Publications

Found 58 results
Author Title Type [ Year(Asc)]
Filters: Author is M. W. Mahoney  [Clear All Filters]
2020
Martin, C.. H., & Mahoney M. W. (2020).  Heavy-Tailed Universality Predicts Trends in Test Accuracies for Very Large Pre-Trained Deep Neural Networks. Proceedings of 2020 SDM Conference.
Ma, L.., Montague G.., Ye J.., Yao Z.., Gholami A.., Keutzer K.., et al. (2020).  Inefficiency of K-FAC for Large Batch Size Training. Proceedings of the AAAI-20 Conference.
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.
2019
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.
2018
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.
2017
Jing, L., Liu B., Choi J., Janin A., Bernd J., Mahoney M. W., et al. (2017).  DCAR: A Discriminative and Compact Audio Representation for Audio Processing. IEEE Transactions on Multimedia. PP(99), 
2016
Mahoney, M. W., 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. W. (2016).  Avoiding communication in primal and dual block coordinate descent methods.
Jing, L., Liu B., Choi J., Janin A., Bernd J., Mahoney M. W., 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. W. (2016).  Exploiting Optimization for Local Graph Clustering.
Yang, J., Mahoney M. W., Saunders M. A., & Sun Y. (2016).  Feature-distributed sparse regression: a screen-and-clean approach. Proceedings of the 2016 NIPS Conference.

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