech by Incorporating Wiener Filtering in a CELP Codec
INTERSPEECH 2016
Gaussian quadrature for matrix inverse forms with applications
ICML 2016
Polynomial Networks and Factorization Machines: New Insights and Efficient Training Algorithms
ICML 2016
Primal-Dual Rates and Certificates
ICML 2016
SDCA without Duality, Regularization, and Individual Convexity
ICML 2016
Hyperparameter optimization with approximate gradient
ICML 2016
Minding the Gaps for Block Frank-Wolfe Optimization of Structured SVMs
ICML 2016
Additive Approximations in High Dimensional Nonparametric Regression via the SALSA
ICML 2016
MLlib: Machine Learning in Apache Spark
JMLR 2016
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