Michael W. Mahoney
Orcid: 0000-0001-7920-4652Affiliations:
- University of California, Berkeley, Department of Statistics
- Stanford University, Department of Mathematics
According to our database1,
Michael W. Mahoney
authored at least 300 papers
between 2003 and 2024.
Collaborative distances:
Collaborative distances:
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Bibliography
2024
Using Uncertainty Quantification to Characterize and Improve Out-of-Domain Learning for PDEs.
CoRR, 2024
Data-Efficient Operator Learning via Unsupervised Pretraining and In-Context Learning.
CoRR, 2024
CoRR, 2024
SALSA: Sequential Approximate Leverage-Score Algorithm with Application in Analyzing Big Time Series Data.
CoRR, 2024
2023
Flow-Based Algorithms for Improving Clusters: A Unifying Framework, Software, and Performance.
SIAM Rev., February, 2023
Math. Program., 2023
Multi-scale Local Network Structure Critically Impacts Epidemic Spread and Interventions.
CoRR, 2023
CoRR, 2023
CoRR, 2023
CoRR, 2023
Surrogate-based Autotuning for Randomized Sketching Algorithms in Regression Problems.
CoRR, 2023
CoRR, 2023
CoRR, 2023
CoRR, 2023
Randomized Numerical Linear Algebra : A Perspective on the Field With an Eye to Software.
CoRR, 2023
Proceedings of the SC '23 Workshops of The International Conference on High Performance Computing, 2023
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023
Towards Foundation Models for Scientific Machine Learning: Characterizing Scaling and Transfer Behavior.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023
Test Accuracy vs. Generalization Gap: Model Selection in NLP without Accessing Training or Testing Data.
Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023
Proceedings of the International Conference on Machine Learning, 2023
Constrained Optimization via Exact Augmented Lagrangian and Randomized Iterative Sketching.
Proceedings of the International Conference on Machine Learning, 2023
Proceedings of the International Conference on Machine Learning, 2023
Proceedings of the International Conference on Machine Learning, 2023
Proceedings of the Eleventh International Conference on Learning Representations, 2023
Proceedings of the Eleventh International Conference on Learning Representations, 2023
Proceedings of the ECAI 2023 - 26th European Conference on Artificial Intelligence, September 30 - October 4, 2023, Kraków, Poland, 2023
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023
2022
Asymptotic Analysis of Sampling Estimators for Randomized Numerical Linear Algebra Algorithms.
J. Mach. Learn. Res., 2022
LSAR: Efficient Leverage Score Sampling Algorithm for the Analysis of Big Time Series Data.
J. Mach. Learn. Res., 2022
EURO J. Comput. Optim., 2022
Asymptotic Convergence Rate and Statistical Inference for Stochastic Sequential Quadratic Programming.
CoRR, 2022
Evaluating natural language processing models with generalization metrics that do not need access to any training or testing data.
CoRR, 2022
NoisyMix: Boosting Robustness by Combining Data Augmentations, Stability Training, and Noise Injections.
CoRR, 2022
Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2022
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022
Proceedings of the International Conference on Machine Learning, 2022
Proceedings of the International Conference on Machine Learning, 2022
Proceedings of the International Conference on Machine Learning, 2022
Proceedings of the International Conference on Machine Learning, 2022
Proceedings of the International Conference on Machine Learning, 2022
Proceedings of the Tenth International Conference on Learning Representations, 2022
Proceedings of the Tenth International Conference on Learning Representations, 2022
Doubly Adaptive Scaled Algorithm for Machine Learning Using Second-Order Information.
Proceedings of the Tenth International Conference on Learning Representations, 2022
Proceedings of the IEEE International Conference on Acoustics, 2022
2021
SIAM J. Sci. Comput., 2021
Implicit Self-Regularization in Deep Neural Networks: Evidence from Random Matrix Theory and Implications for Learning.
J. Mach. Learn. Res., 2021
Limit theorems for out-of-sample extensions of the adjacency and Laplacian spectral embeddings.
J. Mach. Learn. Res., 2021
Learning from learning machines: a new generation of AI technology to meet the needs of science.
CoRR, 2021
CoRR, 2021
Post-mortem on a deep learning contest: a Simpson's paradox and the complementary roles of scale metrics versus shape metrics.
CoRR, 2021
CoRR, 2021
CoRR, 2021
Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, 2021
Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, 2021
Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, 2021
Noise-Response Analysis of Deep Neural Networks Quantifies Robustness and Fingerprints Structural Malware.
Proceedings of the 2021 SIAM International Conference on Data Mining, 2021
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021
Training Recommender Systems at Scale: Communication-Efficient Model and Data Parallelism.
Proceedings of the KDD '21: The 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2021
Improved Guarantees and a Multiple-descent Curve for Column Subset Selection and the Nystrom Method (Extended Abstract).
Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, 2021
Proceedings of the 38th International Conference on Machine Learning, 2021
Proceedings of the 38th International Conference on Machine Learning, 2021
Proceedings of the 38th International Conference on Machine Learning, 2021
Proceedings of the 38th International Conference on Machine Learning, 2021
Adversarially-Trained Deep Nets Transfer Better: Illustration on Image Classification.
Proceedings of the 9th International Conference on Learning Representations, 2021
Proceedings of the 9th International Conference on Learning Representations, 2021
Proceedings of the 9th International Conference on Learning Representations, 2021
Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, 2021
Proceedings of the Conference on Learning Theory, 2021
Improving Semi-supervised Federated Learning by Reducing the Gradient Diversity of Models.
Proceedings of the 2021 IEEE International Conference on Big Data (Big Data), 2021
Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021
Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021
2020
Math. Program., 2020
Fast Distributed Training of Deep Neural Networks: Dynamic Communication Thresholding for Model and Data Parallelism.
CoRR, 2020
CoRR, 2020
Improved guarantees and a multiple-descent curve for the Column Subset Selection Problem and the Nyström method.
CoRR, 2020
Predicting trends in the quality of state-of-the-art neural networks without access to training or testing data.
CoRR, 2020
Proceedings of the 2020 SIAM International Conference on Data Mining, 2020
Heavy-Tailed Universality Predicts Trends in Test Accuracies for Very Large Pre-Trained Deep Neural Networks.
Proceedings of the 2020 SIAM International Conference on Data Mining, 2020
Newton-ADMM: a distributed GPU-accelerated optimizer for multiclass classification problems.
Proceedings of the International Conference for High Performance Computing, 2020
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020
A random matrix analysis of random Fourier features: beyond the Gaussian kernel, a precise phase transition, and the corresponding double descent.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020
Exact expressions for double descent and implicit regularization via surrogate random design.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020
Precise expressions for random projections: Low-rank approximation and randomized Newton.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020
Improved guarantees and a multiple-descent curve for Column Subset Selection and the Nystrom method.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020
Debiasing Distributed Second Order Optimization with Surrogate Sketching and Scaled Regularization.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020
Proceedings of the 9th International Conference on Pattern Recognition Applications and Methods, 2020
Proceedings of the 37th International Conference on Machine Learning, 2020
Proceedings of the 37th International Conference on Machine Learning, 2020
Proceedings of the 37th International Conference on Machine Learning, 2020
Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing, 2020
Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020
Proceedings of the 2020 IEEE International Conference on Big Data (IEEE BigData 2020), 2020
Proceedings of the 2020 IEEE International Conference on Big Data (IEEE BigData 2020), 2020
Asymptotic Analysis of Sampling Estimators for Randomized Numerical Linear Algebra Algorithms.
Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020
Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020
Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020
Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020
2019
The Difficulties of Addressing Interdisciplinary Challenges at theFoundations of Data Science.
SIGACT News, 2019
SIAM J. Sci. Comput., 2019
SIAM J. Matrix Anal. Appl., 2019
Scalable Kernel K-Means Clustering with Nystr\"om Approximation: Relative-Error Bounds.
J. Mach. Learn. Res., 2019
J. Mach. Learn. Res., 2019
Int. J. Comput. Vis., 2019
Running Alchemist on Cray XC and CS Series Supercomputers: Dask and PySpark Interfaces, Deployment Options, and Data Transfer Times.
CoRR, 2019
Bootstrapping the Operator Norm in High Dimensions: Error Estimation for Covariance Matrices and Sketching.
CoRR, 2019
The Difficulties of Addressing Interdisciplinary Challenges at the Foundations of Data Science.
CoRR, 2019
CoRR, 2019
Shallow Learning for Fluid Flow Reconstruction with Limited Sensors and Limited Data.
CoRR, 2019
Proceedings of the 2019 SIAM International Conference on Data Mining, 2019
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019
Statistical Mechanics Methods for Discovering Knowledge from Modern Production Quality Neural Networks.
Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2019
Proceedings of the 36th International Conference on Machine Learning, 2019
Proceedings of the 2019 IEEE/CVF International Conference on Computer Vision, 2019
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2019
Minimax experimental design: Bridging the gap between statistical and worst-case approaches to least squares regression.
Proceedings of the Conference on Learning Theory, 2019
2018
On the Computational Inefficiency of Large Batch Sizes for Stochastic Gradient Descent.
CoRR, 2018
Large batch size training of neural networks with adversarial training and second-order information.
CoRR, 2018
Proceedings of the 2018 IEEE/WIC/ACM International Conference on Web Intelligence, 2018
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018
Accelerating Large-Scale Data Analysis by Offloading to High-Performance Computing Libraries using Alchemist.
Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2018
Proceedings of the 2018 IEEE International Parallel and Distributed Processing Symposium, 2018
Proceedings of the 35th International Conference on Machine Learning, 2018
Proceedings of the 35th International Conference on Machine Learning, 2018
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2018
2017
IEEE Trans. Multim., 2017
J. Mach. Learn. Res., 2017
Sketched Ridge Regression: Optimization Perspective, Statistical Perspective, and Model Averaging.
J. Mach. Learn. Res., 2017
Rethinking generalization requires revisiting old ideas: statistical mechanics approaches and complex learning behavior.
CoRR, 2017
Scalable Kernel K-Means Clustering with Nystrom Approximation: Relative-Error Bounds.
CoRR, 2017
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017
Proceedings of the 34th International Conference on Machine Learning, 2017
Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics, 2017
2016
NII Shonan Meet. Rep., 2016
Proc. IEEE, 2016
J. Mach. Learn. Res., 2016
J. Mach. Learn. Res., 2016
J. Mach. Learn. Res., 2016
Mapping the Similarities of Spectra: Global and Locally-biased Approaches to SDSS Galaxy Data.
CoRR, 2016
CoRR, 2016
Matrix Factorization at Scale: a Comparison of Scientific Data Analytics in Spark and C+MPI Using Three Case Studies.
CoRR, 2016
Proceedings of the Twenty-Seventh Annual ACM-SIAM Symposium on Discrete Algorithms, 2016
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016
Proceedings of the 2016 ACM Conference on Multimedia Conference, 2016
A Multi-Platform Evaluation of the Randomized CX Low-Rank Matrix Factorization in Spark.
Proceedings of the 2016 IEEE International Parallel and Distributed Processing Symposium Workshops, 2016
Proceedings of the 33nd International Conference on Machine Learning, 2016
Unified Acceleration Method for Packing and Covering Problems via Diameter Reduction.
Proceedings of the 43rd International Colloquium on Automata, Languages, and Programming, 2016
Approximating the Solution to Mixed Packing and Covering LPs in Parallel O˜(epsilon^{-3}) Time.
Proceedings of the 43rd International Colloquium on Automata, Languages, and Programming, 2016
Matrix factorizations at scale: A comparison of scientific data analytics in spark and C+MPI using three case studies.
Proceedings of the 2016 IEEE International Conference on Big Data (IEEE BigData 2016), 2016
Structural Properties Underlying High-Quality Randomized Numerical Linear Algebra Algorithms.
Proceedings of the Handbook of Big Data., 2016
2015
IEEE Trans. Inf. Theory, 2015
Faster Parallel Solver for Positive Linear Programs via Dynamically-Bucketed Selective Coordinate Descent.
CoRR, 2015
CoRR, 2015
Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015
Proceedings of the 21th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2015
Statistical and Algorithmic Perspectives on Randomized Sketching for Ordinary Least-Squares.
Proceedings of the 32nd International Conference on Machine Learning, 2015
Spectral Gap Error Bounds for Improving CUR Matrix Decomposition and the Nyström Method.
Proceedings of the Eighteenth International Conference on Artificial Intelligence and Statistics, 2015
2014
IEEE Signal Process. Mag., 2014
SIAM J. Sci. Comput., 2014
J. Mach. Learn. Res., 2014
Think Locally, Act Locally: The Detection of Small, Medium-Sized, and Large Communities in Large Networks.
CoRR, 2014
Anti-differentiating approximation algorithms: A case study with min-cuts, spectral, and flow.
Proceedings of the 31th International Conference on Machine Learning, 2014
Proceedings of the 2014 IEEE Conference on Computer Vision and Pattern Recognition, 2014
2013
Low-distortion subspace embeddings in input-sparsity time and applications to robust linear regression.
Proceedings of the Symposium on Theory of Computing Conference, 2013
Proceedings of the OpenMP in the Era of Low Power Devices and Accelerators, 2013
Proceedings of the 30th International Conference on Machine Learning, 2013
Proceedings of the 2013 IEEE 13th International Conference on Data Mining, 2013
2012
A local spectral method for graphs: with applications to improving graph partitions and exploring data graphs locally.
J. Mach. Learn. Res., 2012
J. Mach. Learn. Res., 2012
The Fast Cauchy Transform: with Applications to Basis Construction, Regression, and Subspace Approximation in L1
CoRR, 2012
Approximate computation and implicit regularization for very large-scale data analysis.
Proceedings of the 31st ACM SIGMOD-SIGACT-SIGART Symposium on Principles of Database Systems, 2012
Proceedings of the Advances in Neural Information Processing Systems 25: 26th Annual Conference on Neural Information Processing Systems 2012. Proceedings of a meeting held December 3-6, 2012
Proceedings of the Algorithms and Computation - 23rd International Symposium, 2012
2011
CoRR, 2011
Proceedings of the Advances in Neural Information Processing Systems 24: 25th Annual Conference on Neural Information Processing Systems 2011. Proceedings of a meeting held 12-14 December 2011, 2011
Proceedings of the 28th International Conference on Machine Learning, 2011
2010
Computation in large-scale scientific and internet data applications is a focus of MMDS 2010.
SIGKDD Explor., 2010
SIGACT news algorithms column: computation in large-scale scientific and internet data applications is a focus of MMDS 2010.
SIGACT News, 2010
Effective Resistances, Statistical Leverage, and Applications to Linear Equation Solving
CoRR, 2010
Proceedings of the 19th International Conference on World Wide Web, 2010
Proceedings of the UAI 2010, 2010
Proceedings of the Advances in Neural Information Processing Systems 23: 24th Annual Conference on Neural Information Processing Systems 2010. Proceedings of a meeting held 6-9 December 2010, 2010
2009
SIAM J. Comput., 2009
Proc. Natl. Acad. Sci. USA, 2009
Community Structure in Large Networks: Natural Cluster Sizes and the Absence of Large Well-Defined Clusters.
Internet Math., 2009
Proceedings of the Experimental Algorithms, 8th International Symposium, 2009
Proceedings of the Twentieth Annual ACM-SIAM Symposium on Discrete Algorithms, 2009
Proceedings of the Advances in Neural Information Processing Systems 22: 23rd Annual Conference on Neural Information Processing Systems 2009. Proceedings of a meeting held 7-10 December 2009, 2009
2008
Algorithmic and statistical challenges in modern largescale data analysis are the focus of MMDS 2008.
SIGKDD Explor., 2008
Random Struct. Algorithms, 2008
Algorithmic and Statistical Challenges in Modern Large-Scale Data Analysis are the Focus of MMDS 2008
CoRR, 2008
Statistical properties of community structure in large social and information networks.
Proceedings of the 17th International Conference on World Wide Web, 2008
Proceedings of the Nineteenth Annual ACM-SIAM Symposium on Discrete Algorithms, 2008
Proceedings of the 14th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2008
2007
Proceedings of the 13th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2007
07071 Abstracts Collection -- Web Information Retrieval and Linear Algebra Algorithms.
Proceedings of the Web Information Retrieval and Linear Algebra Algorithms, 11.02., 2007
07071 Report on Dagstuhl Seminar -- Web Information Retrieval and Linear Algebra Algorithms.
Proceedings of the Web Information Retrieval and Linear Algebra Algorithms, 11.02., 2007
2006
Fast Monte Carlo Algorithms for Matrices III: Computing a Compressed Approximate Matrix Decomposition.
SIAM J. Comput., 2006
Fast Monte Carlo Algorithms for Matrices II: Computing a Low-Rank Approximation to a Matrix.
SIAM J. Comput., 2006
SIAM J. Comput., 2006
Proceedings of the 32nd International Conference on Very Large Data Bases, 2006
Proceedings of the Seventeenth Annual ACM-SIAM Symposium on Discrete Algorithms, 2006
Proceedings of the Algorithms, 2006
Proceedings of the Approximation, 2006
2005
On the Nyström Method for Approximating a Gram Matrix for Improved Kernel-Based Learning.
J. Mach. Learn. Res., 2005
Sampling Sub-problems of Heterogeneous Max-cut Problems and Approximation Algorithms.
Proceedings of the STACS 2005, 2005
Proceedings of the Learning Theory, 18th Annual Conference on Learning Theory, 2005
2003
Proceedings of the Algorithms and Computation, 14th International Symposium, 2003