Found 58 results
Author Title Type [ Year(Asc)]
Filters: Author is M. W. Mahoney  [Clear All Filters]
Zhang, T.., Yao Z.., Gholami A.., Keutzer K.., Gonzalez J.., Biros G.., et al. (2019).  ANODEV2: A Coupled Neural ODE Evolution Framework. Proceedings of the 2019 NeurIPS Conference.
Derezinski, M.., & Mahoney M. W. (2019).  Distributed estimation of the inverse Hessian by determinantal averaging. Proceedings of the 2019 NeurIPS Conference.
Kylasa, S.. B., Roosta-Khorasani F.., Mahoney M.. W., & Grama A.. (2019).  GPU Accelerated Sub-Sampled Newton's Method. Proceedings of the 2019 SDM Conference. 702-710.
Dong, Z.., Yao Z.., Gholami A.., Mahoney M. W., & Keutzer K.. (2019).  HAWQ: Hessian AWare Quantization of Neural Networks with Mixed-Precision. Proceedings of ICCV 2019.
Derezinski, M.., Clarkson K.. L., Mahoney M. W., & Warmuth M.. K. (2019).  Minimax experimental design: Bridging the gap between statistical and worst-case approaches to least squares regression. Proceedings of 2019 COLT.
Martin, C.. H., & Mahoney M. W. (2019).  Statistical Mechanics Methods for Discovering Knowledge from Modern Production Quality Neural Networks. Proceedings of the 25th Annual SIGKDD. 3239-3240.
Roosta-Khorasani, F.., & Mahoney M. W. (2019).  Sub-Sampled Newton Methods. Mathematical Programming. 293-326.
Martin, C.. H., & Mahoney M. W. (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.. W. (2019).  Trust Region Based Adversarial Attack on Neural Networks. Proceedings of the 32nd CVPR Conference. 11350-11359.
Gittens, A.., Rothauge K.., Wang S.., Mahoney M.. W., 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.. W., 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.. W. (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.. W. (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.. W. (2018).  Hessian-based Analysis of Large Batch Training and Robustness to Adversaries. Proceedings of the 2018 NeurIPS Conference. 4954-4964.
Mahoney, M. W., Duchi J. C., & Gilbert A. C. (2018).  The Mathematics of Data. 25,
Fountoulakis, K.., Gleich D.. F., & Mahoney M.. W. (2018).  A Short Introduction to Local Graph Clustering Methods and Software. Abstracts of the 7th International Conference on Complex Networks and Their Applications.