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Stochastic gradient descent, weighted sampling, and the randomized Kaczmarz algorithm

Mathematical programming, 2016-01, Vol.155 (1-2), p.549-573

2016

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Pegasos: primal estimated sub-gradient solver for SVM

Mathematical programming, 2011-03, Vol.127 (1), p.3-30

2011

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Sketching meets random projection in the dual: A provable recovery algorithm for big and high-dimensional data

Electronic journal of statistics, 2017-01, Vol.11 (2)

2017

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Pegasos: primal estimated sub-gradient solver for SVM

Mathematical programming, 2011-03, Vol.127 (1), p.3-30

2011

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Trading Accuracy for Sparsity in Optimization Problems with Sparsity Constraints

SIAM journal on optimization, 2010-01, Vol.20 (6), p.2807-2832

2010

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Lower bounds for non-convex stochastic optimization

Mathematical programming, 2023-05, Vol.199 (1-2), p.165-214

2023

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Rank, Trace-Norm and Max-Norm

Learning Theory, 2005, p.545-560

2005

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Data-Dependent Convergence for Consensus Stochastic Optimization

IEEE transactions on automatic control, 2017-09, Vol.62 (9), p.4483-4498

2017

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A theory of learning with similarity functions

Machine learning, 2008-08, Vol.72 (1-2), p.89-112

2008

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Optimistic Rates: A Unifying Theory for Interpolation Learning and Regularization in Linear Regression

ACM / IMS journal of data science, 2024-06, Vol.1 (2), p.1-51

2024

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Sparse Data Reconstruction, Missing Value and Multiple Imputation through Matrix Factorization

Sociological methodology, 2023-02, Vol.53 (1), p.72-114

2023

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Uncovering shared structures in multiclass classification

ACM International Conference Proceeding Series; Vol. 227: Proceedings of the 24th international conference on Machine learning; 20-24 June 2007, 2007, p.17-24

2007

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Distribution of Short Paired Duplications in Mammalian Genomes

Proceedings of the National Academy of Sciences - PNAS, 2004-07, Vol.101 (28), p.10349-10354

2004

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Fast maximum margin matrix factorization for collaborative prediction

ACM International Conference Proceeding Series; Vol. 119: Proceedings of the 22nd international conference on Machine learning; 07-11 Aug. 2005, 2005, p.713-719

2005

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An accelerated communication-efficient primal-dual optimization framework for structured machine learning

Optimization methods & software, 2021-01, Vol.36 (1), p.20-44

2021

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Distributed stochastic optimization and learning

2014 52nd Annual Allerton Conference on Communication, Control, and Computing (Allerton), 2014, p.850-857

2014

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Maximum likelihood bounded tree-width Markov networks

Artificial intelligence, 2003, Vol.143 (1), p.123-138

Srebro, Nathan

2003

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From Fair Decision Making To Social Equality

Proceedings of the Conference on Fairness, Accountability, and Transparency, 2019, p.359-368

2019

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Learning Bounds for Support Vector Machines with Learned Kernels

Learning Theory, 2006, p.169-183

2006

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Implicit Regularization in Matrix Factorization

2018 Information Theory and Applications Workshop (ITA), 2018, p.1-10

2018

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An iterated graph laplacian approach for ranking on manifolds

Proceedings of the 17th ACM SIGKDD international conference on Knowledge discovery and data mining, 2011, p.877-885

2011

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Pegasos: Primal Estimated sub-GrAdient SOlver for SVM

ACM International Conference Proceeding Series; Vol. 227: Proceedings of the 24th international conference on Machine learning; 20-24 June 2007, 2007, p.807-814

2007

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Stochastic gradient descent, weighted sampling, and the randomized Kaczmarz algorithm

Pegasos: primal estimated sub-gradient solver for SVM

Sketching meets random projection in the dual: A provable recovery algorithm for big and high-dimensional data

Pegasos: primal estimated sub-gradient solver for SVM

Trading Accuracy for Sparsity in Optimization Problems with Sparsity Constraints

Lower bounds for non-convex stochastic optimization

Rank, Trace-Norm and Max-Norm

Data-Dependent Convergence for Consensus Stochastic Optimization

A theory of learning with similarity functions

Optimistic Rates: A Unifying Theory for Interpolation Learning and Regularization in Linear Regression

Sparse Data Reconstruction, Missing Value and Multiple Imputation through Matrix Factorization

Uncovering shared structures in multiclass classification

Distribution of Short Paired Duplications in Mammalian Genomes

Fast maximum margin matrix factorization for collaborative prediction

An accelerated communication-efficient primal-dual optimization framework for structured machine learning

Distributed stochastic optimization and learning

Maximum likelihood bounded tree-width Markov networks

From Fair Decision Making To Social Equality

Learning Bounds for Support Vector Machines with Learned Kernels

Implicit Regularization in Matrix Factorization

An iterated graph laplacian approach for ranking on manifolds

Pegasos: Primal Estimated sub-GrAdient SOlver for SVM

Are There Local Maxima in the Infinite-Sample Likelihood of Gaussian Mixture Estimation?

How Good Is a Kernel When Used as a Similarity Measure?

Pegasos: primal estimated sub-gradient solver for SVM: Optimization and Machine Learning

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