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We design and mathematically analyze sampling-based algorithms for regularized loss minimization problems that are implementable in popular computational models for large data, in which the access to the data is restricted in some way.
Vladimir N. Vapnik · 1905
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On the limited memory bfgs method for large scale optimization
Dong C Liu and Jorge Nocedal · 1989
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Streaming-data algorithms for high-quality clustering
Liadan O’Callaghan, Adam Meyerson, Rajeev Motwani, Nina Mishra, and Sudipto Guha · 2002
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On coresets for k-means and k-median clustering
S. Har-Peled and S. Mazumdar · 2004
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A k -median algorithm with running time independent of data size
Adam Meyerson, Liadan O’Callaghan, and Serge A. Plotkin · 2004
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Core vector machines: Fast svm training on very large data sets
Ivor W. Tsang, James T. Kwok, and Pak-Ming Cheung · 2005
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Sampling algorithms and coresets for ℓ p \ell_{p} regression
Anirban Dasgupta, Petros Drineas, Boulos Harb, Ravi Kumar, and Michael W. Mahoney · 2009
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A unified framework for high-dimensional analysis of m-estimators with decomposable regularizers
Sahand N. Negahban, Pradeep Ravikumar, Martin J. Wainwright, and Bin Yu · 2009
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Sebastian Ruder · 2016
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Dheeru Dua and Casey Graff · 2017
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Efficient massively parallel methods for dynamic programming
Sungjin Im, Benjamin Moseley, and Xiaorui Sun · 2017
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Scalable k -means clustering via lightweight coresets
Olivier Bachem, Mario Lucic, and Andreas Krause · 2018
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mlpack 3: a fast, flexible machine learning library
Ryan R. Curtin, Marcus Edel, Mikhail Lozhnikov, Yannis Mentekidis, Sumedh Ghaisas, and Shangtong Zhang · 2018
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Coresets-methods and history: A theoreticians design pattern for approximation and streaming algorithms
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Randomized composable core-sets for distributed submodular maximization
Vahab S. Mirrokni and Morteza Zadimoghaddam · 2015
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Vladimir Braverman, Dan Feldman, and Harry Lang · 2016
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Mahmoud Abo Khamis, Hung Q. Ngo, and Atri Rudra · 2016
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Alexander Munteanu and Chris Schwiegelshohn · 2018
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On coresets for logistic regression
Alexander Munteanu, Chris Schwiegelshohn, Christian Sohler, and David P. Woodruff · 2018
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Coresets for monotonic functions with applications to deep learning
Elad Tolochinsky and Dan Feldman · 2018
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