A. Gholami

发表

Checkmate: Breaking the Memory Wall with Optimal Tensor Rematerialization pdf

Kurt Keutzer, Joseph E. Gonzalez, Pieter Abbeel, 2019, MLSys.

A Novel Domain Adaptation Framework for Medical Image Segmentation

Kurt Keutzer, George Biros, Sicheng Zhao, 2018, BrainLes@MICCAI.

Simulation of glioblastoma growth using a 3D multispecies tumor model with mass effect

G. Biros, A. Gholami, Shashank Subramanian, 2018, Journal of Mathematical Biology.

Inefficiency of K-FAC for Large Batch Size Training

Kurt Keutzer, Michael W. Mahoney, Amir Gholami, 2019, AAAI.

CLAIRE: A distributed-memory solver for constrained large deformation diffeomorphic image registration

Christos Davatzikos, George Biros, Amir Gholami, 2018, SIAM J. Sci. Comput..

An inverse problem formulation for parameter estimation of a reaction–diffusion model of low grade gliomas

G. Biros, A. Gholami, A. Mang, 2014, Journal of mathematical biology.

AccFFT: A library for distributed-memory FFT on CPU and GPU architectures pdf

Dhairya Malhotra, George Biros, Amir Gholami, 2015, ArXiv.

FFT, FMM, or Multigrid? A comparative study of state-of-the-art Poisson solvers in the unit cube

Dhairya Malhotra, George Biros, Hari Sundar, 2014 .

Hessian-Aware Pruning and Optimal Neural Implant pdf

Kurt Keutzer, Michael W. Mahoney, Amir Gholami, 2021, 2022 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV).

PyHessian: Neural Networks Through the Lens of the Hessian

Michael W. Mahoney, K. Keutzer, A. Gholami, 2019, 2020 IEEE International Conference on Big Data (Big Data).

ADAHESSIAN: An Adaptive Second Order Optimizer for Machine Learning pdf

Kurt Keutzer, Michael W. Mahoney, Sheng Shen, 2020, AAAI.

Squeezeformer: An Efficient Transformer for Automatic Speech Recognition

Michael W. Mahoney, K. Keutzer, J. Malik, 2022, NeurIPS.

Image-driven parameter estimation for low grade gliomas

G. Biros, A. Gholami, A. Mang, 2014 .

Learned Token Pruning for Transformers

K. Keutzer, A. Gholami, Sheng Shen, 2021, KDD.

Technology roadmap for social banking

A. Gholami, Sepehr Ghazinoory, N. Dastranj, 2017 .

Adaptive Self-supervision Algorithms for Physics-informed Neural Networks

Michael W. Mahoney, Robert M. Kirby, A. Gholami, 2022, ECAI.

A Fast Post-Training Pruning Framework for Transformers

Michael W. Mahoney, K. Keutzer, A. Gholami, 2022, NeurIPS.

ZeroQ: A Novel Zero Shot Quantization Framework

Michael W. Mahoney, K. Keutzer, Zhen Dong, 2020, 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

An inverse problem formulation for parameter estimation of a reaction–diffusion model of low grade gliomas

G. Biros, A. Gholami, A. Mang, 2015, Journal of Mathematical Biology.

Q-BERT: Hessian Based Ultra Low Precision Quantization of BERT

Michael W. Mahoney, K. Keutzer, Zhen Dong, 2019, AAAI.

PDE-constrained optimization in medical image analysis

G. Biros, C. Davatzikos, A. Gholami, 2018, Optimization and Engineering.

Applications and Techniques for Fast Machine Learning in Science pdf

Zhiqiang Que, Ricardo Vilalta, Seda Ogrenci Memik, 2021, Frontiers in Big Data.

Checkmate: Breaking the Memory Wall with Optimal Tensor Rematerialization

P. Abbeel, K. Keutzer, I. Stoica, 2019, MLSys.

ANODEV2: A Coupled Neural ODE Evolution Framework pdf

Kurt Keutzer, Joseph Gonzalez, George Biros, 2019, ArXiv.

ANODE: Unconditionally Accurate Memory-Efficient Gradients for Neural ODEs

Kurt Keutzer, George Biros, Amir Gholami, 2019, IJCAI.

Full Stack Optimization of Transformer Inference: a Survey

Michael W. Mahoney, K. Keutzer, A. Gholami, 2023, ArXiv.

Big Little Transformer Decoder

Michael W. Mahoney, K. Keutzer, J. Malik, 2023, ArXiv.

Integrated Model, Batch, and Domain Parallelism in Training Neural Networks

Kurt Keutzer, Ariful Azad, Amir Gholami, 2017, SPAA.

Characterizing possible failure modes in physics-informed neural networks pdf

Michael W. Mahoney, Shandian Zhe, Amir Gholami, 2021, NeurIPS.

HAWQ-V2: Hessian Aware trace-Weighted Quantization of Neural Networks

Michael W. Mahoney, K. Keutzer, Zhen Dong, 2019, NeurIPS.

HAWQ: Hessian AWare Quantization of Neural Networks With Mixed-Precision

Kurt Keutzer, Zhen Dong, Michael W. Mahoney, 2019, 2019 IEEE/CVF International Conference on Computer Vision (ICCV).

SqueezeNext: Hardware-Aware Neural Network Design

Kurt Keutzer, Sicheng Zhao, Xiangyu Yue, 2018, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW).

I-BERT: Integer-only BERT Quantization

Kurt Keutzer, Michael W. Mahoney, Amir Gholami, 2021, ICML.

A Survey of Quantization Methods for Efficient Neural Network Inference

Michael W. Mahoney, K. Keutzer, Zhen Dong, 2021, Low-Power Computer Vision.

Hessian-based Analysis of Large Batch Training and Robustness to Adversaries

Kurt Keutzer, Michael W. Mahoney, Qi Lei, 2018, NeurIPS.

PDE-constrained optimization in medical image analysis

Christos Davatzikos, George Biros, Amir Gholami, 2018, Optimization and Engineering.

A risk-based optimization framework for integrated supply chains using genetic algorithm and artificial neural networks

Faisal Aqlan, Nasim Nezamoddini, Amirhosein Gholami, 2020 .

Simulation of glioblastoma growth using a 3D multispecies tumor model with mass effect

G. Biros, A. Gholami, Shashank Subramanian, 2019, Journal of Mathematical Biology.

A Framework for Scalable Biophysics-based Image Analysis

Christos Davatzikos, George Biros, Klaudius Scheufele, 2017, SC17: International Conference for High Performance Computing, Networking, Storage and Analysis.

Coupling brain-tumor biophysical models and diffeomorphic image registration.

Christos Davatzikos, George Biros, Klaudius Scheufele, 2017, Computer methods in applied mechanics and engineering.

Integer-Only Zero-Shot Quantization for Efficient Speech Recognition

Michael W. Mahoney, K. Keutzer, Aniruddha Nrusimha, 2021, ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

PowerNorm: Rethinking Batch Normalization in Transformers

Kurt Keutzer, Michael W. Mahoney, Sheng Shen, 2020, ICML.

Boundary thickness and robustness in learning models

Michael W. Mahoney, K. Keutzer, Joseph Gonzalez, 2020, NeurIPS.

End-to-end codesign of Hessian-aware quantized neural networks for FPGAs and ASICs

Michael W. Mahoney, Zhen Dong, J. Mitrevski, 2023, ArXiv.

Rethinking Batch Normalization in Transformers pdf

Kurt Keutzer, Michael W. Mahoney, Sheng Shen, 2020, ICML 2020.

HAWQV3: Dyadic Neural Network Quantization

Kurt Keutzer, Michael W. Mahoney, Leyuan Wang, 2020, ICML.

SqueezeLLM: Dense-and-Sparse Quantization

Michael W. Mahoney, K. Keutzer, Zhen Dong, 2023, ArXiv.

Big Little Transformer Decoder

Michael W. Mahoney, K. Keutzer, J. Malik, 2023, ArXiv.

Full Stack Optimization of Transformer Inference

Michael W. Mahoney, K. Keutzer, A. Gholami, 2023 .

On the Computational Inefficiency of Large Batch Sizes for Stochastic Gradient Descent pdf

Joseph Gonzalez, Michael W. Mahoney, Amir Gholami, 2018, ArXiv.

Towards Foundation Models for Scientific Machine Learning: Characterizing Scaling and Transfer Behavior

Michael W. Mahoney, K. Keutzer, D. Morozov, 2023, NeurIPS.

ANODEV2: A Coupled Neural ODE Framework

Kurt Keutzer, Joseph E. Gonzalez, George Biros, 2019, NeurIPS.

Distributed-Memory Large Deformation Diffeomorphic 3D Image Registration

George Biros, Amir Gholami, Andreas Mang, 2016, SC16: International Conference for High Performance Computing, Networking, Storage and Analysis.

FFT, FMM, or Multigrid? A comparative Study of State-Of-the-Art Poisson Solvers for Uniform and Nonuniform Grids in the Unit Cube

Hari Sundar, Dhairya Malhotra, George Biros, 2014, SIAM J. Sci. Comput..

Risk Based Optimization of Electronics Manufacturing Supply Chains

Faisal Aqlan, Nasim Nezamoddini, Amirhosein Gholami, 2019, Optimization in Large Scale Problems.

Co-design of deep neural nets and neural net accelerators for embedded vision applications

Kurt Keutzer, Krste Asanovic, Amir Gholami, 2019, IBM J. Res. Dev..

Invited: Co-Design of Deep Neural Nets and Neural Net Accelerators for Embedded Vision Applications

Kurt Keutzer, Krste Asanovic, Amir Gholami, 2018, 2018 55th ACM/ESDA/IEEE Design Automation Conference (DAC).

SqueezeLLM: Dense-and-Sparse Quantization

Michael W. Mahoney, K. Keutzer, Zhen Dong, 2023, ArXiv.

Outlier Suppression+: Accurate quantization of large language models by equivalent and effective shifting and scaling

Michael W. Mahoney, Steven K. Esser, Prafulla Dhariwal, 2023, EMNLP.

Speculative Decoding with Big Little Decoder

Michael W. Mahoney, K. Keutzer, J. Malik, 2023, NeurIPS.

An LLM Compiler for Parallel Function Calling

A. Gholami, Nicholas Lee, Kurt Keutzer, 2023, ArXiv.

PyHessian: Neural Networks Through the Lens of the Hessian pdf

Kurt Keutzer, Michael W. Mahoney, Amir Gholami, 2019, 2020 IEEE International Conference on Big Data (Big Data).

Applications and Techniques for Fast Machine Learning in Science

Eric A. Moreno, Sang Eon Park, Tomas E. Muller Bravo, 2021, Frontiers in Big Data.

Road accident risk prediction using generalized regression neural network optimized with self-organizing map

A. Gholami, Neda Kaffash Charandabi, Ali Abdollahzadeh Bina, 2022, Neural Computing and Applications.

KVQuant: Towards 10 Million Context Length LLM Inference with KV Cache Quantization

A. Gholami, Y. Shao, Sehoon Kim, 2024, ArXiv.