Publications

Found 73 results
Author Title Type [ Year(Asc)]
Filters: Author is Michael W. Mahoney  [Clear All Filters]
2016
Mahoney, M., & Drineas P. (2016).  Structural properties underlying high-quality Randomized Numerical Linear Algebra algorithms. Handbook of Big Data. 137-154.
Roosta-Khorasani, F., & Mahoney M. (2016).  Sub-Sampled Newton Methods I: Globally Convergent Algorithms.
Roosta-Khorasani, F., & Mahoney M. (2016).  Sub-Sampled Newton Methods II: Local Convergence Rates.
Xu, P., Yang J., Roosta-Khorasani F., Re C., & Mahoney M. (2016).  Sub-sampled Newton Methods with Non-uniform Sampling. Proceedings of the 2016 NIPS Conference.
2015
Wang, D., Mahoney M., Mohan N., & Rao S. (2015).  Faster Parallel Solver for Positive Linear Programs via Dynamically-Bucketed Selective Coordinate Descent.
Yang, J., Rübel O., Prabhat, Mahoney M., & Bowen B. P. (2015).  Identifying Important Ions and Positions in Mass Spectrometry Imaging Data Using CUR Matrix Decompositions. Analytical Chemistry. 87(9), 4658-4666.
Yang, J., Meng X., & Mahoney M. (2015).  Implementing Randomized Matrix Algorithms in Parallel and Distributed Environments.
Jeub, L. G. S., Mahoney M., Mucha P. J., & Porter M. A. (2015).  A Local Perspective on Community Structure in Multilayer Networks.
Zhu, R., Ma P., Mahoney M., & Yu B. (2015).  Optimal Subsampling Approaches for Large Sample Linear Regression.
Andersen, D. G., Du S. S., Mahoney M., Melgaard C., Wu K., & Gu M. (2015).  Spectral Gap Error Bounds for Improving CUR Matrix Decomposition and the Nystrom Method.
Wang, R., Li Y., Mahoney M., & Darve E. (2015).  Structured Block Basis Factorization for Scalable Kernel Matrix Evaluation.
Wang, D., Rao S., & Mahoney M. (2015).  Unified Acceleration Method for Packing and Covering Problems via Diameter Reduction. Proceedings of the 43rd ICALP Conference.
Gleich, D., & Mahoney M. (2015).  Using Local Spectral Methods to Robustify Graph-Based Learning Algorithms. Proceedings of the 21st Annual SIGKDD.
Yang, J., Chow Y-L., Re C., & Mahoney M. (2015).  Weighted SGD for ℓp Regression with Randomized Preconditioning. Proceedings of the 27th Annual SODA Conference. 558-569.
2014
Gleich, D., & Mahoney M. (2014).  Anti-Differentiating Approximation Algorithms: A Case Study with Min-Cuts, Spectral, and Flow.
Alaou, A. El, & Mahoney M. (2014).  Fast Randomized Kernel Methods With Statistical Guarantees.
Mahoney, M. (2014).  A New Spin on an Old Algorithm: Technical Perspective on "Communication Costs of Strassen's Matrix Multiplication". Communications of the ACM. 57(2), 106.
Yang, J., Sindhwani V., Avron H., & Mahoney M. (2014).  Quasi-Monte Carlo Feature Maps for Shift-Invariant Kernels.
Yang, J., Sindhwani V., Fan Q., Avron H., & Mahoney M. (2014).  Random Laplace Feature Maps for Semigroup Kernels on Histograms.
Giannakis, G. B., Bach F., Cendrillon R., Mahoney M., & Neville J. (2014).  Signal Processing for Big Data (Editorial for Special Issue). IEEE Signal Processing Magazine. 31, 15-16.
Raskutti, G., & Mahoney M. (2014).  A Statistical Perspective on Randomized Sketching for Ordinary Least-Squares.
Jeub, L. G. S., Balachandran P., Porter M. A., Mucha P. J., & Mahoney M. (2014).  Think Locally, Act Locally: The Detection of Small, Medium-Sized, and Large Communities in Large Networks.
Adcock, A. B., Sullivan B. D., & Mahoney M. (2014).  Tree Decompositions and Social Graphs.

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