Michael W. Mahoney

ORCID

Publication Activity (10 Years)

Years Active: 2003-2024
Publications (10 Years): 315

Top Venues

Publications

Yuchen Fang, Sen Na, Michael W. Mahoney, Mladen Kolar
Fully Stochastic Trust-Region Sequential Quadratic Programming for Equality-Constrained Optimization Problems. SIAM J. Optim. 34 (2) (2024)
Da Long, Wei W. Xing, Aditi S. Krishnapriyan, Robert M. Kirby, Shandian Zhe, Michael W. Mahoney
Equation Discovery with Bayesian Spike-and-Slab Priors and Efficient Kernels. AISTATS (2024)
Konstantin Schürholt, Michael W. Mahoney, Damian Borth
Towards Scalable and Versatile Weight Space Learning. CoRR (2024)
Nicholas Lee, Thanakul Wattanawong, Sehoon Kim, Karttikeya Mangalam, Sheng Shen, Gopala Anumanchipali, Michael W. Mahoney, Kurt Keutzer, Amir Gholami
LLM2LLM: Boosting LLMs with Novel Iterative Data Enhancement. CoRR (2024)
Abdul Fatir Ansari, Lorenzo Stella, Ali Caner Türkmen, Xiyuan Zhang, Pedro Mercado, Huibin Shen, Oleksandr Shchur, Syama Sundar Rangapuram, Sebastian Pineda-Arango, Shubham Kapoor, Jasper Zschiegner, Danielle C. Maddix, Michael W. Mahoney, Kari Torkkola, Andrew Gordon Wilson, Michael Bohlke-Schneider, Yuyang Wang
Chronos: Learning the Language of Time Series. CoRR (2024)
Michal Derezinski, Michael W. Mahoney
Recent and Upcoming Developments in Randomized Numerical Linear Algebra for Machine Learning. KDD (2024)
Annan Yu, Michael W. Mahoney, N. Benjamin Erichson
There is HOPE to Avoid HiPPOs for Long-memory State Space Models. CoRR (2024)
Pu Ren, Rie Nakata, Maxime Lacour, Ilan Naiman, Nori Nakata, Jialin Song, Zhengfa Bi, Osman Asif Malik, Dmitriy Morozov, Omri Azencot, N. Benjamin Erichson, Michael W. Mahoney
Learning Physics for Unveiling Hidden Earthquake Ground Motions via Conditional Generative Modeling. CoRR (2024)
Nicholas Lee, Thanakul Wattanawong, Sehoon Kim, Karttikeya Mangalam, Sheng Shen, Gopala Anumanchipalli, Michael W. Mahoney, Kurt Keutzer, Amir Gholami
LLM2LLM: Boosting LLMs with Novel Iterative Data Enhancement. ACL (Findings) (2024)
Tommaso Baldi, Javier Campos, Benjamin Hawks, Jennifer Ngadiuba, Nhan Tran, Daniel Diaz, Javier M. Duarte, Ryan Kastner, Andres Meza, Melissa Quinnan, Olivia Weng, Caleb Geniesse, Amir Gholami, Michael W. Mahoney, Vladimir Loncar, Philip C. Harris, Joshua Agar, Shuyu Qin
Reliable edge machine learning hardware for scientific applications. CoRR (2024)
Tommaso Baldi, Javier Campos, Benjamin Hawks, Jennifer Ngadiuba, Nhan Tran, Daniel Diaz, Javier M. Duarte, Ryan Kastner, Andres Meza, Melissa Quinnan, Olivia Weng, Caleb Geniesse, Amir Gholami, Michael W. Mahoney, Vladimir Loncar, Philip C. Harris, Joshua Agar, Shuyu Qin
Reliable edge machine learning hardware for scientific applications. VTS (2024)
Wuyang Chen, Jialin Song, Pu Ren, Shashank Subramanian, Dmitriy Morozov, Michael W. Mahoney
Data-Efficient Operator Learning via Unsupervised Pretraining and In-Context Learning. CoRR (2024)
Amir Gholami, Zhewei Yao, Sehoon Kim, Coleman Hooper, Michael W. Mahoney, Kurt Keutzer
AI and Memory Wall. IEEE Micro 44 (3) (2024)
Annan Yu, Arnur Nigmetov, Dmitriy Morozov, Michael W. Mahoney, N. Benjamin Erichson
Robustifying State-space Models for Long Sequences via Approximate Diagonalization. ICLR (2024)
Amir Gholami, Zhewei Yao, Sehoon Kim, Coleman Hooper, Michael W. Mahoney, Kurt Keutzer
AI and Memory Wall. CoRR (2024)
Ali Eshragh, Luke Yerbury, Asef Nazari, Fred Roosta, Michael W. Mahoney
SALSA: Sequential Approximate Leverage-Score Algorithm with Application in Analyzing Big Time Series Data. CoRR (2024)
Michal Derezinski, Michael W. Mahoney
Recent and Upcoming Developments in Randomized Numerical Linear Algebra for Machine Learning. CoRR (2024)
S. Chandra Mouli, Danielle C. Maddix, Shima Alizadeh, Gaurav Gupta, Andrew Stuart, Michael W. Mahoney, Yuyang Wang
Using Uncertainty Quantification to Characterize and Improve Out-of-Domain Learning for PDEs. CoRR (2024)
Dongwei Lyu, Rie Nakata, Pu Ren, Michael W. Mahoney, Arben Pitarka, Nori Nakata, N. Benjamin Erichson
WaveCastNet: An AI-enabled Wavefield Forecasting Framework for Earthquake Early Warning. CoRR (2024)
N. Benjamin Erichson, Soon Hoe Lim, Winnie Xu, Francisco Utrera, Ziang Cao, Michael W. Mahoney
NoisyMix: Boosting Model Robustness to Common Corruptions. AISTATS (2024)
Coleman Hooper, Sehoon Kim, Hiva Mohammadzadeh, Michael W. Mahoney, Yakun Sophia Shao, Kurt Keutzer, Amir Gholami
KVQuant: Towards 10 Million Context Length LLM Inference with KV Cache Quantization. CoRR (2024)
Haiquan Lu, Xiaotian Liu, Yefan Zhou, Qunli Li, Kurt Keutzer, Michael W. Mahoney, Yujun Yan, Huanrui Yang, Yaoqing Yang
Sharpness-diversity tradeoff: improving flat ensembles with SharpBalance. CoRR (2024)
Ilan Naiman, N. Benjamin Erichson, Pu Ren, Michael W. Mahoney, Omri Azencot
Generative Modeling of Regular and Irregular Time Series Data via Koopman VAEs. ICLR (2024)
Matthias Karlbauer, Danielle C. Maddix, Abdul Fatir Ansari, Boran Han, Gaurav Gupta, Yuyang Wang, Andrew Stuart, Michael W. Mahoney
Comparing and Contrasting Deep Learning Weather Prediction Backbones on Navier-Stokes and Atmospheric Dynamics. CoRR (2024)
Maksim Melnichenko, Oleg Balabanov, Riley Murray, James Demmel, Michael W. Mahoney, Piotr Luszczek
CholeskyQR with Randomization and Pivoting for Tall Matrices (CQRRPT). CoRR (2023)
Da Long, Wei W. Xing, Aditi S. Krishnapriyan, Robert M. Kirby, Shandian Zhe, Michael W. Mahoney
Equation Discovery with Bayesian Spike-and-Slab Priors and Efficient Kernels. CoRR (2023)
Javier Campos, Zhen Dong, Javier M. Duarte, Amir Gholami, Michael W. Mahoney, Jovan Mitrevski, Nhan Tran
End-to-end codesign of Hessian-aware quantized neural networks for FPGAs and ASICs. CoRR (2023)
Liam Hodgkinson, Christopher van der Heide, Robert Salomone, Fred Roosta, Michael W. Mahoney
The Interpolating Information Criterion for Overparameterized Models. CoRR (2023)
Yefan Zhou, Tianyu Pang, Keqin Liu, Charles H. Martin, Michael W. Mahoney, Yaoqing Yang
Temperature Balancing, Layer-wise Weight Analysis, and Neural Network Training. NeurIPS (2023)
Liam Hodgkinson, Christopher van der Heide, Robert Salomone, Fred Roosta, Michael W. Mahoney
A PAC-Bayesian Perspective on the Interpolating Information Criterion. CoRR (2023)
Derek Hansen, Danielle C. Maddix, Shima Alizadeh, Gaurav Gupta, Michael W. Mahoney
Learning Physical Models that Can Respect Conservation Laws. CoRR (2023)
Liam Hodgkinson, Christopher van der Heide, Fred Roosta, Michael W. Mahoney
Monotonicity and Double Descent in Uncertainty Estimation with Gaussian Processes. ICML (2023)
Pu Ren, N. Benjamin Erichson, Shashank Subramanian, Omer San, Zarija Lukic, Michael W. Mahoney
SuperBench: A Super-Resolution Benchmark Dataset for Scientific Machine Learning. CoRR (2023)
Yaoqing Yang, Ryan Theisen, Liam Hodgkinson, Joseph E. Gonzalez, Kannan Ramchandran, Charles H. Martin, Michael W. Mahoney
Test Accuracy vs. Generalization Gap: Model Selection in NLP without Accessing Training or Testing Data. KDD (2023)
Sehoon Kim, Suhong Moon, Ryan Tabrizi, Nicholas Lee, Michael W. Mahoney, Kurt Keutzer, Amir Gholami
An LLM Compiler for Parallel Function Calling. CoRR (2023)
Younghyun Cho, James Weldon Demmel, Michal Derezinski, Haoyun Li, Hengrui Luo, Michael W. Mahoney, Riley J. Murray
Surrogate-based Autotuning for Randomized Sketching Algorithms in Regression Problems. CoRR (2023)
Riley Murray, James Demmel, Michael W. Mahoney, N. Benjamin Erichson, Maksim Melnichenko, Osman Asif Malik, Laura Grigori, Piotr Luszczek, Michal Derezinski, Miles E. Lopes, Tianyu Liang, Hengrui Luo, Jack J. Dongarra
Randomized Numerical Linear Algebra : A Perspective on the Field With an Eye to Software. CoRR (2023)
Omar Eldaghar, Michael W. Mahoney, David F. Gleich
Multi-scale Local Network Structure Critically Impacts Epidemic Spread and Interventions. CoRR (2023)
Annan Yu, Arnur Nigmetov, Dmitriy Morozov, Michael W. Mahoney, N. Benjamin Erichson
Robustifying State-space Models for Long Sequences via Approximate Diagonalization. CoRR (2023)
Yefan Zhou, Yaoqing Yang, Arin Chang, Michael W. Mahoney
A Three-regime Model of Network Pruning. CoRR (2023)
Burlen Loring, E. Wes Bethel, Gunther H. Weber, Michael W. Mahoney
Extensions to the SENSEI In situ Framework for Heterogeneous Architectures. SC Workshops (2023)
Sehoon Kim, Coleman Hooper, Thanakul Wattanawong, Minwoo Kang, Ruohan Yan, Hasan Genc, Grace Dinh, Qijing Huang, Kurt Keutzer, Michael W. Mahoney, Yakun Sophia Shao, Amir Gholami
Full Stack Optimization of Transformer Inference: a Survey. CoRR (2023)
Yefan Zhou, Tianyu Pang, Keqin Liu, Charles H. Martin, Michael W. Mahoney, Yaoqing Yang
Temperature Balancing, Layer-wise Weight Analysis, and Neural Network Training. CoRR (2023)
Feynman T. Liang, Liam Hodgkinson, Michael W. Mahoney
A Heavy-Tailed Algebra for Probabilistic Programming. NeurIPS (2023)
Kimon Fountoulakis, Meng Liu, David F. Gleich, Michael W. Mahoney
Flow-Based Algorithms for Improving Clusters: A Unifying Framework, Software, and Performance. SIAM Rev. 65 (1) (2023)
Ilan Naiman, N. Benjamin Erichson, Pu Ren, Michael W. Mahoney, Omri Azencot
Generative Modeling of Regular and Irregular Time Series Data via Koopman VAEs. CoRR (2023)
Ryan Theisen, Hyunsuk Kim, Yaoqing Yang, Liam Hodgkinson, Michael W. Mahoney
When are ensembles really effective? CoRR (2023)
Ryan Theisen, Hyunsuk Kim, Yaoqing Yang, Liam Hodgkinson, Michael W. Mahoney
When are ensembles really effective? NeurIPS (2023)
Sen Na, Michal Derezinski, Michael W. Mahoney
Hessian averaging in stochastic Newton methods achieves superlinear convergence. Math. Program. 201 (1) (2023)
T. Konstantin Rusch, Benjamin Paul Chamberlain, Michael W. Mahoney, Michael M. Bronstein, Siddhartha Mishra
Gradient Gating for Deep Multi-Rate Learning on Graphs. ICLR (2023)
Sehoon Kim, Karttikeya Mangalam, Suhong Moon, Jitendra Malik, Michael W. Mahoney, Amir Gholami, Kurt Keutzer
Speculative Decoding with Big Little Decoder. NeurIPS (2023)
Ilgee Hong, Sen Na, Michael W. Mahoney, Mladen Kolar
Constrained Optimization via Exact Augmented Lagrangian and Randomized Iterative Sketching. ICML (2023)
Geoffrey Négiar, Michael W. Mahoney, Aditi S. Krishnapriyan
Learning differentiable solvers for systems with hard constraints. ICLR (2023)
Sehoon Kim, Coleman Hooper, Amir Gholami, Zhen Dong, Xiuyu Li, Sheng Shen, Michael W. Mahoney, Kurt Keutzer
SqueezeLLM: Dense-and-Sparse Quantization. CoRR (2023)
Derek Hansen, Danielle C. Maddix, Shima Alizadeh, Gaurav Gupta, Michael W. Mahoney
Learning Physical Models that Can Respect Conservation Laws. ICML (2023)
Shashank Subramanian, Peter Harrington, Kurt Keutzer, Wahid Bhimji, Dmitriy Morozov, Michael W. Mahoney, Amir Gholami
Towards Foundation Models for Scientific Machine Learning: Characterizing Scaling and Transfer Behavior. NeurIPS (2023)
Sehoon Kim, Karttikeya Mangalam, Jitendra Malik, Michael W. Mahoney, Amir Gholami, Kurt Keutzer
Big Little Transformer Decoder. CoRR (2023)
Yefan Zhou, Yaoqing Yang, Arin Chang, Michael W. Mahoney
A Three-regime Model of Network Pruning. ICML (2023)
Luis Oala, Manil Maskey, Lilith Bat-Leah, Alicia Parrish, Nezihe Merve Gürel, Tzu-Sheng Kuo, Yang Liu, Rotem Dror, Danilo Brajovic, Xiaozhe Yao, Max Bartolo, William Gaviria Rojas, Ryan Hileman, Rainier Aliment, Michael W. Mahoney, Meg Risdal, Matthew Lease, Wojciech Samek, Debojyoti Dutta, Curtis G. Northcutt, Cody Coleman, Braden Hancock, Bernard Koch, Girmaw Abebe Tadesse, Bojan Karlas, Ahmed Alaa, Adji Bousso Dieng, Natasha F. Noy, Vijay Janapa Reddi, James Zou, Praveen K. Paritosh, Mihaela van der Schaar, Kurt D. Bollacker, Lora Aroyo, Ce Zhang, Joaquin Vanschoren, Isabelle Guyon, Peter Mattson
DMLR: Data-centric Machine Learning Research - Past, Present and Future. CoRR (2023)
Feynman T. Liang, Liam Hodgkinson, Michael W. Mahoney
A Heavy-Tailed Algebra for Probabilistic Programming. CoRR (2023)
Burlen Loring, E. Wes Bethel, Gunther H. Weber, Michael W. Mahoney
Extensions to the SENSEI In situ Framework for Heterogeneous Architectures. CoRR (2023)
Sitan Yang, Malcolm Wolff, Shankar Ramasubramanian, Vincent Quenneville-Bélair, Ronak Metha, Michael W. Mahoney
GEANN: Scalable Graph Augmentations for Multi-Horizon Time Series Forecasting. CoRR (2023)
Francesco Quinzan, Rajiv Khanna, Moshik Hershcovitch, Sarel Cohen, Daniel G. Waddington, Tobias Friedrich, Michael W. Mahoney
Fast Feature Selection with Fairness Constraints. AISTATS (2023)
Geoffrey Négiar, Ruijun Ma, O. Nangba Meetei, Mengfei Cao, Michael W. Mahoney
Probabilistic Forecasting with Coherent Aggregation. CoRR (2023)
Shashank Subramanian, Robert M. Kirby, Michael W. Mahoney, Amir Gholami
Adaptive Self-Supervision Algorithms for Physics-Informed Neural Networks. ECAI (2023)
Ilgee Hong, Sen Na, Michael W. Mahoney, Mladen Kolar
Constrained Optimization via Exact Augmented Lagrangian and Randomized Iterative Sketching. CoRR (2023)
Shixing Yu, Zhewei Yao, Amir Gholami, Zhen Dong, Sehoon Kim, Michael W. Mahoney, Kurt Keutzer
Hessian-Aware Pruning and Optimal Neural Implant. WACV (2022)
Sarah Chasins, Alvin Cheung, Natacha Crooks, Ali Ghodsi, Ken Goldberg, Joseph E. Gonzalez, Joseph M. Hellerstein, Michael I. Jordan, Anthony D. Joseph, Michael W. Mahoney, Aditya G. Parameswaran, David A. Patterson, Raluca Ada Popa, Koushik Sen, Scott Shenker, Dawn Song, Ion Stoica
The Sky Above The Clouds. CoRR (2022)
Liam Hodgkinson, Umut Simsekli, Rajiv Khanna, Michael W. Mahoney
Generalization Bounds using Lower Tail Exponents in Stochastic Optimizers. ICML (2022)
Geoffrey Négiar, Michael W. Mahoney, Aditi S. Krishnapriyan
Learning differentiable solvers for systems with hard constraints. CoRR (2022)
Zhengming Zhang, Ashwinee Panda, Linyue Song, Yaoqing Yang, Michael W. Mahoney, Joseph E. Gonzalez, Kannan Ramchandran, Prateek Mittal
Neurotoxin: Durable Backdoors in Federated Learning. CoRR (2022)
Sehoon Kim, Amir Gholami, Zhewei Yao, Nicholas Lee, Patrick Wang, Aniruddha Nrusimha, Bohan Zhai, Tianren Gao, Michael W. Mahoney, Kurt Keutzer
Integer-Only Zero-Shot Quantization for Efficient Speech Recognition. ICASSP (2022)
Sen Na, Michael W. Mahoney
Asymptotic Convergence Rate and Statistical Inference for Stochastic Sequential Quadratic Programming. CoRR (2022)
Shashank Subramanian, Robert M. Kirby, Michael W. Mahoney, Amir Gholami
Adaptive Self-supervision Algorithms for Physics-informed Neural Networks. CoRR (2022)
Woosuk Kwon, Sehoon Kim, Michael W. Mahoney, Joseph Hassoun, Kurt Keutzer, Amir Gholami
A Fast Post-Training Pruning Framework for Transformers. NeurIPS (2022)
Sehoon Kim, Amir Gholami, Albert E. Shaw, Nicholas Lee, Karttikeya Mangalam, Jitendra Malik, Michael W. Mahoney, Kurt Keutzer
Squeezeformer: An Efficient Transformer for Automatic Speech Recognition. CoRR (2022)
T. Konstantin Rusch, Siddhartha Mishra, N. Benjamin Erichson, Michael W. Mahoney
Long Expressive Memory for Sequence Modeling. ICLR (2022)
Woosuk Kwon, Sehoon Kim, Michael W. Mahoney, Joseph Hassoun, Kurt Keutzer, Amir Gholami
A Fast Post-Training Pruning Framework for Transformers. CoRR (2022)
Da Long, Zheng Wang, Aditi S. Krishnapriyan, Robert M. Kirby, Shandian Zhe, Michael W. Mahoney
AutoIP: A United Framework to Integrate Physics into Gaussian Processes. CoRR (2022)
N. Benjamin Erichson, Soon Hoe Lim, Michael W. Mahoney
Gated Recurrent Neural Networks with Weighted Time-Delay Feedback. CoRR (2022)
T. Konstantin Rusch, Benjamin Paul Chamberlain, Michael W. Mahoney, Michael M. Bronstein, Siddhartha Mishra
Gradient Gating for Deep Multi-Rate Learning on Graphs. CoRR (2022)
Soon Hoe Lim, N. Benjamin Erichson, Francisco Utrera, Winnie Xu, Michael W. Mahoney
Noisy Feature Mixup. ICLR (2022)
Feynman T. Liang, Liam Hodgkinson, Michael W. Mahoney
Fat-Tailed Variational Inference with Anisotropic Tail Adaptive Flows. CoRR (2022)
Majid Jahani, Sergey Rusakov, Zheng Shi, Peter Richtárik, Michael W. Mahoney, Martin Takác
Doubly Adaptive Scaled Algorithm for Machine Learning Using Second-Order Information. ICLR (2022)
Feynman T. Liang, Michael W. Mahoney, Liam Hodgkinson
Fat-Tailed Variational Inference with Anisotropic Tail Adaptive Flows. ICML (2022)
Fred Roosta, Yang Liu, Peng Xu, Michael W. Mahoney
Newton-MR: Inexact Newton Method with minimum residual sub-problem solver. EURO J. Comput. Optim. 10 (2022)
Sen Na, Michal Derezinski, Michael W. Mahoney
Hessian Averaging in Stochastic Newton Methods Achieves Superlinear Convergence. CoRR (2022)
Ping Ma, Yongkai Chen, Xinlian Zhang, Xin Xing, Jingyi Ma, Michael W. Mahoney
Asymptotic Analysis of Sampling Estimators for Randomized Numerical Linear Algebra Algorithms. J. Mach. Learn. Res. 23 (2022)
Liam Hodgkinson, Christopher van der Heide, Fred Roosta, Michael W. Mahoney
Monotonicity and Double Descent in Uncertainty Estimation with Gaussian Processes. CoRR (2022)
Ali Eshragh, Fred Roosta, Asef Nazari, Michael W. Mahoney
LSAR: Efficient Leverage Score Sampling Algorithm for the Analysis of Big Time Series Data. J. Mach. Learn. Res. 23 (2022)
Yaoqing Yang, Ryan Theisen, Liam Hodgkinson, Joseph E. Gonzalez, Kannan Ramchandran, Charles H. Martin, Michael W. Mahoney
Evaluating natural language processing models with generalization metrics that do not need access to any training or testing data. CoRR (2022)
N. Benjamin Erichson, Soon Hoe Lim, Francisco Utrera, Winnie Xu, Ziang Cao, Michael W. Mahoney
NoisyMix: Boosting Robustness by Combining Data Augmentations, Stability Training, and Noise Injections. CoRR (2022)
Aditi S. Krishnapriyan, Alejandro F. Queiruga, N. Benjamin Erichson, Michael W. Mahoney
Learning continuous models for continuous physics. CoRR (2022)
Zhengming Zhang, Ashwinee Panda, Linyue Song, Yaoqing Yang, Michael W. Mahoney, Prateek Mittal, Kannan Ramchandran, Joseph Gonzalez
Neurotoxin: Durable Backdoors in Federated Learning. ICML (2022)
Sehoon Kim, Amir Gholami, Albert E. Shaw, Nicholas Lee, Karttikeya Mangalam, Jitendra Malik, Michael W. Mahoney, Kurt Keutzer
Squeezeformer: An Efficient Transformer for Automatic Speech Recognition. NeurIPS (2022)
Da Long, Zheng Wang, Aditi S. Krishnapriyan, Robert M. Kirby, Shandian Zhe, Michael W. Mahoney
AutoIP: A United Framework to Integrate Physics into Gaussian Processes. ICML (2022)
Francesco Quinzan, Rajiv Khanna, Moshik Hershcovitch, Sarel Cohen, Daniel G. Waddington, Tobias Friedrich, Michael W. Mahoney
Fast Feature Selection with Fairness Constraints. CoRR (2022)
Sheng Shen, Zhewei Yao, Douwe Kiela, Kurt Keutzer, Michael W. Mahoney
What's Hidden in a One-layer Randomly Weighted Transformer? EMNLP (1) (2021)
Yaoqing Yang, Liam Hodgkinson, Ryan Theisen, Joe Zou, Joseph E. Gonzalez, Kannan Ramchandran, Michael W. Mahoney
Taxonomizing local versus global structure in neural network loss landscapes. CoRR (2021)
Soon Hoe Lim, N. Benjamin Erichson, Liam Hodgkinson, Michael W. Mahoney
Noisy Recurrent Neural Networks. CoRR (2021)

Michael W. Mahoney.css-eqlu8i{font-size:small;padding-left:4px;}

Publication Activity (10 Years)

Top Topics

Top Venues

Michael W. Mahoney