Amir Gholami

Publication Activity (10 Years)

Years Active: 2014-2024
Publications (10 Years): 94

Top Topics

Power Distribution

Top Venues

Publications

Mehdi Ganjkhani, Amir Gholami, Jairo Giraldo, Anurag K. Srivastava, Masood Parvania
Multi-Source Data Aggregation and Real-Time Anomaly Classification and Localization in Power Distribution Systems. IEEE Trans. Smart Grid 15 (2) (2024)
Siddharth Jha, Lutfi Eren Erdogan, Sehoon Kim, Kurt Keutzer, Amir Gholami
Characterizing Prompt Compression Methods for Long Context Inference. 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)
Amir Gholami, Anurag Srivastava
ORCA: Outage Root Cause Analysis in DER-Rich Power Distribution System Using Data Fusion, Hierarchical Clustering and FP-Growth Rule Mining. IEEE Trans. Smart Grid 15 (1) (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)
Arman Ahmed, Sagnik Basumallik, Amir Gholami, Sajan K. Sadanandan, Mohammad Hossein Namaki, Anurag K. Srivastava, Yinghui Wu
Spatio-Temporal Deep Graph Network for Event Detection, Localization, and Classification in Cyber-Physical Electric Distribution System. IEEE Trans. Ind. Informatics 20 (2) (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)
Amir Gholami, Zhewei Yao, Sehoon Kim, Coleman Hooper, Michael W. Mahoney, Kurt Keutzer
AI and Memory Wall. IEEE Micro 44 (3) (2024)
Allison McCarn Deiana, Nhan Tran, Joshua Agar, Michaela Blott, Giuseppe Di Guglielmo, Javier M. Duarte, Philip C. Harris, Scott Hauck, Mia Liu, Mark S. Neubauer, Jennifer Ngadiuba, Seda Ogrenci-Memik, Maurizio Pierini, Thea Aarrestad, Steffen Bähr, Jürgen Becker, Anne-Sophie Berthold, Richard J. Bonventre, Tomás E. Müller-Bravo, Markus Diefenthaler, Zhen Dong, Nick Fritzsche, Amir Gholami, Ekaterina Govorkova, Dongning Guo, Kyle J. Hazelwood, Christian Herwig, Babar Khan, Sehoon Kim, Thomas Klijnsma, Yaling Liu, Kin Ho Lo, Tri Nguyen, Gianantonio Pezzullo, Seyedramin Rasoulinezhad, Ryan A. Rivera, Kate Scholberg, Justin Selig, Sougata Sen, Dmitri Strukov, William Tang, Savannah Thais, Kai Lukas Unger, Ricardo Vilalta, Belinavon Krosigk, Shen Wang, Thomas K. Warburton
Corrigendum: Applications and techniques for fast machine learning in science. Frontiers Big Data 6 (2024)
Amir Gholami, Zhewei Yao, Sehoon Kim, Coleman Hooper, Michael W. Mahoney, Kurt Keutzer
AI and Memory Wall. CoRR (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)
Amir Gholami, Ashutosh Tiwari, Chuan Qin, Sanjeev Pannala, Anurag Srivastava, Roshan Sharma, Shikhar Pandey, Farnoosh Rahmatian
Detection and Classification of Anomalies in Power Distribution System Using Outlier Filtered Weighted Least Square. IEEE Trans. Ind. Informatics 20 (5) (2024)
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)
Coleman Hooper, Sehoon Kim, Hiva Mohammadzadeh, Hasan Genc, Kurt Keutzer, Amir Gholami, Yakun Sophia Shao
SPEED: Speculative Pipelined Execution for Efficient Decoding. CoRR (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)
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)
Shashank Subramanian, Peter Harrington, Kurt Keutzer, Wahid Bhimji, Dmitriy Morozov, Michael Mahoney, Amir Gholami
Towards Foundation Models for Scientific Machine Learning: Characterizing Scaling and Transfer Behavior. CoRR (2023)
Sehoon Kim, Karttikeya Mangalam, Suhong Moon, Jitendra Malik, Michael W. Mahoney, Amir Gholami, Kurt Keutzer
Speculative Decoding with Big Little Decoder. NeurIPS (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)
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)
Shashank Subramanian, Robert M. Kirby, Michael W. Mahoney, Amir Gholami
Adaptive Self-Supervision Algorithms for Physics-Informed Neural Networks. ECAI (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)
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)
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)
Woosuk Kwon, Sehoon Kim, Michael W. Mahoney, Joseph Hassoun, Kurt Keutzer, Amir Gholami
A Fast Post-Training Pruning Framework for Transformers. CoRR (2022)
Neda Kaffash-Charandabi, Amir Gholami, Ali Abdollahzadeh Bina
Road accident risk prediction using generalized regression neural network optimized with self-organizing map. Neural Comput. Appl. 34 (11) (2022)
Allison McCarn Deiana, Nhan Tran, Joshua Agar, Michaela Blott, Giuseppe Di Guglielmo, Javier M. Duarte, Philip C. Harris, Scott Hauck, Mia Liu, Mark S. Neubauer, Jennifer Ngadiuba, Seda Ogrenci Memik, Maurizio Pierini, Thea Aarrestad, Steffen Bähr, Jürgen Becker, Anne-Sophie Berthold, Richard J. Bonventre, Tomás E. Müller-Bravo, Markus Diefenthaler, Zhen Dong, Nick Fritzsche, Amir Gholami, Ekaterina Govorkova, Dongning Guo, Kyle J. Hazelwood, Christian Herwig, Babar Khan, Sehoon Kim, Thomas Klijnsma, Yaling Liu, Kin Ho Lo, Tri Nguyen, Gianantonio Pezzullo, Seyedramin Rasoulinezhad, Ryan A. Rivera, Kate Scholberg, Justin Selig, Sougata Sen, Dmitri Strukov, William Tang, Savannah Thais, Kai Lukas Unger, Ricardo Vilalta, Belinavon Krosigk, Shen Wang, Thomas K. Warburton
Applications and Techniques for Fast Machine Learning in Science. Frontiers Big Data 5 (2022)
Sehoon Kim, Sheng Shen, David Thorsley, Amir Gholami, Woosuk Kwon, Joseph Hassoun, Kurt Keutzer
Learned Token Pruning for Transformers. KDD (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)
Amirkhosro Vosughi, Amir Gholami, Anurag K. Srivastava
Denoising and Bad Data Detection in Distribution Phasor Measurements using Filtering, Clustering and Koopman Mode Analysis. IAS (2021)
Zhewei Yao, Zhen Dong, Zhangcheng Zheng, Amir Gholami, Jiali Yu, Eric Tan, Leyuan Wang, Qijing Huang, Yida Wang, Michael W. Mahoney, Kurt Keutzer
HAWQ-V3: Dyadic Neural Network Quantization. ICML (2021)
Allison McCarn Deiana, Nhan Tran, Joshua Agar, Michaela Blott, Giuseppe Di Guglielmo, Javier M. Duarte, Philip C. Harris, Scott Hauck, Mia Liu, Mark S. Neubauer, Jennifer Ngadiuba, Seda Ogrenci Memik, Maurizio Pierini, Thea Aarrestad, Steffen Bähr, Jürgen Becker, Anne-Sophie Berthold, Richard J. Bonventre, Tomas E. Muller Bravo, Markus Diefenthaler, Zhen Dong, Nick Fritzsche, Amir Gholami, Ekaterina Govorkova, Kyle J. Hazelwood, Christian Herwig, Babar Khan, Sehoon Kim, Thomas Klijnsma, Yaling Liu, Kin Ho Lo, Tri Nguyen, Gianantonio Pezzullo, SeyedRamin Rasoulinezhad, Ryan A. Rivera, Kate Scholberg, Justin Selig, Sougata Sen, Dmitri Strukov, William Tang, Savannah Thais, Kai Lukas Unger, Ricardo Vilalta, Belinavon Krosigk, Thomas K. Warburton, Maria Acosta Flechas, Anthony Aportela, Thomas Calvet, Leonardo Cristella, Daniel Diaz, Caterina Doglioni, Maria Domenica Galati, Elham E Khoda, Farah Fahim, Davide Giri, Benjamin Hawks, Duc Hoang, Burt Holzman, Shih-Chieh Hsu, Sergo Jindariani, Iris Johnson, Raghav Kansal, Ryan Kastner, Erik Katsavounidis, Jeffrey Krupa, Pan Li, Sandeep Madireddy, Ethan Marx, Patrick McCormack, Andres Meza, Jovan Mitrevski, Mohammed Attia Mohammed, Farouk Mokhtar, Eric Moreno, Srishti Nagu, Rohin Narayan, Noah Palladino, Zhiqiang Que, Sang Eon Park, Subramanian Ramamoorthy, Dylan Rankin, Simon Rothman, Ashish Sharma, Sioni Summers, Pietro Vischia, Jean-Roch Vlimant, Olivia Weng
Applications and Techniques for Fast Machine Learning in Science. CoRR (2021)
Sehoon Kim, Amir Gholami, Zhewei Yao, Aniruddha Nrusimha, Bohan Zhai, Tianren Gao, Michael W. Mahoney, Kurt Keutzer
Q-ASR: Integer-only Zero-shot Quantization for Efficient Speech Recognition. CoRR (2021)
Amir Gholami, Sehoon Kim, Zhen Dong, Zhewei Yao, Michael W. Mahoney, Kurt Keutzer
A Survey of Quantization Methods for Efficient Neural Network Inference. CoRR (2021)
Sehoon Kim, Amir Gholami, Zhewei Yao, Michael W. Mahoney, Kurt Keutzer
I-BERT: Integer-only BERT Quantization. ICML (2021)
Aditi S. Krishnapriyan, Amir Gholami, Shandian Zhe, Robert M. Kirby, Michael W. Mahoney
Characterizing possible failure modes in physics-informed neural networks. CoRR (2021)
Shixing Yu, Zhewei Yao, Amir Gholami, Zhen Dong, Michael W. Mahoney, Kurt Keutzer
Hessian-Aware Pruning and Optimal Neural Implant. CoRR (2021)
Sehoon Kim, Amir Gholami, Zhewei Yao, Michael W. Mahoney, Kurt Keutzer
I-BERT: Integer-only BERT Quantization. CoRR (2021)
Sehoon Kim, Sheng Shen, David Thorsley, Amir Gholami, Joseph Hassoun, Kurt Keutzer
Learned Token Pruning for Transformers. CoRR (2021)
Aditi S. Krishnapriyan, Amir Gholami, Shandian Zhe, Robert M. Kirby, Michael W. Mahoney
Characterizing possible failure modes in physics-informed neural networks. NeurIPS (2021)
Zhewei Yao, Amir Gholami, Sheng Shen, Mustafa Mustafa, Kurt Keutzer, Michael W. Mahoney
ADAHESSIAN: An Adaptive Second Order Optimizer for Machine Learning. AAAI (2021)
Yaohui Cai, Zhewei Yao, Zhen Dong, Amir Gholami, Michael W. Mahoney, Kurt Keutzer
ZeroQ: A Novel Zero Shot Quantization Framework. CVPR (2020)
Yaoqing Yang, Rajiv Khanna, Yaodong Yu, Amir Gholami, Kurt Keutzer, Joseph E. Gonzalez, Kannan Ramchandran, Michael W. Mahoney
Boundary thickness and robustness in learning models. CoRR (2020)
Zhen Dong, Zhewei Yao, Daiyaan Arfeen, Amir Gholami, Michael W. Mahoney, Kurt Keutzer
HAWQ-V2: Hessian Aware trace-Weighted Quantization of Neural Networks. NeurIPS (2020)
Linjian Ma, Gabe Montague, Jiayu Ye, Zhewei Yao, Amir Gholami, Kurt Keutzer, Michael W. Mahoney
Inefficiency of K-FAC for Large Batch Size Training. AAAI (2020)
Zhewei Yao, Amir Gholami, Kurt Keutzer, Michael W. Mahoney
PyHessian: Neural Networks Through the Lens of the Hessian. IEEE BigData (2020)
Zhewei Yao, Zhen Dong, Zhangcheng Zheng, Amir Gholami, Jiali Yu, Eric Tan, Leyuan Wang, Qijing Huang, Yida Wang, Michael W. Mahoney, Kurt Keutzer
HAWQV3: Dyadic Neural Network Quantization. CoRR (2020)
Yaohui Cai, Zhewei Yao, Zhen Dong, Amir Gholami, Michael W. Mahoney, Kurt Keutzer
ZeroQ: A Novel Zero Shot Quantization Framework. CoRR (2020)
Sheng Shen, Zhewei Yao, Amir Gholami, Michael W. Mahoney, Kurt Keutzer
PowerNorm: Rethinking Batch Normalization in Transformers. ICML (2020)
Paras Jain, Ajay Jain, Aniruddha Nrusimha, Amir Gholami, Pieter Abbeel, Kurt Keutzer, Ion Stoica, Joseph Gonzalez
Checkmate: Breaking the Memory Wall with Optimal Tensor Rematerialization. MLSys (2020)
Sheng Shen, Zhen Dong, Jiayu Ye, Linjian Ma, Zhewei Yao, Amir Gholami, Michael W. Mahoney, Kurt Keutzer
Q-BERT: Hessian Based Ultra Low Precision Quantization of BERT. AAAI (2020)
Zhewei Yao, Amir Gholami, Sheng Shen, Kurt Keutzer, Michael W. Mahoney
ADAHESSIAN: An Adaptive Second Order Optimizer for Machine Learning. CoRR (2020)
Sheng Shen, Zhewei Yao, Amir Gholami, Michael W. Mahoney, Kurt Keutzer
Rethinking Batch Normalization in Transformers. CoRR (2020)
Yaoqing Yang, Rajiv Khanna, Yaodong Yu, Amir Gholami, Kurt Keutzer, Joseph E. Gonzalez, Kannan Ramchandran, Michael W. Mahoney
Boundary thickness and robustness in learning models. NeurIPS (2020)
Andreas Mang, Amir Gholami, Christos Davatzikos, George Biros
CLAIRE: A Distributed-Memory Solver for Constrained Large Deformation Diffeomorphic Image Registration. SIAM J. Sci. Comput. 41 (5) (2019)
Tianjun Zhang, Zhewei Yao, Amir Gholami, Kurt Keutzer, Joseph Gonzalez, George Biros, Michael W. Mahoney
ANODEV2: A Coupled Neural ODE Evolution Framework. CoRR (2019)
Zhen Dong, Zhewei Yao, Amir Gholami, Michael W. Mahoney, Kurt Keutzer
HAWQ: Hessian AWare Quantization of Neural Networks With Mixed-Precision. ICCV (2019)
Amir Gholami, Alireza Sahab, Abdolreza Tavakoli, Behnam Alizadeh
A novel LMI-based robust model predictive control for DFIG-based wind energy conversion systems. Kybernetika 55 (6) (2019)
Linjian Ma, Gabe Montague, Jiayu Ye, Zhewei Yao, Amir Gholami, Kurt Keutzer, Michael W. Mahoney
Inefficiency of K-FAC for Large Batch Size Training. CoRR (2019)
Amir Gholami, Milad Moradi, Majid Majidi
A Simulation Platform Design and Kinematics Analysis of MRL-HSL Humanoid Robot. RoboCup (2019)
Sheng Shen, Zhen Dong, Jiayu Ye, Linjian Ma, Zhewei Yao, Amir Gholami, Michael W. Mahoney, Kurt Keutzer
Q-BERT: Hessian Based Ultra Low Precision Quantization of BERT. CoRR (2019)
Zhewei Yao, Amir Gholami, Peng Xu, Kurt Keutzer, Michael W. Mahoney
Trust Region Based Adversarial Attack on Neural Networks. CVPR (2019)
Hamed Mahmudi, Amir Gholami, Mohammad Hossein Delavaran, Soheil Khatibi, Saeid Bazargan, Milad Moradi, Bita Alaee, Arash Rahmani, Kazem Firouzmandi Bandpey, Peyman Fallahzadeh, Meisam Teimouri
MRL Champion Team Paper in Humanoid TeenSize League of RoboCup 2019. RoboCup (2019)
Amir Gholami, Kurt Keutzer, George Biros
ANODE: Unconditionally Accurate Memory-Efficient Gradients for Neural ODEs. CoRR (2019)
Zhen Dong, Zhewei Yao, Yaohui Cai, Daiyaan Arfeen, Amir Gholami, Michael W. Mahoney, Kurt Keutzer
HAWQ-V2: Hessian Aware trace-Weighted Quantization of Neural Networks. CoRR (2019)
Tianjun Zhang, Zhewei Yao, Amir Gholami, Joseph E. Gonzalez, Kurt Keutzer, Michael W. Mahoney, George Biros
ANODEV2: A Coupled Neural ODE Framework. NeurIPS (2019)
Zhen Dong, Zhewei Yao, Amir Gholami, Michael W. Mahoney, Kurt Keutzer
HAWQ: Hessian AWare Quantization of Neural Networks with Mixed-Precision. CoRR (2019)
Paras Jain, Ajay Jain, Aniruddha Nrusimha, Amir Gholami, Pieter Abbeel, Kurt Keutzer, Ion Stoica, Joseph E. Gonzalez
Checkmate: Breaking the Memory Wall with Optimal Tensor Rematerialization. CoRR (2019)
Alon Amid, Kiseok Kwon, Amir Gholami, Bichen Wu, Krste Asanovic, Kurt Keutzer
Co-design of deep neural nets and neural net accelerators for embedded vision applications. IBM J. Res. Dev. 63 (6) (2019)
Zhewei Yao, Amir Gholami, Kurt Keutzer, Michael W. Mahoney
PyHessian: Neural Networks Through the Lens of the Hessian. CoRR (2019)
Andreas Mang, Amir Gholami, Christos Davatzikos, George Biros
PDE-constrained optimization in medical image analysis. CoRR (2018)
Andreas Mang, Amir Gholami, Christos Davatzikos, George Biros
CLAIRE: A distributed-memory solver for constrained large deformation diffeomorphic image registration. CoRR (2018)
Zhewei Yao, Amir Gholami, Kurt Keutzer, Michael W. Mahoney
Large batch size training of neural networks with adversarial training and second-order information. CoRR (2018)
Kiseok Kwon, Alon Amid, Amir Gholami, Bichen Wu, Krste Asanovic, Kurt Keutzer
Co-Design of Deep Neural Nets and Neural Net Accelerators for Embedded Vision Applications. CoRR (2018)
Zhewei Yao, Amir Gholami, Peng Xu, Kurt Keutzer, Michael W. Mahoney
Trust Region Based Adversarial Attack on Neural Networks. CoRR (2018)
Zhewei Yao, Amir Gholami, Qi Lei, Kurt Keutzer, Michael W. Mahoney
Hessian-based Analysis of Large Batch Training and Robustness to Adversaries. CoRR (2018)
Noah Golmant, Nikita Vemuri, Zhewei Yao, Vladimir Feinberg, Amir Gholami, Kai Rothauge, Michael W. Mahoney, Joseph Gonzalez
On the Computational Inefficiency of Large Batch Sizes for Stochastic Gradient Descent. CoRR (2018)
Amir Gholami, Ariful Azad, Peter H. Jin, Kurt Keutzer, Aydin Buluç
Integrated Model, Batch, and Domain Parallelism in Training Neural Networks. SPAA (2018)
Amir Gholami, Shashank Subramanian, Varun Shenoy, Naveen Himthani, Xiangyu Yue, Sicheng Zhao, Peter H. Jin, George Biros, Kurt Keutzer
A Novel Domain Adaptation Framework for Medical Image Segmentation. CoRR (2018)
Amir Gholami, Kiseok Kwon, Bichen Wu, Zizheng Tai, Xiangyu Yue, Peter H. Jin, Sicheng Zhao, Kurt Keutzer
SqueezeNext: Hardware-Aware Neural Network Design. CVPR Workshops (2018)
Kiseok Kwon, Alon Amid, Amir Gholami, Bichen Wu, Krste Asanovic, Kurt Keutzer
Co-design of deep neural nets and neural net accelerators for embedded vision applications. DAC (2018)
Amir Gholami, Shashank Subramanian, Varun Shenoy, Naveen Himthani, Xiangyu Yue, Sicheng Zhao, Peter H. Jin, George Biros, Kurt Keutzer
A Novel Domain Adaptation Framework for Medical Image Segmentation. BrainLes@MICCAI (2) (2018)
Zhewei Yao, Amir Gholami, Qi Lei, Kurt Keutzer, Michael W. Mahoney
Hessian-based Analysis of Large Batch Training and Robustness to Adversaries. NeurIPS (2018)
Norman Mu, Zhewei Yao, Amir Gholami, Kurt Keutzer, Michael W. Mahoney
Parameter Re-Initialization through Cyclical Batch Size Schedules. CoRR (2018)
Amir Gholami, Kiseok Kwon, Bichen Wu, Zizheng Tai, Xiangyu Yue, Peter H. Jin, Sicheng Zhao, Kurt Keutzer
SqueezeNext: Hardware-Aware Neural Network Design. CoRR (2018)
Amir Gholami, Andreas Mang, Klaudius Scheufele, Christos Davatzikos, Miriam Mehl, George Biros
A framework for scalable biophysics-based image analysis. SC (2017)
Amir Gholami, Ariful Azad, Kurt Keutzer, Aydin Buluç
Integrated Model and Data Parallelism in Training Neural Networks. CoRR (2017)
Andreas Mang, Amir Gholami, George Biros
Distributed-memory large deformation diffeomorphic 3D image registration. SC (2016)
Amir Gholami, Dhairya Malhotra, Hari Sundar, George Biros
FFT, FMM, or Multigrid? A comparative Study of State-Of-the-Art Poisson Solvers for Uniform and Nonuniform Grids in the Unit Cube. SIAM J. Sci. Comput. 38 (3) (2016)
Andreas Mang, Amir Gholami, George Biros
Distributed-memory large deformation diffeomorphic 3D image registration. CoRR (2016)
Amir Gholami, Judith Hill, Dhairya Malhotra, George Biros
AccFFT: A library for distributed-memory FFT on CPU and GPU architectures. CoRR (2015)
Amir Gholami, Dhairya Malhotra, Hari Sundar, George Biros
FFT, FMM, or MULTIGRID? A comparative study of state-of-the-art poisson solvers. CoRR (2014)
Dhairya Malhotra, Amir Gholami, George Biros
A Volume Integral Equation Stokes Solver for Problems with Variable Coefficients. SC (2014)