Michael W. M. Mahoney
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Michael W. M. Mahoneycomputer-science Degrees
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Michael W. M. Mahoneymathematics Degrees
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Linear Algebra
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Computer Science Mathematics
Michael W. M. Mahoney's Degrees
- PhD Applied Mathematics California Institute of Technology
- Bachelors Mathematics California Institute of Technology
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(Suggest an Edit or Addition)Michael W. M. Mahoney's Published Works
Number of citations in a given year to any of this author's works
Total number of citations to an author for the works they published in a given year. This highlights publication of the most important work(s) by the author
Published Works
- A five-site model for liquid water and the reproduction of the density anomaly by rigid, nonpolarizable potential functions (2000) (1879)
- Community Structure in Large Networks: Natural Cluster Sizes and the Absence of Large Well-Defined Clusters (2008) (1806)
- Empirical comparison of algorithms for network community detection (2010) (1030)
- On the Nyström Method for Approximating a Gram Matrix for Improved Kernel-Based Learning (2005) (987)
- Statistical properties of community structure in large social and information networks (2008) (962)
- Randomized Algorithms for Matrices and Data (2011) (898)
- CUR matrix decompositions for improved data analysis (2009) (714)
- Fast Monte Carlo Algorithms for Matrices II: Computing a Low-Rank Approximation to a Matrix (2006) (534)
- Fast approximation of matrix coherence and statistical leverage (2011) (460)
- Relative-Error CUR Matrix Decompositions (2007) (450)
- Fast Monte Carlo Algorithms for Matrices I: Approximating Matrix Multiplication (2006) (443)
- Faster least squares approximation (2007) (435)
- An improved approximation algorithm for the column subset selection problem (2008) (374)
- Revisiting the Nystrom Method for Improved Large-scale Machine Learning (2013) (362)
- Q-BERT: Hessian Based Ultra Low Precision Quantization of BERT (2019) (337)
- Sampling algorithms for l2 regression and applications (2006) (333)
- Fast Monte Carlo Algorithms for Matrices III: Computing a Compressed Approximate Matrix Decomposition (2006) (314)
- Diffusion constant of the TIP5P model of liquid water (2001) (303)
- PCA-Correlated SNPs for Structure Identification in Worldwide Human Populations (2007) (292)
- A statistical perspective on algorithmic leveraging (2013) (270)
- Low-distortion subspace embeddings in input-sparsity time and applications to robust linear regression (2012) (257)
- Fast Randomized Kernel Ridge Regression with Statistical Guarantees (2015) (251)
- Feature selection methods for text classification (2007) (207)
- Randomized Dimensionality Reduction for $k$ -Means Clustering (2011) (204)
- RandNLA: randomized numerical linear algebra (2016) (195)
- Sampling algorithms and coresets for ℓp regression (2007) (176)
- A Berkeley View of Systems Challenges for AI (2017) (171)
- Newton-type methods for non-convex optimization under inexact Hessian information (2017) (160)
- Quasi-Monte Carlo Feature Maps for Shift-Invariant Kernels (2014) (148)
- Think Locally, Act Locally: The Detection of Small, Medium-Sized, and Large Communities in Large Networks (2014) (148)
- PyHessian: Neural Networks Through the Lens of the Hessian (2019) (144)
- Unsupervised Feature Selection for the $k$-means Clustering Problem (2009) (144)
- Tensor-CUR decompositions for tensor-based data (2006) (142)
- LSRN: A Parallel Iterative Solver for Strongly Over- or Underdetermined Systems (2011) (140)
- Hessian-based Analysis of Large Batch Training and Robustness to Adversaries (2018) (127)
- Unsupervised feature selection for principal components analysis (2008) (123)
- Second-Order Optimization for Non-Convex Machine Learning: An Empirical Study (2017) (117)
- A local spectral method for graphs: with applications to improving graph partitions and exploring data graphs locally (2009) (110)
- Tree-Like Structure in Large Social and Information Networks (2013) (107)
- A randomized algorithm for a tensor-based generalization of the singular value decomposition (2007) (106)
- Physics-informed Autoencoders for Lyapunov-stable Fluid Flow Prediction (2019) (105)
- Implicit Self-Regularization in Deep Neural Networks: Evidence from Random Matrix Theory and Implications for Learning (2018) (104)
- Subspace Sampling and Relative-Error Matrix Approximation: Column-Based Methods (2006) (98)
- Sub-sampled Newton methods (2018) (98)
- Sub-sampled Newton Methods with Non-uniform Sampling (2016) (94)
- The Fast Cauchy Transform and Faster Robust Linear Regression (2012) (94)
- Quantum, intramolecular flexibility, and polarizability effects on the reproduction of the density anomaly of liquid water by simple potential functions (2001) (93)
- Scalable Kernel K-Means Clustering with Nystrom Approximation: Relative-Error Bounds (2017) (93)
- GIANT: Globally Improved Approximate Newton Method for Distributed Optimization (2017) (89)
- Sub-Sampled Newton Methods I: Globally Convergent Algorithms (2016) (87)
- Fast Randomized Kernel Methods With Statistical Guarantees (2014) (84)
- Sub-Sampled Newton Methods II: Local Convergence Rates (2016) (83)
- On the Hyperbolicity of Small-World and Treelike Random Graphs (2012) (83)
- Traditional and Heavy-Tailed Self Regularization in Neural Network Models (2019) (82)
- A Statistical Perspective on Randomized Sketching for Ordinary Least-Squares (2014) (78)
- Sketched Ridge Regression: Optimization Perspective, Statistical Perspective, and Model Averaging (2017) (78)
- Skip-Gram − Zipf + Uniform = Vector Additivity (2017) (70)
- A high accuracy microwave ranging system for industrial applications (1993) (69)
- On the Computational Inefficiency of Large Batch Sizes for Stochastic Gradient Descent (2018) (65)
- Forecasting Sequential Data using Consistent Koopman Autoencoders (2020) (64)
- Lectures on Randomized Numerical Linear Algebra (2017) (64)
- Exact expressions for double descent and implicit regularization via surrogate random design (2019) (60)
- A local perspective on community structure in multilayer networks (2015) (58)
- Implementing Randomized Matrix Algorithms in Parallel and Distributed Environments (2015) (57)
- Quantile Regression for Large-Scale Applications (2013) (56)
- A random matrix analysis of random Fourier features: beyond the Gaussian kernel, a precise phase transition, and the corresponding double descent (2020) (53)
- Intra- and interpopulation genotype reconstruction from tagging SNPs. (2006) (52)
- Multiplicative noise and heavy tails in stochastic optimization (2020) (51)
- Rethinking generalization requires revisiting old ideas: statistical mechanics approaches and complex learning behavior (2017) (50)
- Random Laplace Feature Maps for Semigroup Kernels on Histograms (2014) (49)
- PowerNorm: Rethinking Batch Normalization in Transformers (2020) (45)
- Matrix factorizations at scale: A comparison of scientific data analytics in spark and C+MPI using three case studies (2016) (45)
- Predicting trends in the quality of state-of-the-art neural networks without access to training or testing data (2020) (44)
- Trust Region Based Adversarial Attack on Neural Networks (2018) (43)
- CUR from a Sparse Optimization Viewpoint (2010) (40)
- Using Local Spectral Methods to Robustify Graph-Based Learning Algorithms (2015) (40)
- Implementing regularization implicitly via approximate eigenvector computation (2010) (40)
- Inexact Nonconvex Newton-Type Methods (2018) (39)
- Future Directions in Tensor-Based Computation and Modeling (2009) (39)
- Subspace Sampling and Relative-Error Matrix Approximation: Column-Row-Based Methods (2006) (37)
- Capacity Releasing Diffusion for Speed and Locality (2017) (34)
- A Simple and Strongly-Local Flow-Based Method for Cut Improvement (2016) (34)
- Identifying important ions and positions in mass spectrometry imaging data using CUR matrix decompositions. (2015) (34)
- Approximate computation and implicit regularization for very large-scale data analysis (2012) (34)
- Anti-differentiating approximation algorithms: A case study with min-cuts, spectral, and flow (2014) (33)
- Theatres of Struggle and the End of Apartheid (review) (2005) (32)
- Weighted SGD for ℓp Regression with Randomized Preconditioning (2016) (32)
- Shallow Learning for Fluid Flow Reconstruction with Limited Sensors and Limited Data (2019) (31)
- Large batch size training of neural networks with adversarial training and second-order information (2018) (31)
- Heavy-Tailed Universality Predicts Trends in Test Accuracies for Very Large Pre-Trained Deep Neural Networks (2019) (30)
- Unified Acceleration Method for Packing and Covering Problems via Diameter Reduction (2015) (29)
- Localization on low-order eigenvectors of data matrices (2011) (29)
- Tree decompositions and social graphs (2014) (28)
- Rapid Mixing of Several Markov Chains for a Hard-Core Model (2003) (28)
- Effective Resistances, Statistical Leverage, and Applications to Linear Equation Solving (2010) (28)
- Asymptotic Analysis of Sampling Estimators for Randomized Numerical Linear Algebra Algorithms (2020) (28)
- Algorithmic and Statistical Perspectives on Large-Scale Data Analysis (2010) (27)
- Group Collaborative Representation for Image Set Classification (2019) (26)
- OverSketched Newton: Fast Convex Optimization for Serverless Systems (2019) (25)
- Newton-MR: Newton's Method Without Smoothness or Convexity (2018) (24)
- Approximating a Gram Matrix for Improved Kernel-Based Learning (Extended Abstract) (2005) (23)
- Lecture Notes on Randomized Linear Algebra (2016) (23)
- rCUR: an R package for CUR matrix decomposition (2012) (23)
- Open Problems in Data Streams, Property Testing, and Related Topics (2011) (21)
- Error Estimation for Randomized Least-Squares Algorithms via the Bootstrap (2018) (21)
- Robust Regression on MapReduce (2013) (20)
- Inefficiency of K-FAC for Large Batch Size Training (2019) (20)
- Evaluating OpenMP Tasking at Scale for the Computation of Graph Hyperbolicity (2013) (19)
- Minimax experimental design: Bridging the gap between statistical and worst-case approaches to least squares regression (2019) (19)
- Distributed estimation of the inverse Hessian by determinantal averaging (2019) (19)
- Bayesian experimental design using regularized determinantal point processes (2019) (18)
- Improved Guarantees and a Multiple-descent Curve for Column Subset Selection and the Nystrom Method (Extended Abstract) (2021) (18)
- Signal Processing for Big Data [From the Guest Editors] (2014) (18)
- Debiasing Distributed Second Order Optimization with Surrogate Sketching and Scaled Regularization (2020) (18)
- Spectral Gap Error Bounds for Improving CUR Matrix Decomposition and the Nyström Method (2015) (17)
- Stochastic Dimensionality Reduction for K-means Clustering (2011) (17)
- Structural Properties Underlying High-Quality Randomized Numerical Linear Algebra Algorithms (2016) (17)
- Algorithmic and statistical challenges in modern largescale data analysis are the focus of MMDS 2008 (2008) (17)
- Optimal Subsampling Approaches for Large Sample Linear Regression (2015) (17)
- Weighted SGD for $\ell_p$ Regression with Randomized Preconditioning (2015) (17)
- Union of Intersections (UoI) for Interpretable Data Driven Discovery and Prediction (2017) (17)
- LASAGNE: Locality and Structure Aware Graph Node Embedding (2017) (16)
- Variational perspective on local graph clustering (2016) (16)
- Statistical and Algorithmic Perspectives on Randomized Sketching for Ordinary Least-Squares (2015) (16)
- An Optimization Approach to Locally-Biased Graph Algorithms (2016) (16)
- Rethinking Batch Normalization in Transformers (2020) (16)
- Maturation of Cerebellar Purkinje Cell Population Activity during Postnatal Refinement of Climbing Fiber Network. (2017) (16)
- GPU Accelerated Sub-Sampled Newton's Method for Convex Classification Problems (2019) (15)
- Accelerating Large-Scale Data Analysis by Offloading to High-Performance Computing Libraries using Alchemist (2018) (13)
- Approximating Higher-Order Distances Using Random Projections (2010) (13)
- Hessian Eigenspectra of More Realistic Nonlinear Models (2021) (13)
- Bootstrapping the Operator Norm in High Dimensions: Error Estimation for Covariance Matrices and Sketching (2019) (13)
- Out-of-sample extension of graph adjacency spectral embedding (2018) (13)
- Alchemist: An Apache Spark ⇔ MPI interface (2018) (13)
- Structured Block Basis Factorization for Scalable Kernel Matrix Evaluation (2015) (12)
- Empirical Evaluation of Graph Partitioning Using Spectral Embeddings and Flow (2009) (12)
- Semi-supervised eigenvectors for large-scale locally-biased learning (2013) (12)
- Sparse Quantized Spectral Clustering (2020) (12)
- A Bootstrap Method for Error Estimation in Randomized Matrix Multiplication (2017) (12)
- Avoiding communication in primal and dual block coordinate descent methods (2016) (12)
- MAPPING THE SIMILARITIES OF SPECTRA: GLOBAL AND LOCALLY-BIASED APPROACHES TO SDSS GALAXIES (2016) (12)
- Regularized Laplacian Estimation and Fast Eigenvector Approximation (2011) (12)
- Approximating the Solution to Mixed Packing and Covering LPs in parallel Õ ( − 3 ) time (2016) (11)
- Approximating the Solution to Mixed Packing and Covering LPs in Parallel O˜(epsilon^{-3}) Time (2016) (11)
- Efficient Genomewide Selection of PCA‐Correlated tSNPs for Genotype Imputation (2011) (11)
- Sparse sketches with small inversion bias (2020) (11)
- Rapid estimation of electronic degrees of freedom in Monte Carlo calculations for polarizable models of liquid water (2001) (11)
- Exploiting Optimization for Local Graph Clustering (2016) (11)
- Discrete representations of the protein Cα chain (1997) (11)
- Mining Large Graphs (2016) (11)
- Improved guarantees and a multiple-descent curve for the Column Subset Selection Problem and the Nyström method (2020) (10)
- A Multi-Platform Evaluation of the Randomized CX Low-Rank Matrix Factorization in Spark (2016) (10)
- Newton-LESS: Sparsification without Trade-offs for the Sketched Newton Update (2021) (9)
- Faster Parallel Solver for Positive Linear Programs via Dynamically-Bucketed Selective Coordinate Descent (2015) (9)
- Parameter Re-Initialization through Cyclical Batch Size Schedules (2018) (8)
- GPU Accelerated Sub-Sampled Newton's Method (2018) (8)
- Sampling Sub-problems of Heterogeneous Max-cut Problems and Approximation Algorithms (2005) (8)
- DCAR: A Discriminative and Compact Audio Representation for Audio Processing (2017) (7)
- A Spectral Algorithm for Improving Graph Partitions (2009) (7)
- JumpReLU: A Retrofit Defense Strategy for Adversarial Attacks (2019) (7)
- Statistical guarantees for local graph clustering (2019) (7)
- Semi-supervised Eigenvectors for Locally-biased Learning (2012) (6)
- Feature-distributed sparse regression: a screen-and-clean approach (2016) (6)
- Newton-type methods for non-convex optimization under inexact Hessian information (2019) (6)
- A Short Introduction to Local Graph Clustering Methods and Software (2018) (6)
- A Discriminative and Compact Audio Representation for Event Detection (2016) (6)
- Asymptotic Convergence Rate and Statistical Inference for Stochastic Sequential Quadratic Programming (2022) (6)
- Lecture Notes on Spectral Graph Methods (2016) (6)
- The Mathematics of Data (2018) (6)
- Peer-Mediated Instruction and Activity Schedules: Tools for Providing Academic Support for Students With ASD (2019) (5)
- Distributed Second-order Convex Optimization (2018) (5)
- GACT: Activation Compressed Training for Generic Network Architectures (2022) (5)
- Hessian Averaging in Stochastic Newton Methods Achieves Superlinear Convergence (2022) (4)
- Avoiding Synchronization in First-Order Methods for Sparse Convex Optimization (2017) (4)
- A Spectral Algorithm for Improving Graph Partitions with Applications to Exploring Data Graphs Locally (2009) (4)
- The Fast Cauchy Transform: with Applications to Basis Construction, Regression, and Subspace Approximation in L1 (2012) (4)
- Evaluating natural language processing models with generalization metrics that do not need access to any training or testing data (2022) (4)
- Generalization Bounds using Lower Tail Exponents in Stochastic Optimizers (2021) (4)
- Doubly Adaptive Scaled Algorithm for Machine Learning Using Second-Order Information (2021) (4)
- terrainr: An R package for creating immersive virtual environments (2022) (4)
- Learning with Spectral Kernels and Heavy-Tailed Data (2009) (3)
- A Differential Geometry Perspective on Orthogonal Recurrent Models (2021) (3)
- On the Hyperbolicity of Small-World Networks and Tree-Like Graphs (2012) (3)
- Social Discrete Choice Models (2017) (3)
- Randomized algorithms for matrices and massive data sets (2006) (3)
- Newton-MR: Inexact Newton Method with minimum residual sub-problem solver (2018) (3)
- Inexact Newton-CG algorithms with complexity guarantees (2021) (3)
- Statistical Mechanics Methods for Discovering Knowledge from Modern Production Quality Neural Networks (2019) (3)
- MMDS 2008 : Algorithmic and Statistical Challenges in Modern Large-Scale Data Analysis are the Focus (2009) (2)
- Workshop on Algorithms for Modern Massive Datasets (2006) (2)
- Fully Stochastic Trust-Region Sequential Quadratic Programming for Equality-Constrained Optimization Problems (2022) (2)
- Good Classifiers are Abundant in the Interpolating Regime (2021) (2)
- Parallel and Communication Avoiding Least Angle Regression (2019) (2)
- Discrete representations of the protein C alpha chain. (1997) (2)
- Stochastic Normalizing Flows (2020) (2)
- Good linear classifiers are abundant in the interpolating regime (2020) (2)
- On Linear Convergence of Weighted Kernel Herding (2019) (2)
- Limit theorems for out-of-sample extensions of the adjacency and Laplacian spectral embeddings (2019) (2)
- Supplementary Material : Large-scale community structurein social and information networks (2009) (1)
- The Difficulties of Addressing Interdisciplinary Challenges at the Foundations of Data Science (2019) (1)
- Stochastic continuous normalizing flows: training SDEs as ODEs (2021) (1)
- THE BERKELEY DATA ANALYSIS SYSTEM (BDAS): AN OPEN SOURCE PLATFORM FOR BIG DATA ANALYTICS (2017) (1)
- GPU Accelerated Sub-Sampled Newton\textsf{'}s Method (2018) (1)
- DCAR: A Discriminative and Compact Audio Representation to Improve Event Detection (2016) (1)
- MMDS 2008 : Algorithmic and Statistical Challenges in Modern Large-Scale Data Analysis , Part I (2009) (1)
- Sampling subproblems of heterogeneous Max-Cut problems and approximation algorithms (2008) (1)
- SIGACT news algorithms column: computation in large-scale scientific and internet data applications is a focus of MMDS 2010 (2010) (1)
- Cornell University Autonomous Underwater Vehicle : Design and Implementation of the Argo AUV (2011) (1)
- Residual Networks as Nonlinear Systems: Stability Analysis using Linearization (2019) (1)
- Geometric rates of convergence for kernel-based sampling algorithms (2019) (1)
- Bridging the Gap Between Numerical Linear Algebra , Theoretical Computer Science , and Data Applications By Gene (2006) (1)
- rCUR: an R package for CUR matrix decomposition (2012) (1)
- Sampling subproblems of heterogeneous Max‐Cut problems and approximation algorithms (2008) (1)
- AutoIP: A United Framework to Integrate Physics into Gaussian Processes (2022) (1)
- A new spin on an old algorithm: technical perspective (2014) (1)
- Best IVR Number Providers // 2019's Top IVR Number Software Solutions (2019) (0)
- Variational perspective on local graph clustering (2017) (0)
- The computational statistical mechanics of simple models of liquid water (2000) (0)
- ropensci/terrainr: terrainr v 0.5.0 (2021) (0)
- Check Toll Free and Local Number Portability in Asia (2019 Guide) (2018) (0)
- 07071 Report on Dagstuhl Seminar -- Web Information Retrieval and Linear Algebra Algorithms (2007) (0)
- Recent Advances in Randomized Numerical Linear Algebra (NII Shonan Meeting 2016-10) (2016) (0)
- ICML 2010 Tutorial: Geometric Tools for Identifying Structure in Large Social and Information Networks (2010) (0)
- An Empirical Exploration of Gradient Correlations in Deep Learning (2018) (0)
- Summary: Empirical Comparison of Algorithms for Network Community De- Tection. (2010) (2013) (0)
- Easily Obtain Spatial Data and Make Better Maps [R package spacey version 0.1.1] (2020) (0)
- Lower Extremity EMG during Stair Ascent Following TKA with Four Different Surgical Approaches (2010) (0)
- The Sky Above The Clouds (2022) (0)
- Unsupervised Learning Through Randomized Algorithms for High-Volume High-Velocity Data (ULTRA-HV). (2018) (0)
- Randomized Numerical Linear Algebra : A Perspective on the Field With an Eye to Software (2023) (0)
- Implant rachidien avec élément d'extension flexible (2010) (0)
- Forecasting Sequential Data Using Consistent Koopman Autoencoders — Supplementary Materials — (2020) (0)
- rCUR: an R package for CUR matrix (2012) (0)
- Second Order Machine Learning (2017) (0)
- Fast Feature Selection with Fairness Constraints (2022) (0)
- Running Alchemist on Cray XC and CS Series Supercomputers: Dask and PySpark Interfaces, Deployment Options, and Data Transfer Times (2019) (0)
- Scalable Matrix Algorithms for Interactive Analytics of Very Large Informatics Graphs (2017) (0)
- Web Information Retrieval and Linear Algebra Algorithms, 11.02. - 16.02.2007 (2007) (0)
- AVOXI Launches AVOXI Genius - A Cloud Contact Center Platform (2019) (0)
- AVOXI Continues Global Expansion With New Virtual Number Coverage in Asia-Pacific (2020) (0)
- D S ] 11 J ul 2 00 7 Sampling Algorithms and Coresets for l p Regression (2008) (0)
- Meeting: Algorithms for Modern Massive Data Sets (2008) (0)
- Low-Rank and Temporal Smoothness Regularization on Value-Based Deep Reinforcement Learning (2022) (0)
- SNPsand interpopulation genotype reconstruction from tagging (2007) (0)
- A Spectral Algorithm with Applications to Exploring Data Graphs Locally (2010) (0)
- Pre-surgical evaluation of mandibular third molars using computed tomography imaging and cone beam volumetric tomography imaging (2007) (0)
- Dynamic R Markdown Document Generation [R package heddlr version 0.6.0] (2020) (0)
- TIP5P and the reproduction on the density anomaly by simple potential functions (2000) (0)
- Principles and Applications of Science of Information (2017) (0)
- Clarke, Marieke, Mambo Hills: Historical and Religious Significance , with an introduction by Pathisa Nyathi, Bulawayo, ‘amaBooks, 2008, viii + 28 pp., map, bibliography, 978-0-7974-3589-6. (2010) (0)
- FLAG: Fast Linearly-Coupled Adaptive Gradient Method (2016) (0)
- Lecture 25 : Element-wise Sampling of Graphs and Linear Equation Solving , Cont (2015) (0)
- Implant pour arthrodèse (2007) (0)
- Bozzoli Belinda. Theatres of Struggle and the End of Apartheid . Athens: Ohio University Press/Oxford: James Currey Publishers, 2004. xvi + 326 pp. Photographs. Bibliography. Index. $28.95. Paper. (2005) (0)
- The Top 3 Toll Free Forwarding Providers // Best Toll Free Forwarding (2019) (0)
- FLAG n' FLARE: Fast Linearly-Coupled Adaptive Gradient Methods (2016) (0)
- Fixation stable en torsion (2007) (0)
- 07071 Abstracts Collection -- Web Information Retrieval and Linear Algebra Algorithms (2007) (0)
- Sparse Random Structures : Analysis and Computation January 24 – 29 , 2010 MEALS (2010) (0)
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