Please note: This is a beta version of the new dblp website.
You can find the classic dblp view of this page here.
You can find the classic dblp view of this page here.
Michael W. Mahoney
2010 – today
- 2013
[c29]Aaron B. Adcock, Blair D. Sullivan, Oscar R. Hernandez, Michael W. Mahoney: Evaluating OpenMP Tasking at Scale for the Computation of Graph Hyperbolicity. IWOMP 2013: 71-83- [c28]Kenneth L. Clarkson, Petros Drineas, Malik Magdon-Ismail, Michael W. Mahoney, Xiangrui Meng, David P. Woodruff: The Fast Cauchy Transform and Faster Robust Linear Regression. SODA 2013: 466-477
- [c27]Xiangrui Meng, Michael W. Mahoney: Low-distortion subspace embeddings in input-sparsity time and applications to robust linear regression. STOC 2013: 91-100
- [i29]Alex Gittens, Michael W. Mahoney: Revisiting the Nystrom Method for Improved Large-Scale Machine Learning. CoRR abs/1303.1849 (2013)
- [i28]Toke Jansen Hansen, Michael W. Mahoney: Semi-supervised Eigenvectors for Large-scale Locally-biased Learning. CoRR abs/1304.7528 (2013)
- [i27]Jiyan Yang, Xiangrui Meng, Michael W. Mahoney: Quantile Regression for Large-scale Applications. CoRR abs/1305.0087 (2013)
- [i26]Ping Ma, Michael W. Mahoney, Bin Yu: A Statistical Perspective on Algorithmic Leveraging. CoRR abs/1306.5362 (2013)
- 2012
- [j14]Andras Bodor, István Csabai, Michael W. Mahoney, Norbert Solymosi: rCUR: an R package for CUR matrix decomposition. BMC Bioinformatics 13: 103 (2012)
- [c26]Michael W. Mahoney, Petros Drineas, Malik Magdon-Ismail, David P. Woodruff: Fast approximation of matrix coherence and statistical leverage. ICML 2012
- [c25]Wei Chen, Wenjie Fang, Guangda Hu, Michael W. Mahoney: On the Hyperbolicity of Small-World and Tree-Like Random Graphs. ISAAC 2012: 278-288
- [c24]Toke Jansen Hansen, Michael W. Mahoney: Semi-supervised Eigenvectors for Locally-biased Learning. NIPS 2012: 2537-2545
- [c23]Michael W. Mahoney: Approximate computation and implicit regularization for very large-scale data analysis. PODS 2012: 143-154
- [i25]Wei Chen, Wenjie Fang, Guangda Hu, Michael W. Mahoney: On the Hyperbolicity of Small-World Networks and Tree-Like Graphs. CoRR abs/1201.1717 (2012)
- [i24]Michael W. Mahoney: Approximate Computation and Implicit Regularization for Very Large-scale Data Analysis. CoRR abs/1203.0786 (2012)
- [i23]Ping Li, Michael W. Mahoney, Yiyuan She: Approximating Higher-Order Distances Using Random Projections. CoRR abs/1203.3492 (2012)
- [i22]Kenneth L. Clarkson, Petros Drineas, Malik Magdon-Ismail, Michael W. Mahoney, Xiangrui Meng, David P. Woodruff: The Fast Cauchy Transform: with Applications to Basis Construction, Regression, and Subspace Approximation in L1. CoRR abs/1207.4684 (2012)
- [i21]Xiangrui Meng, Michael W. Mahoney: Low-distortion Subspace Embeddings in Input-sparsity Time and Applications to Robust Linear Regression. CoRR abs/1210.3135 (2012)
- 2011
- [j13]Michael W. Mahoney: Randomized Algorithms for Matrices and Data. Foundations and Trends in Machine Learning 3(2): 123-224 (2011)
- [c22]Michael W. Mahoney, Lorenzo Orecchia: Implementing regularization implicitly via approximate eigenvector computation. ICML 2011: 121-128
- [c21]Patrick O. Perry, Michael W. Mahoney: Regularized Laplacian Estimation and Fast Eigenvector Approximation. NIPS 2011: 2420-2428
- [i20]
- [i19]Mihai Cucuringu, Michael W. Mahoney: Localization on low-order eigenvectors of data matrices. CoRR abs/1109.1355 (2011)
- [i18]Petros Drineas, Malik Magdon-Ismail, Michael W. Mahoney, David P. Woodruff: Fast approximation of matrix coherence and statistical leverage. CoRR abs/1109.3843 (2011)
- [i17]Xiangrui Meng, Michael A. Saunders, Michael W. Mahoney: LSRN: A Parallel Iterative Solver for Strongly Over- or Under-Determined Systems. CoRR abs/1109.5981 (2011)
- [i16]Patrick O. Perry, Michael W. Mahoney: Regularized Laplacian Estimation and Fast Eigenvector Approximation. CoRR abs/1110.1757 (2011)
- [i15]Christos Boutsidis, Anastasios Zouzias, Michael W. Mahoney, Petros Drineas: Stochastic Dimensionality Reduction for K-means Clustering. CoRR abs/1110.2897 (2011)
- 2010
- [j12]Samir Kuller, Michael W. Mahoney: SIGACT news algorithms column: computation in large-scale scientific and internet data applications is a focus of MMDS 2010. SIGACT News 41(4): 65-72 (2010)
- [j11]Michael W. Mahoney: Computation in large-scale scientific and internet data applications is a focus of MMDS 2010. SIGKDD Explorations 12(2): 59-62 (2010)
- [c20]
- [c19]Ping Li, Michael W. Mahoney, Yiyuan She: Approximating Higher-Order Distances Using Random Projections. UAI 2010: 312-321
- [c18]Jure Leskovec, Kevin J. Lang, Michael W. Mahoney: Empirical comparison of algorithms for network community detection. WWW 2010: 631-640
- [i14]Jure Leskovec, Kevin J. Lang, Michael W. Mahoney: Empirical Comparison of Algorithms for Network Community Detection. CoRR abs/1004.3539 (2010)
- [i13]Petros Drineas, Michael W. Mahoney: Effective Resistances, Statistical Leverage, and Applications to Linear Equation Solving. CoRR abs/1005.3097 (2010)
- [i12]Michael W. Mahoney, Lorenzo Orecchia: Implementing regularization implicitly via approximate eigenvector computation. CoRR abs/1010.0703 (2010)
- [i11]Michael W. Mahoney: Algorithmic and Statistical Perspectives on Large-Scale Data Analysis. CoRR abs/1010.1609 (2010)
- [i10]Jacob Bien, Ya Xu, Michael W. Mahoney: CUR from a Sparse Optimization Viewpoint. CoRR abs/1011.0413 (2010)
- [i9]Michael W. Mahoney: Computation in Large-Scale Scientific and Internet Data Applications is a Focus of MMDS 2010. CoRR abs/1012.4231 (2010)
2000 – 2009
- 2009
- [j10]Jure Leskovec, Kevin J. Lang, Anirban Dasgupta, Michael W. Mahoney: Community Structure in Large Networks: Natural Cluster Sizes and the Absence of Large Well-Defined Clusters. Internet Mathematics 6(1): 29-123 (2009)
- [j9]Anirban Dasgupta, Petros Drineas, Boulos Harb, Ravi Kumar, Michael W. Mahoney: Sampling Algorithms and Coresets for $\ellp Regression. SIAM J. Comput. 38(5): 2060-2078 (2009)
- [c17]Christos Boutsidis, Michael W. Mahoney, Petros Drineas: Unsupervised Feature Selection for the $k$-means Clustering Problem. NIPS 2009: 153-161
- [c16]Christos Boutsidis, Michael W. Mahoney, Petros Drineas: An improved approximation algorithm for the column subset selection problem. SODA 2009: 968-977
- [c15]Kevin J. Lang, Michael W. Mahoney, Lorenzo Orecchia: Empirical Evaluation of Graph Partitioning Using Spectral Embeddings and Flow. SEA 2009: 197-208
- [i8]Michael W. Mahoney, Hariharan Narayanan: Learning with Spectral Kernels and Heavy-Tailed Data. CoRR abs/0906.4539 (2009)
- [i7]Michael W. Mahoney, Lorenzo Orecchia, Nisheeth K. Vishnoi: A Spectral Algorithm for Improving Graph Partitions. CoRR abs/0912.0681 (2009)
- 2008
- [j8]Petros Drineas, Ravi Kannan, Michael W. Mahoney: Sampling subproblems of heterogeneous Max-Cut problems and approximation algorithms. Random Struct. Algorithms 32(3): 307-333 (2008)
- [j7]Petros Drineas, Michael W. Mahoney, S. Muthukrishnan: Relative-Error CUR Matrix Decompositions. SIAM J. Matrix Analysis Applications 30(2): 844-881 (2008)
- [j6]Michael W. Mahoney, Mauro Maggioni, Petros Drineas: Tensor-CUR Decompositions for Tensor-Based Data. SIAM J. Matrix Analysis Applications 30(3): 957-987 (2008)
- [j5]Michael W. Mahoney, Lek-Heng Lim, Gunnar E. Carlsson: Algorithmic and statistical challenges in modern largescale data analysis are the focus of MMDS 2008. SIGKDD Explorations 10(2): 57-60 (2008)
- [c14]Christos Boutsidis, Michael W. Mahoney, Petros Drineas: Unsupervised feature selection for principal components analysis. KDD 2008: 61-69
- [c13]Anirban Dasgupta, Petros Drineas, Boulos Harb, Ravi Kumar, Michael W. Mahoney: Sampling algorithms and coresets for ℓp regression. SODA 2008: 932-941
- [c12]Jure Leskovec, Kevin J. Lang, Anirban Dasgupta, Michael W. Mahoney: Statistical properties of community structure in large social and information networks. WWW 2008: 695-704
- [i6]Jure Leskovec, Kevin J. Lang, Anirban Dasgupta, Michael W. Mahoney: Community Structure in Large Networks: Natural Cluster Sizes and the Absence of Large Well-Defined Clusters. CoRR abs/0810.1355 (2008)
- [i5]Michael W. Mahoney, Lek-Heng Lim, Gunnar E. Carlsson: Algorithmic and Statistical Challenges in Modern Large-Scale Data Analysis are the Focus of MMDS 2008. CoRR abs/0812.3702 (2008)
- [i4]Christos Boutsidis, Michael W. Mahoney, Petros Drineas: An Improved Approximation Algorithm for the Column Subset Selection Problem. CoRR abs/0812.4293 (2008)
- 2007
- [c11]Andreas Frommer, Michael W. Mahoney, Daniel B. Szyld: 07071 Report on Dagstuhl Seminar -- Web Information Retrieval and Linear Algebra Algorithms. Web Information Retrieval and Linear Algebra Algorithms 2007
- [c10]Andreas Frommer, Michael W. Mahoney, Daniel B. Szyld: 07071 Abstracts Collection -- Web Information Retrieval and Linear Algebra Algorithms. Web Information Retrieval and Linear Algebra Algorithms 2007
- [c9]Anirban Dasgupta, Petros Drineas, Boulos Harb, Vanja Josifovski, Michael W. Mahoney: Feature selection methods for text classification. KDD 2007: 230-239
- [e1]Andreas Frommer, Michael W. Mahoney, Daniel B. Szyld (Eds.): Web Information Retrieval and Linear Algebra Algorithms, 11.02. - 16.02.2007. Dagstuhl Seminar Proceedings 07071, Internationales Begegnungs- und Forschungszentrum für Informatik (IBFI), Schloss Dagstuhl, Germany 2007
- [i3]Anirban Dasgupta, Petros Drineas, Boulos Harb, Ravi Kumar, Michael W. Mahoney: Sampling Algorithms and Coresets for Lp Regression. CoRR abs/0707.1714 (2007)
- [i2]Petros Drineas, Michael W. Mahoney, S. Muthukrishnan: Relative-Error CUR Matrix Decompositions. CoRR abs/0708.3696 (2007)
- [i1]Petros Drineas, Michael W. Mahoney, S. Muthukrishnan, Tamás Sarlós: Faster Least Squares Approximation. CoRR abs/0710.1435 (2007)
- 2006
- [j4]Petros Drineas, Ravi Kannan, Michael W. Mahoney: Fast Monte Carlo Algorithms for Matrices I: Approximating Matrix Multiplication. SIAM J. Comput. 36(1): 132-157 (2006)
- [j3]Petros Drineas, Ravi Kannan, Michael W. Mahoney: Fast Monte Carlo Algorithms for Matrices II: Computing a Low-Rank Approximation to a Matrix. SIAM J. Comput. 36(1): 158-183 (2006)
- [j2]Petros Drineas, Ravi Kannan, Michael W. Mahoney: Fast Monte Carlo Algorithms for Matrices III: Computing a Compressed Approximate Matrix Decomposition. SIAM J. Comput. 36(1): 184-206 (2006)
- [c8]Petros Drineas, Michael W. Mahoney, S. Muthukrishnan: Subspace Sampling and Relative-Error Matrix Approximation: Column-Based Methods. APPROX-RANDOM 2006: 316-326
- [c7]Petros Drineas, Michael W. Mahoney, S. Muthukrishnan: Subspace Sampling and Relative-Error Matrix Approximation: Column-Row-Based Methods. ESA 2006: 304-314
- [c6]Michael W. Mahoney, Mauro Maggioni, Petros Drineas: Tensor-CUR decompositions for tensor-based data. KDD 2006: 327-336
- [c5]Petros Drineas, Michael W. Mahoney, S. Muthukrishnan: Sampling algorithms for l2 regression and applications. SODA 2006: 1127-1136
- [c4]Petros Drineas, Michael W. Mahoney: Randomized Algorithms for Matrices and Massive Data Sets. VLDB 2006: 1269
- 2005
- [j1]Petros Drineas, Michael W. Mahoney: On the Nyström Method for Approximating a Gram Matrix for Improved Kernel-Based Learning. Journal of Machine Learning Research 6: 2153-2175 (2005)
- [c3]Petros Drineas, Michael W. Mahoney: Approximating a Gram Matrix for Improved Kernel-Based Learning. COLT 2005: 323-337
- [c2]Petros Drineas, Ravi Kannan, Michael W. Mahoney: Sampling Sub-problems of Heterogeneous Max-cut Problems and Approximation Algorithms. STACS 2005: 57-68
- 2003
- [c1]Ravi Kannan, Michael W. Mahoney, Ravi Montenegro: Rapid Mixing of Several Markov Chains for a Hard-Core Model. ISAAC 2003: 663-675
Coauthor Index
data released under the ODC-BY 1.0 license. See also our legal information page
last updated on 2013-10-02 11:16 CEST by the dblp team