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ORCIDMichael W. Mahoney
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- affiliation: University of California, Berkeley, Department of Statistics
- affiliation: Stanford University, Department of Mathematics
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2020 – today
- 2024
[j62]Amir Gholami
, Zhewei Yao, Sehoon Kim, Coleman Hooper, Michael W. Mahoney, Kurt Keutzer:
AI and Memory Wall. IEEE Micro 44(3): 33-39 (2024)- [j61]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): 2007-2037 (2024) - [c154]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: 6498-6526 - [c153]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: 2413-2421 - [c152]N. Benjamin Erichson, Soon Hoe Lim, Winnie Xu, Francisco Utrera, Ziang Cao, Michael W. Mahoney:
NoisyMix: Boosting Model Robustness to Common Corruptions. AISTATS 2024: 4033-4041 - [c151]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 - [c150]Annan Yu, Arnur Nigmetov, Dmitriy Morozov, Michael W. Mahoney, N. Benjamin Erichson:
Robustifying State-space Models for Long Sequences via Approximate Diagonalization. ICLR 2024 - [c149]Sehoon Kim, Coleman Hooper, Amir Gholami, Zhen Dong, Xiuyu Li, Sheng Shen, Michael W. Mahoney, Kurt Keutzer:
SqueezeLLM: Dense-and-Sparse Quantization. ICML 2024 - [c148]Sehoon Kim, Suhong Moon, Ryan Tabrizi, Nicholas Lee, Michael W. Mahoney, Kurt Keutzer, Amir Gholami:
An LLM Compiler for Parallel Function Calling. ICML 2024 - [c147]S. Chandra Mouli, Danielle C. Maddix, Shima Alizadeh, Gaurav Gupta, Andrew Stuart, Michael W. Mahoney, Bernie Wang:
Using Uncertainty Quantification to Characterize and Improve Out-of-Domain Learning for PDEs. ICML 2024 - [c146]Konstantin Schürholt, Michael W. Mahoney, Damian Borth:
Towards Scalable and Versatile Weight Space Learning. ICML 2024 - [c145]Michal Derezinski, Michael W. Mahoney:
Recent and Upcoming Developments in Randomized Numerical Linear Algebra for Machine Learning. KDD 2024: 6470-6479 - [c144]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: 1-5 - [i211]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 abs/2401.00122 (2024) - [i210]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 abs/2401.18079 (2024) - [i209]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 abs/2402.15734 (2024) - [i208]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 abs/2403.07815 (2024) - [i207]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 abs/2403.10642 (2024) - [i206]Amir Gholami, Zhewei Yao, Sehoon Kim, Coleman Hooper, Michael W. Mahoney, Kurt Keutzer:
AI and Memory Wall. CoRR abs/2403.14123 (2024) - [i205]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. CoRR abs/2403.15042 (2024) - [i204]Annan Yu, Michael W. Mahoney, N. Benjamin Erichson:
There is HOPE to Avoid HiPPOs for Long-memory State Space Models. CoRR abs/2405.13975 (2024) - [i203]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 abs/2405.20516 (2024) - [i202]Konstantin Schürholt, Michael W. Mahoney, Damian Borth:
Towards Scalable and Versatile Weight Space Learning. CoRR abs/2406.09997 (2024) - [i201]Michal Derezinski, Michael W. Mahoney:
Recent and Upcoming Developments in Randomized Numerical Linear Algebra for Machine Learning. CoRR abs/2406.11151 (2024) - [i200]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 abs/2406.19522 (2024) - [i199]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 abs/2407.12996 (2024) - [i198]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 abs/2407.14129 (2024) - [i197]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 abs/2407.15089 (2024) - 2023
- [j60]Sen Na, Michal Derezinski, Michael W. Mahoney:
Hessian averaging in stochastic Newton methods achieves superlinear convergence. Math. Program. 201(1): 473-520 (2023) - [j59]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): 59-143 (2023) - [c143]Francesco Quinzan, Rajiv Khanna, Moshik Hershcovitch, Sarel Cohen, Daniel G. Waddington, Tobias Friedrich, Michael W. Mahoney:
Fast Feature Selection with Fairness Constraints. AISTATS 2023: 7800-7823 - [c142]Shashank Subramanian, Robert M. Kirby, Michael W. Mahoney, Amir Gholami:
Adaptive Self-Supervision Algorithms for Physics-Informed Neural Networks. ECAI 2023: 2234-2241 - [c141]Geoffrey Négiar, Michael W. Mahoney, Aditi S. Krishnapriyan:
Learning differentiable solvers for systems with hard constraints. ICLR 2023 - [c140]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 - [c139]Derek Hansen, Danielle C. Maddix, Shima Alizadeh, Gaurav Gupta, Michael W. Mahoney:
Learning Physical Models that Can Respect Conservation Laws. ICML 2023: 12469-12510 - [c138]Liam Hodgkinson, Christopher van der Heide, Fred Roosta, Michael W. Mahoney:
Monotonicity and Double Descent in Uncertainty Estimation with Gaussian Processes. ICML 2023: 13085-13117 - [c137]Ilgee Hong, Sen Na, Michael W. Mahoney, Mladen Kolar:
Constrained Optimization via Exact Augmented Lagrangian and Randomized Iterative Sketching. ICML 2023: 13174-13198 - [c136]Yefan Zhou, Yaoqing Yang, Arin Chang, Michael W. Mahoney:
A Three-regime Model of Network Pruning. ICML 2023: 42790-42809 - [c135]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: 3011-3021 - [c134]Sehoon Kim, Karttikeya Mangalam, Suhong Moon, Jitendra Malik, Michael W. Mahoney, Amir Gholami, Kurt Keutzer:
Speculative Decoding with Big Little Decoder. NeurIPS 2023 - [c133]Feynman T. Liang, Liam Hodgkinson, Michael W. Mahoney:
A Heavy-Tailed Algebra for Probabilistic Programming. NeurIPS 2023 - [c132]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 - [c131]Ryan Theisen, Hyunsuk Kim, Yaoqing Yang, Liam Hodgkinson, Michael W. Mahoney:
When are ensembles really effective? NeurIPS 2023 - [c130]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 - [c129]Burlen Loring, E. Wes Bethel, Gunther H. Weber, Michael W. Mahoney:
Extensions to the SENSEI In situ Framework for Heterogeneous Architectures. SC Workshops 2023: 868-874 - [i196]Sehoon Kim, Karttikeya Mangalam, Jitendra Malik, Michael W. Mahoney, Amir Gholami, Kurt Keutzer:
Big Little Transformer Decoder. CoRR abs/2302.07863 (2023) - [i195]Derek Hansen, Danielle C. Maddix, Shima Alizadeh, Gaurav Gupta, Michael W. Mahoney:
Learning Physical Models that Can Respect Conservation Laws. CoRR abs/2302.11002 (2023) - [i194]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 abs/2302.11474 (2023) - [i193]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 abs/2302.14017 (2023) - [i192]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 abs/2304.06745 (2023) - [i191]Ryan Theisen, Hyunsuk Kim, Yaoqing Yang, Liam Hodgkinson, Michael W. Mahoney:
When are ensembles really effective? CoRR abs/2305.12313 (2023) - [i190]Ilgee Hong, Sen Na, Michael W. Mahoney, Mladen Kolar:
Constrained Optimization via Exact Augmented Lagrangian and Randomized Iterative Sketching. CoRR abs/2305.18379 (2023) - [i189]Yefan Zhou, Yaoqing Yang, Arin Chang, Michael W. Mahoney:
A Three-regime Model of Network Pruning. CoRR abs/2305.18383 (2023) - [i188]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. CoRR abs/2306.00258 (2023) - [i187]Sehoon Kim, Coleman Hooper, Amir Gholami, Zhen Dong, Xiuyu Li, Sheng Shen, Michael W. Mahoney, Kurt Keutzer:
SqueezeLLM: Dense-and-Sparse Quantization. CoRR abs/2306.07629 (2023) - [i186]Feynman T. Liang, Liam Hodgkinson, Michael W. Mahoney:
A Heavy-Tailed Algebra for Probabilistic Programming. CoRR abs/2306.09262 (2023) - [i185]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 abs/2306.14070 (2023) - [i184]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 abs/2307.03595 (2023) - [i183]Liam Hodgkinson, Christopher van der Heide, Robert Salomone, Fred Roosta, Michael W. Mahoney:
The Interpolating Information Criterion for Overparameterized Models. CoRR abs/2307.07785 (2023) - [i182]Geoffrey Négiar, Ruijun Ma, O. Nangba Meetei, Mengfei Cao, Michael W. Mahoney:
Probabilistic Forecasting with Coherent Aggregation. CoRR abs/2307.09797 (2023) - [i181]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 abs/2308.15720 (2023) - [i180]Annan Yu, Arnur Nigmetov, Dmitriy Morozov, Michael W. Mahoney, N. Benjamin Erichson:
Robustifying State-space Models for Long Sequences via Approximate Diagonalization. CoRR abs/2310.01698 (2023) - [i179]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 abs/2310.02619 (2023) - [i178]Burlen Loring, E. Wes Bethel, Gunther H. Weber, Michael W. Mahoney:
Extensions to the SENSEI In situ Framework for Heterogeneous Architectures. CoRR abs/2310.02926 (2023) - [i177]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 abs/2310.05387 (2023) - [i176]Liam Hodgkinson, Christopher van der Heide, Robert Salomone, Fred Roosta, Michael W. Mahoney:
A PAC-Bayesian Perspective on the Interpolating Information Criterion. CoRR abs/2311.07013 (2023) - [i175]Maksim Melnichenko, Oleg Balabanov, Riley Murray, James Demmel, Michael W. Mahoney, Piotr Luszczek:
CholeskyQR with Randomization and Pivoting for Tall Matrices (CQRRPT). CoRR abs/2311.08316 (2023) - [i174]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 M. 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 abs/2311.13028 (2023) - [i173]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 abs/2312.00359 (2023) - [i172]Sehoon Kim, Suhong Moon, Ryan Tabrizi, Nicholas Lee, Michael W. Mahoney, Kurt Keutzer, Amir Gholami:
An LLM Compiler for Parallel Function Calling. CoRR abs/2312.04511 (2023) - [i171]Omar Eldaghar, Michael W. Mahoney, David F. Gleich:
Multi-scale Local Network Structure Critically Impacts Epidemic Spread and Interventions. CoRR abs/2312.17351 (2023) - 2022
- [j58]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: 100035 (2022) - [j57]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: 22:1-22:36 (2022) - [j56]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: 177:1-177:45 (2022) - [c128]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: 4288-4292 - [c127]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 - [c126]Soon Hoe Lim, N. Benjamin Erichson, Francisco Utrera, Winnie Xu, Michael W. Mahoney:
Noisy Feature Mixup. ICLR 2022 - [c125]T. Konstantin Rusch, Siddhartha Mishra, N. Benjamin Erichson, Michael W. Mahoney:
Long Expressive Memory for Sequence Modeling. ICLR 2022 - [c124]Liam Hodgkinson, Umut Simsekli, Rajiv Khanna, Michael W. Mahoney:
Generalization Bounds using Lower Tail Exponents in Stochastic Optimizers. ICML 2022: 8774-8795 - [c123]Feynman T. Liang, Michael W. Mahoney, Liam Hodgkinson:
Fat-Tailed Variational Inference with Anisotropic Tail Adaptive Flows. ICML 2022: 13257-13270 - [c122]Xiaoxuan Liu, Lianmin Zheng, Dequan Wang, Yukuo Cen, Weize Chen, Xu Han, Jianfei Chen, Zhiyuan Liu, Jie Tang, Joey Gonzalez, Michael W. Mahoney, Alvin Cheung:
GACT: Activation Compressed Training for Generic Network Architectures. ICML 2022: 14139-14152 - [c121]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: 14210-14222 - [c120]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: 26429-26446 - [c119]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 - [c118]Woosuk Kwon, Sehoon Kim, Michael W. Mahoney, Joseph Hassoun, Kurt Keutzer, Amir Gholami:
A Fast Post-Training Pruning Framework for Transformers. NeurIPS 2022 - [c117]Shixing Yu, Zhewei Yao, Amir Gholami, Zhen Dong, Sehoon Kim, Michael W. Mahoney, Kurt Keutzer:
Hessian-Aware Pruning and Optimal Neural Implant. WACV 2022: 3665-3676 - [i170]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 abs/2202.01263 (2022) - [i169]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 abs/2202.02842 (2022) - [i168]Aditi S. Krishnapriyan, Alejandro F. Queiruga, N. Benjamin Erichson, Michael W. Mahoney:
Learning continuous models for continuous physics. CoRR abs/2202.08494 (2022) - [i167]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 abs/2202.12316 (2022) - [i166]Francesco Quinzan, Rajiv Khanna, Moshik Hershcovitch, Sarel Cohen, Daniel G. Waddington, Tobias Friedrich, Michael W. Mahoney:
Fast Feature Selection with Fairness Constraints. CoRR abs/2202.13718 (2022) - [i165]Sen Na, Michal Derezinski, Michael W. Mahoney:
Hessian Averaging in Stochastic Newton Methods Achieves Superlinear Convergence. CoRR abs/2204.09266 (2022) - [i164]Woosuk Kwon, Sehoon Kim, Michael W. Mahoney, Joseph Hassoun, Kurt Keutzer, Amir Gholami:
A Fast Post-Training Pruning Framework for Transformers. CoRR abs/2204.09656 (2022) - [i163]Sarah E. 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 abs/2205.07147 (2022) - [i162]Feynman T. Liang, Liam Hodgkinson, Michael W. Mahoney:
Fat-Tailed Variational Inference with Anisotropic Tail Adaptive Flows. CoRR abs/2205.07918 (2022) - [i161]Sen Na, Michael W. Mahoney:
Asymptotic Convergence Rate and Statistical Inference for Stochastic Sequential Quadratic Programming. CoRR abs/2205.13687 (2022) - [i160]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 abs/2206.00888 (2022) - [i159]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 abs/2206.10341 (2022) - [i158]Xiaoxuan Liu, Lianmin Zheng, Dequan Wang, Yukuo Cen, Weize Chen, Xu Han, Jianfei Chen, Zhiyuan Liu, Jie Tang, Joey Gonzalez, Michael W. Mahoney, Alvin Cheung:
GACT: Activation Compressed Training for General Architectures. CoRR abs/2206.11357 (2022) - [i157]Shashank Subramanian, Robert M. Kirby, Michael W. Mahoney, Amir Gholami:
Adaptive Self-supervision Algorithms for Physics-informed Neural Networks. CoRR abs/2207.04084 (2022) - [i156]Geoffrey Négiar, Michael W. Mahoney, Aditi S. Krishnapriyan:
Learning differentiable solvers for systems with hard constraints. CoRR abs/2207.08675 (2022) - [i155]T. Konstantin Rusch, Benjamin Paul Chamberlain, Michael W. Mahoney, Michael M. Bronstein, Siddhartha Mishra:
Gradient Gating for Deep Multi-Rate Learning on Graphs. CoRR abs/2210.00513 (2022) - [i154]Liam Hodgkinson, Christopher van der Heide, Fred Roosta, Michael W. Mahoney:
Monotonicity and Double Descent in Uncertainty Estimation with Gaussian Processes. CoRR abs/2210.07612 (2022) - [i153]N. Benjamin Erichson, Soon Hoe Lim, Michael W. Mahoney:
Gated Recurrent Neural Networks with Weighted Time-Delay Feedback. CoRR abs/2212.00228 (2022) - 2021
- [j55]Zhewei Yao, Peng Xu, Fred Roosta, Michael W. Mahoney:
Inexact Nonconvex Newton-Type Methods. INFORMS J. Optim. 3(2): 154-182 (2021) - [j54]Wooseok Ha, Kimon Fountoulakis, Michael W. Mahoney:
Statistical guarantees for local graph clustering. J. Mach. Learn. Res. 22: 148:1-148:54 (2021) - [j53]Charles H. Martin, Michael W. Mahoney:
Implicit Self-Regularization in Deep Neural Networks: Evidence from Random Matrix Theory and Implications for Learning. J. Mach. Learn. Res. 22: 165:1-165:73 (2021) - [j52]Keith D. Levin, Fred Roosta, Minh Tang, Michael W. Mahoney, Carey E. Priebe:
Limit theorems for out-of-sample extensions of the adjacency and Laplacian spectral embeddings. J. Mach. Learn. Res. 22: 194:1-194:59 (2021) - [j51]Swapnil Das, James Demmel, Kimon Fountoulakis, Laura Grigori, Michael W. Mahoney, Shenghao Yang:
Parallel and Communication Avoiding Least Angle Regression. SIAM J. Sci. Comput. 43(2): C154-C176 (2021) - [c116]Zhewei Yao, Amir Gholami, Sheng Shen, Mustafa Mustafa, Kurt Keutzer, Michael W. Mahoney:
ADAHESSIAN: An Adaptive Second Order Optimizer for Machine Learning. AAAI 2021: 10665-10673 - [c115]Ryan Theisen, Jason M. Klusowski, Michael W. Mahoney:
Good Classifiers are Abundant in the Interpolating Regime. AISTATS 2021: 3376-3384 - [c114]