Publications

Found 70 results
Author Title [ Type(Desc)] Year
Filters: Author is M. W. Mahoney  [Clear All Filters]
Conference Paper
N. Erichson, B., Taylor D., Wu Q., & Mahoney M. (2021).  Noise-Response Analysis of Deep Neural Networks Quantifies Robustness and Fingerprints Structural Malware. Proceedings of the 2021 SIAM International Conference on Data Mining (SDM). 100-108.
Lim, S. Hoe, N. Erichson B., Hodgkinson L., & Mahoney M. (2021).  Noisy Recurrent Neural Networks. Advances in Neural Information Processing Systems Conference. 34,
Shun, J., Roosta-Khorasani F., Fountoulakis K., & Mahoney M. (2016).  Parallel Local Graph Clustering. Proceedings of the VLDB Endowment. 9(12), 
Shen, S.., Dong Z.., Ye J.., Ma L.., Yao Z.., Gholami A.., et al. (2020).  Q-BERT: Hessian Based Ultra Low Precision Quantization of BERT. Proceedings of the AAAI-20 Conference.
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.
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.
Veldt, N., Gleich D., & Mahoney M. (2016).  A Simple and Strongly-Local Flow-Based Method for Cut Improvement. Proceedings of the 33rd ICML Conference.
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.
Martin, C.. H., & Mahoney M. (2019).  Statistical Mechanics Methods for Discovering Knowledge from Modern Production Quality Neural Networks. Proceedings of the 25th Annual SIGKDD. 3239-3240.
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.
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.
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.
Journal Article
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.
Jing, L., Liu B., Choi J., Janin A., Bernd J., Mahoney M., et al. (2017).  DCAR: A Discriminative and Compact Audio Representation for Audio Processing. IEEE Transactions on Multimedia. PP(99), 
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.
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.
Eshragh, A., Roosta F., Nazari A., & Mahoney M. (2022).  LSAR: Efficient Leverage Score Sampling Algorithm for the Analysis of Big Time Series Data. Journal of Machine Learning Research. 23, 1-36.
Lawlor, D., Budavári T., & Mahoney M. (2016).  Mapping the Similarities of Spectra: Global and Locally-biased Approaches to SDSS Galaxy Data. The Astrophysical Journal.
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.
Drineas, P., & Mahoney M. (2016).  RandNLA: Randomized Numerical Linear Algebra. Communications of the ACM. 59, 80-90.
N. Erichson, B., Mathelin L., Yao Z., Bruntonq S. L., Mahoney M., & J. Kutz N. (2020).  Shallow neural networks for fluid flow reconstruction with limited sensors. Proceedings of the Royal Society A. 476(2238), 

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