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← Optimization & Theory
Machine Learning
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Optimization & Theory
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Optimization
14,207 papers
Papers per year
2001: 10
2002: 9
2003: 16
2004: 6
2005: 16
2006: 58
2007: 67
2008: 72
2009: 84
2010: 106
2011: 132
2012: 164
2013: 333
2014: 295
2015: 310
2016: 380
2017: 509
2018: 669
2019: 1072
2020: 1217
2021: 1489
2022: 1470
2023: 1746
2024: 1819
2025: 1567
2026: 591
Papers
Efficient Learning with a Family of Nonconvex Regularizers by Redistributing Nonconvexity
JMLR 2018
Divide-and-Conquer for Debiased $l_1$-norm Support Vector Machine in Ultra-high Dimensions
JMLR 2018
On Faster Convergence of Cyclic Block Coordinate Descent-type Methods for Strongly Convex Minimization
JMLR 2018
Hyperband: A Novel Bandit-Based Approach to Hyperparameter Optimization
JMLR 2018
From Predictive Methods to Missing Data Imputation: An Optimization Approach
JMLR 2018
Nonasymptotic convergence of stochastic proximal point methods for constrained convex optimization
JMLR 2018
An $\ell_{\infty}$ Eigenvector Perturbation Bound and Its Application
JMLR 2018
Catalyst Acceleration for First-order Convex Optimization: from Theory to Practice
JMLR 2018
SGDLibrary: A MATLAB library for stochastic optimization algorithms
JMLR 2018
Sketched Ridge Regression: Optimization Perspective, Statistical Perspective, and Model Averaging
JMLR 2018
Katyusha: The First Direct Acceleration of Stochastic Gradient Methods
JMLR 2018
Parallelizing Stochastic Gradient Descent for Least Squares Regression: Mini-batching, Averaging, and Model Misspecification
JMLR 2018
RSG: Beating Subgradient Method without Smoothness and Strong Convexity
JMLR 2018
Scalable Bayes via Barycenter in Wasserstein Space
JMLR 2018
A Robust Learning Approach for Regression Models Based on Distributionally Robust Optimization
JMLR 2018
ELFI: Engine for Likelihood-Free Inference
JMLR 2018
Refining the Confidence Level for Optimistic Bandit Strategies
JMLR 2018
Importance Sampling for Minibatches
JMLR 2018
Generalized Rank-Breaking: Computational and Statistical Tradeoffs
JMLR 2018
Parallelizing Spectrally Regularized Kernel Algorithms
JMLR 2018
Profile-Based Bandit with Unknown Profiles
JMLR 2018
Modular Proximal Optimization for Multidimensional Total-Variation Regularization
JMLR 2018
An efficient distributed learning algorithm based on effective local functional approximations
JMLR 2018
Improved Asynchronous Parallel Optimization Analysis for Stochastic Incremental Methods
JMLR 2018
Integrating Hypertension Phenotype and Genotype with Hybrid Non-negative Matrix Factorization
MLHC 2018
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