More from the Same Authors

• 2021 Spotlight: Newton-LESS: Sparsification without Trade-offs for the Sketched Newton Update »
  Michal Derezinski · Jonathan Lacotte · Mert Pilanci · Michael Mahoney
• 2023 : Does In-Context Operator Learning Generalize to Domain-Shifted Settings? »
  Jerry Liu · N. Benjamin Erichson · Kush Bhatia · Michael Mahoney · Christopher Ré
• 2023 : Rapid Fitting of Band-Excitation Piezoresponse Force Microscopy Using Physics Constrained Unsupervised Neural Networks »
  Alibek T Kaliyev · Shuyu Qin · Yichen Guo · Seda Memik · Michael Mahoney · Amir Gholami · Nhan Tran · Martin Takac · Joshua Agar
• 2023 : A PAC-Bayesian Perspective on the Interpolating Information Criterion »
  Liam Hodgkinson · Chris van der Heide · Robert Salomone · Fred Roosta · Michael Mahoney
• 2023 Workshop: Heavy Tails in ML: Structure, Stability, Dynamics »
  Mert Gurbuzbalaban · Stefanie Jegelka · Michael Mahoney · Umut Simsekli
• 2023 Poster: Temperature Balancing, Layer-wise Weight Analysis, and Neural Network Training »
  Yefan Zhou · TIANYU PANG · Keqin Liu · charles martin · Michael Mahoney · Yaoqing Yang
• 2023 Poster: When are ensembles really effective? »
  Ryan Theisen · Hyunsuk Kim · Yaoqing Yang · Liam Hodgkinson · Michael Mahoney
• 2023 Poster: A Heavy-Tailed Algebra for Probabilistic Programming »
  Feynman Liang · Liam Hodgkinson · Michael Mahoney
• 2023 Poster: Speculative Decoding with Big Little Decoder »
  Sehoon Kim · Karttikeya Mangalam · Suhong Moon · Jitendra Malik · Michael Mahoney · Amir Gholami · Kurt Keutzer
• 2023 Poster: Towards Foundation Models for Scientific Machine Learning: Characterizing Scaling and Transfer Behavior »
  Shashank Subramanian · Peter Harrington · Kurt Keutzer · Wahid Bhimji · Dmitriy Morozov · Michael Mahoney · Amir Gholami
• 2023 Tutorial: Recent and Upcoming Developments in Randomized Numerical Linear Algebra for ML »
  Michal Derezinski · Michael Mahoney
• 2022 Poster: A Fast Post-Training Pruning Framework for Transformers »
  Woosuk Kwon · Sehoon Kim · Michael Mahoney · Joseph Hassoun · Kurt Keutzer · Amir Gholami
• 2022 Poster: Squeezeformer: An Efficient Transformer for Automatic Speech Recognition »
  Sehoon Kim · Amir Gholami · Albert Shaw · Nicholas Lee · Karttikeya Mangalam · Jitendra Malik · Michael Mahoney · Kurt Keutzer
• 2022 Poster: LSAR: Efficient Leverage Score Sampling Algorithm for the Analysis of Big Time Series Data »
  Ali Eshragh · Fred Roosta · Asef Nazari · Michael Mahoney
• 2021 : Q&A with Michael Mahoney »
  Michael Mahoney
• 2021 : Putting Randomized Matrix Algorithms in LAPACK, and Connections with Second-order Stochastic Optimization, Michael Mahoney »
  Michael Mahoney
• 2021 Poster: Newton-LESS: Sparsification without Trade-offs for the Sketched Newton Update »
  Michal Derezinski · Jonathan Lacotte · Mert Pilanci · Michael Mahoney
• 2021 Poster: Noisy Recurrent Neural Networks »
  Soon Hoe Lim · N. Benjamin Erichson · Liam Hodgkinson · Michael Mahoney
• 2021 Poster: Hessian Eigenspectra of More Realistic Nonlinear Models »
  Zhenyu Liao · Michael Mahoney
• 2021 Poster: Characterizing possible failure modes in physics-informed neural networks »
  Aditi Krishnapriyan · Amir Gholami · Shandian Zhe · Robert Kirby · Michael Mahoney
• 2021 Poster: Taxonomizing local versus global structure in neural network loss landscapes »
  Yaoqing Yang · Liam Hodgkinson · Ryan Theisen · Joe Zou · Joseph Gonzalez · Kannan Ramchandran · Michael Mahoney
• 2021 Poster: Stateful ODE-Nets using Basis Function Expansions »
  Alejandro Queiruga · N. Benjamin Erichson · Liam Hodgkinson · Michael Mahoney
• 2021 Oral: Hessian Eigenspectra of More Realistic Nonlinear Models »
  Zhenyu Liao · Michael Mahoney
• 2020 Poster: Boundary thickness and robustness in learning models »
  Yaoqing Yang · Rajiv Khanna · Yaodong Yu · Amir Gholami · Kurt Keutzer · Joseph Gonzalez · Kannan Ramchandran · Michael Mahoney
• 2020 Poster: Debiasing Distributed Second Order Optimization with Surrogate Sketching and Scaled Regularization »
  Michal Derezinski · Burak Bartan · Mert Pilanci · Michael Mahoney
• 2020 Poster: Exact expressions for double descent and implicit regularization via surrogate random design »
  Michal Derezinski · Feynman Liang · Michael Mahoney
• 2020 Poster: Improved guarantees and a multiple-descent curve for Column Subset Selection and the Nystrom method »
  Michal Derezinski · Rajiv Khanna · Michael Mahoney
• 2020 Poster: Precise expressions for random projections: Low-rank approximation and randomized Newton »
  Michal Derezinski · Feynman Liang · Zhenyu Liao · Michael Mahoney
• 2020 Oral: Improved guarantees and a multiple-descent curve for Column Subset Selection and the Nystrom method »
  Michal Derezinski · Rajiv Khanna · Michael Mahoney
• 2020 Poster: A random matrix analysis of random Fourier features: beyond the Gaussian kernel, a precise phase transition, and the corresponding double descent »
  Zhenyu Liao · Romain Couillet · Michael Mahoney
• 2020 Poster: A Statistical Framework for Low-bitwidth Training of Deep Neural Networks »
  Jianfei Chen · Yu Gai · Zhewei Yao · Michael Mahoney · Joseph Gonzalez
• 2019 : Final remarks »
  Anastasios Kyrillidis · Albert Berahas · Fred Roosta · Michael Mahoney
• 2019 Workshop: Beyond first order methods in machine learning systems »
  Anastasios Kyrillidis · Albert Berahas · Fred Roosta · Michael Mahoney
• 2019 : Opening Remarks »
  Anastasios Kyrillidis · Albert Berahas · Fred Roosta · Michael Mahoney
• 2019 Poster: ANODEV2: A Coupled Neural ODE Framework »
  Tianjun Zhang · Zhewei Yao · Amir Gholami · Joseph Gonzalez · Kurt Keutzer · Michael Mahoney · George Biros
• 2019 Poster: Distributed estimation of the inverse Hessian by determinantal averaging »
  Michal Derezinski · Michael Mahoney
• 2018 Poster: GIANT: Globally Improved Approximate Newton Method for Distributed Optimization »
  Shusen Wang · Fred Roosta · Peng Xu · Michael Mahoney
• 2018 Poster: Hessian-based Analysis of Large Batch Training and Robustness to Adversaries »
  Zhewei Yao · Amir Gholami · Qi Lei · Kurt Keutzer · Michael Mahoney
• 2017 Poster: Union of Intersections (UoI) for Interpretable Data Driven Discovery and Prediction »
  Kristofer Bouchard · Alejandro Bujan · Farbod Roosta-Khorasani · Shashanka Ubaru · Mr. Prabhat · Antoine Snijders · Jian-Hua Mao · Edward Chang · Michael W Mahoney · Sharmodeep Bhattacharya
• 2016 Poster: Feature-distributed sparse regression: a screen-and-clean approach »
  Jiyan Yang · Michael Mahoney · Michael Saunders · Yuekai Sun
• 2016 Poster: Sub-sampled Newton Methods with Non-uniform Sampling »
  Peng Xu · Jiyan Yang · Farbod Roosta-Khorasani · Christopher Ré · Michael Mahoney
• 2015 : Using Local Spectral Methods in Theory and in Practice »
  Michael Mahoney
• 2015 Poster: Fast Randomized Kernel Ridge Regression with Statistical Guarantees »
  Ahmed Alaoui · Michael Mahoney
• 2013 Workshop: Large Scale Matrix Analysis and Inference »
  Reza Zadeh · Gunnar Carlsson · Michael Mahoney · Manfred K. Warmuth · Wouter M Koolen · Nati Srebro · Satyen Kale · Malik Magdon-Ismail · Ashish Goel · Matei A Zaharia · David Woodruff · Ioannis Koutis · Benjamin Recht
• 2012 Poster: Semi-supervised Eigenvectors for Locally-biased Learning »
  Toke Jansen Hansen · Michael W Mahoney
• 2011 Workshop: Sparse Representation and Low-rank Approximation »
  Ameet S Talwalkar · Lester W Mackey · Mehryar Mohri · Michael W Mahoney · Francis Bach · Mike Davies · Remi Gribonval · Guillaume R Obozinski
• 2011 Poster: Regularized Laplacian Estimation and Fast Eigenvector Approximation »
  Patrick O Perry · Michael W Mahoney
• 2010 Workshop: Low-rank Methods for Large-scale Machine Learning »
  Arthur Gretton · Michael W Mahoney · Mehryar Mohri · Ameet S Talwalkar
• 2010 Poster: CUR from a Sparse Optimization Viewpoint »
  Jacob Bien · Ya Xu · Michael W Mahoney
• 2009 Poster: Unsupervised Feature Selection for the $k$-means Clustering Problem »
  Christos Boutsidis · Michael W Mahoney · Petros Drineas