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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
Adaptive Multichannel Dereverberation for Automatic Speech Recognition
INTERSPEECH 2017
Sampling-Based Speech Parameter Generation Using Moment-Matching Networks
INTERSPEECH 2017
Improving Variational Methods via Pairwise Linear Response Identities
JMLR 2017
On Perturbed Proximal Gradient Algorithms
JMLR 2017
Empirical Evaluation of Resampling Procedures for Optimising SVM Hyperparameters
JMLR 2017
Memory Efficient Kernel Approximation
JMLR 2017
Auto-WEKA 2.0: Automatic model selection and hyperparameter optimization in WEKA
JMLR 2017
Certifiably Optimal Low Rank Factor Analysis
JMLR 2017
Group Sparse Optimization via lp,q Regularization
JMLR 2017
Time-Accuracy Tradeoffs in Kernel Prediction: Controlling Prediction Quality
JMLR 2017
Explaining the Success of AdaBoost and Random Forests as Interpolating Classifiers
JMLR 2017
An Optimal Algorithm for Bandit and Zero-Order Convex Optimization with Two-Point Feedback
JMLR 2017
Two New Approaches to Compressed Sensing Exhibiting Both Robust Sparse Recovery and the Grouping Effect
JMLR 2017
Learning Partial Policies to Speedup MDP Tree Search via Reduction to I.I.D. Learning
JMLR 2017
Sharp Oracle Inequalities for Square Root Regularization
JMLR 2017
Non-parametric Policy Search with Limited Information Loss
JMLR 2017
Stochastic Primal-Dual Coordinate Method for Regularized Empirical Risk Minimization
JMLR 2017
A survey of Algorithms and Analysis for Adaptive Online Learning
JMLR 2017
Optimal Rates for Multi-pass Stochastic Gradient Methods
JMLR 2017
Bayesian Network Learning via Topological Order
JMLR 2017
Harder, Better, Faster, Stronger Convergence Rates for Least-Squares Regression
JMLR 2017
Accelerating Stochastic Composition Optimization
JMLR 2017
Target Curricula via Selection of Minimum Feature Sets: a Case Study in Boolean Networks
JMLR 2017
A General Distributed Dual Coordinate Optimization Framework for Regularized Loss Minimization
JMLR 2017
Second-Order Stochastic Optimization for Machine Learning in Linear Time
JMLR 2017
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