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
• 2021 : Acceleration and Stability of the Stochastic Proximal Point Algorithm »
  Junhyung Lyle Kim · Panos Toulis · Anastasios Kyrillidis
• 2021 : Acceleration and Stability of the Stochastic Proximal Point Algorithm »
  Junhyung Lyle Kim · Panos Toulis · Anastasios Kyrillidis
• 2022 : LOFT: Finding Lottery Tickets through Filter-wise Training »
  Qihan Wang · Chen Dun · Fangshuo Liao · Christopher Jermaine · Anastasios Kyrillidis
• 2022 : Strong Lottery Ticket Hypothesis with $\epsilon$–perturbation »
  Fangshuo Liao · Zheyang Xiong · Anastasios Kyrillidis
• 2022 : Strong Lottery Ticket Hypothesis with $\epsilon$–perturbation »
  Fangshuo Liao · Zheyang Xiong · Anastasios Kyrillidis
• 2022 : Efficient and Light-Weight Federated Learning via Asynchronous Distributed Dropout »
  Chen Dun · Mirian Hipolito Garcia · Dimitrios Dimitriadis · Christopher Jermaine · Anastasios Kyrillidis
• 2022 : GIST: Distributed Training for Large-Scale Graph Convolutional Networks »
  Cameron Wolfe · Jingkang Yang · Fangshuo Liao · Arindam Chowdhury · Chen Dun · Artun Bayer · Santiago Segarra · Anastasios Kyrillidis
• 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 Poster: ANODEV2: A Coupled Neural ODE Framework »
  Tianjun Zhang · Zhewei Yao · Amir Gholami · Joseph Gonzalez · Kurt Keutzer · Michael Mahoney · George Biros
• 2019 Poster: Learning Sparse Distributions using Iterative Hard Thresholding »
  Jacky Zhang · Rajiv Khanna · Anastasios Kyrillidis · Sanmi Koyejo
• 2019 Poster: DINGO: Distributed Newton-Type Method for Gradient-Norm Optimization »
  Rixon Crane · Fred Roosta
• 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
• 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 : Challenges in Multiresolution Methods for Graph-based Learning »
  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