Amir Gholami

Orcid: 0000-0003-0125-3459

Affiliations:
  • University of California Berkeley, CA, USA


According to our database1, Amir Gholami authored at least 69 papers between 2014 and 2024.

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Bibliography

2024
Spatio-Temporal Deep Graph Network for Event Detection, Localization, and Classification in Cyber-Physical Electric Distribution System.
IEEE Trans. Ind. Informatics, February, 2024

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, January, 2024

Multi-Source Data Aggregation and Real-Time Anomaly Classification and Localization in Power Distribution Systems.
IEEE Trans. Smart Grid, 2024

KVQuant: Towards 10 Million Context Length LLM Inference with KV Cache Quantization.
CoRR, 2024

2023
An LLM Compiler for Parallel Function Calling.
CoRR, 2023

SPEED: Speculative Pipelined Execution for Efficient Decoding.
CoRR, 2023

SqueezeLLM: Dense-and-Sparse Quantization.
CoRR, 2023

End-to-end codesign of Hessian-aware quantized neural networks for FPGAs and ASICs.
CoRR, 2023

Full Stack Optimization of Transformer Inference: a Survey.
CoRR, 2023

Big Little Transformer Decoder.
CoRR, 2023

Towards Foundation Models for Scientific Machine Learning: Characterizing Scaling and Transfer Behavior.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Speculative Decoding with Big Little Decoder.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Adaptive Self-Supervision Algorithms for Physics-Informed Neural Networks.
Proceedings of the ECAI 2023 - 26th European Conference on Artificial Intelligence, September 30 - October 4, 2023, Kraków, Poland, 2023

2022
Road accident risk prediction using generalized regression neural network optimized with self-organizing map.
Neural Comput. Appl., 2022

Applications and Techniques for Fast Machine Learning in Science.
Frontiers Big Data, 2022

Hessian-Aware Pruning and Optimal Neural Implant.
Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2022

A Fast Post-Training Pruning Framework for Transformers.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Squeezeformer: An Efficient Transformer for Automatic Speech Recognition.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Learned Token Pruning for Transformers.
Proceedings of the KDD '22: The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, August 14, 2022

Integer-Only Zero-Shot Quantization for Efficient Speech Recognition.
Proceedings of the IEEE International Conference on Acoustics, 2022

2021
Applications and Techniques for Fast Machine Learning in Science.
CoRR, 2021

Learned Token Pruning for Transformers.
CoRR, 2021

Q-ASR: Integer-only Zero-shot Quantization for Efficient Speech Recognition.
CoRR, 2021

A Survey of Quantization Methods for Efficient Neural Network Inference.
CoRR, 2021

Hessian-Aware Pruning and Optimal Neural Implant.
CoRR, 2021

Characterizing possible failure modes in physics-informed neural networks.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

HAWQ-V3: Dyadic Neural Network Quantization.
Proceedings of the 38th International Conference on Machine Learning, 2021

I-BERT: Integer-only BERT Quantization.
Proceedings of the 38th International Conference on Machine Learning, 2021

Denoising and Bad Data Detection in Distribution Phasor Measurements using Filtering, Clustering and Koopman Mode Analysis.
Proceedings of the IEEE Industry Applications Society Annual Meeting, 2021

ADAHESSIAN: An Adaptive Second Order Optimizer for Machine Learning.
Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020
HAWQV3: Dyadic Neural Network Quantization.
CoRR, 2020

ADAHESSIAN: An Adaptive Second Order Optimizer for Machine Learning.
CoRR, 2020

Rethinking Batch Normalization in Transformers.
CoRR, 2020

Boundary thickness and robustness in learning models.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

HAWQ-V2: Hessian Aware trace-Weighted Quantization of Neural Networks.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Checkmate: Breaking the Memory Wall with Optimal Tensor Rematerialization.
Proceedings of Machine Learning and Systems 2020, 2020

PowerNorm: Rethinking Batch Normalization in Transformers.
Proceedings of the 37th International Conference on Machine Learning, 2020

ZeroQ: A Novel Zero Shot Quantization Framework.
Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020

PyHessian: Neural Networks Through the Lens of the Hessian.
Proceedings of the 2020 IEEE International Conference on Big Data (IEEE BigData 2020), 2020

Q-BERT: Hessian Based Ultra Low Precision Quantization of BERT.
Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

Inefficiency of K-FAC for Large Batch Size Training.
Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019
Personalized Emotion Recognition by Personality-Aware High-Order Learning of Physiological Signals.
ACM Trans. Multim. Comput. Commun. Appl., 2019

CLAIRE: A Distributed-Memory Solver for Constrained Large Deformation Diffeomorphic Image Registration.
SIAM J. Sci. Comput., 2019

A novel LMI-based robust model predictive control for DFIG-based wind energy conversion systems.
Kybernetika, 2019

Co-design of deep neural nets and neural net accelerators for embedded vision applications.
IBM J. Res. Dev., 2019

HAWQ-V2: Hessian Aware trace-Weighted Quantization of Neural Networks.
CoRR, 2019

ANODEV2: A Coupled Neural ODE Evolution Framework.
CoRR, 2019

MRL Champion Team Paper in Humanoid TeenSize League of RoboCup 2019.
Proceedings of the RoboCup 2019: Robot World Cup XXIII [Sydney, 2019

A Simulation Platform Design and Kinematics Analysis of MRL-HSL Humanoid Robot.
Proceedings of the RoboCup 2019: Robot World Cup XXIII [Sydney, 2019

ANODEV2: A Coupled Neural ODE Framework.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

ANODE: Unconditionally Accurate Memory-Efficient Gradients for Neural ODEs.
Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019

HAWQ: Hessian AWare Quantization of Neural Networks With Mixed-Precision.
Proceedings of the 2019 IEEE/CVF International Conference on Computer Vision, 2019

Trust Region Based Adversarial Attack on Neural Networks.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2019

2018
Parameter Re-Initialization through Cyclical Batch Size Schedules.
CoRR, 2018

On the Computational Inefficiency of Large Batch Sizes for Stochastic Gradient Descent.
CoRR, 2018

Large batch size training of neural networks with adversarial training and second-order information.
CoRR, 2018

PDE-constrained optimization in medical image analysis.
CoRR, 2018

Integrated Model, Batch, and Domain Parallelism in Training Neural Networks.
Proceedings of the 30th on Symposium on Parallelism in Algorithms and Architectures, 2018

Hessian-based Analysis of Large Batch Training and Robustness to Adversaries.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

A Novel Domain Adaptation Framework for Medical Image Segmentation.
Proceedings of the Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries, 2018

Shift: A Zero FLOP, Zero Parameter Alternative to Spatial Convolutions.
Proceedings of the 2018 IEEE Conference on Computer Vision and Pattern Recognition, 2018

SqueezeNext: Hardware-Aware Neural Network Design.
Proceedings of the 2018 IEEE Conference on Computer Vision and Pattern Recognition Workshops, 2018

2017
Integrated Model and Data Parallelism in Training Neural Networks.
CoRR, 2017

A framework for scalable biophysics-based image analysis.
Proceedings of the International Conference for High Performance Computing, 2017

2016
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., 2016

Distributed-memory large deformation diffeomorphic 3D image registration.
Proceedings of the International Conference for High Performance Computing, 2016

2015
AccFFT: A library for distributed-memory FFT on CPU and GPU architectures.
CoRR, 2015

2014
FFT, FMM, or MULTIGRID? A comparative study of state-of-the-art poisson solvers.
CoRR, 2014

A Volume Integral Equation Stokes Solver for Problems with Variable Coefficients.
Proceedings of the International Conference for High Performance Computing, 2014


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