Publications

Found 73 results
Author Title Type [ Year(Asc)]
Filters: Author is Michael W. Mahoney  [Clear All Filters]
2019
Martin, C.. H., & Mahoney M. (2019).  Traditional and Heavy-Tailed Self Regularization in Neural Network Models. Proceeding of the 36th ICML Conference. 4284-4293.
Yao, Z.., Gholami A.., Xu P.., Keutzer K.., & Mahoney M. (2019).  Trust Region Based Adversarial Attack on Neural Networks. Proceedings of the 32nd CVPR Conference. 11350-11359.
2018
Gittens, A.., Rothauge K.., Wang S.., Mahoney M., Gerhardt L.., Prabhat, et al. (2018).  Accelerating Large-Scale Data Analysis by Offloading to High-Performance Computing Libraries using Alchemist. Proceedings of the 24th Annual SIGKDD. 293-301.
Gittens, A.., Rothauge K.., Mahoney M., Wang S.., Gerhardt L.., Prabhat, et al. (2018).  Alchemist: An Apache Spark <=> MPI Interface. Concurrency and Computation: Practice and Experience (Special Issue of the Cray User Group, CUG 2018), e5026.
Lopes, M.. E., Wang S.., & Mahoney M. (2018).  Error Estimation for Randomized Least-Squares Algorithms via the Bootstrap. Proceedings of the 35th ICML Conference. 3223-3232.
Liu, B.., Jing L.., Li J.., Yu J.., Gittens A.., & Mahoney M. (2018).  Group Collaborative Representation for Image Set Classification. International Journal of Computer Vision. 1-26.
Yao, Z.., Gholami A.., Lei Q.., Keutzer K.., & Mahoney M. (2018).  Hessian-based Analysis of Large Batch Training and Robustness to Adversaries. Proceedings of the 2018 NeurIPS Conference. 4954-4964.
Mahoney, M., Duchi J. C., & Gilbert A. C. (2018).  The Mathematics of Data. 25,
Fountoulakis, K.., Gleich D.. F., & Mahoney M. (2018).  A Short Introduction to Local Graph Clustering Methods and Software. Abstracts of the 7th International Conference on Complex Networks and Their Applications.
2016
Mahoney, M., Rao S., Wang D., & Zhang P. (2016).  Approximating the Solution to Mixed Packing and Covering LPs in parallel time.
Devarakonda, A., Fountoulakis K., Demmel J., & Mahoney M. (2016).  Avoiding communication in primal and dual block coordinate descent methods.
Jing, L., Liu B., Choi J., Janin A., Bernd J., Mahoney M., et al. (2016).  A discriminative and compact audio representation for event detection. Proceedings of the 2016 ACM Conference on Multimedia (MM '16). 57-61.
Fountoulakis, K., Chen X., Shun J., Roosta-Khorasani F., & Mahoney M. (2016).  Exploiting Optimization for Local Graph Clustering.
Yang, J., Mahoney M., Saunders M. A., & Sun Y. (2016).  Feature-distributed sparse regression: a screen-and-clean approach. Proceedings of the 2016 NIPS Conference.
Chen, X., Roosta-Khorasani F., Bartlett P. L., & Mahoney M. (2016).  FLAG: Fast Linearly-Coupled Adaptive Gradient Method.
Lawlor, D., Budavári T., & Mahoney M. (2016).  Mapping the Similarities of Spectra: Global and Locally-biased Approaches to SDSS Galaxy Data. The Astrophysical Journal.
Gittens, A., Devarakonda A., Racah E., Ringenburg M., Gerhardt L., Kottalam J., et al. (2016).  Matrix Factorization at Scale: a Comparison of Scientific Data Analytics in Spark and C+MPI Using Three Case Studies.
Gleich, D., & Mahoney M. (2016).  Mining Large graphs. Handbook of Big Data. 191-220.
Gittens, A., Kottalam J., Yang J., Ringenburg M. F., Chhugani J., Racah E., et al. (2016).  A multi-platform evaluation of the randomized CX low-rank matrix factorization in Spark. Proceedings of the 5th International Workshop on Parallel and Distributed Computing for Large Scale Machine Learning and Big Data Analytics.
Fountoulakis, K., Gleich D., & Mahoney M. (2016).  An optimization approach to locally-biased graph algorithms.
Shun, J., Roosta-Khorasani F., Fountoulakis K., & Mahoney M. (2016).  Parallel Local Graph Clustering. Proceedings of the VLDB Endowment. 9(12), 
Gallopoulos, E., Drineas P., Ipsen I., & Mahoney M. (2016).  RandNLA, Pythons, and the CUR for Your Data Problems: Reporting from G2S3 2015 in Delphi. SIAM News.
Drineas, P., & Mahoney M. (2016).  RandNLA: Randomized Numerical Linear Algebra. Communications of the ACM. 59, 80-90.
Veldt, N., Gleich D., & Mahoney M. (2016).  A Simple and Strongly-Local Flow-Based Method for Cut Improvement. Proceedings of the 33rd ICML Conference.

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