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James Diffenderfer
James Diffenderfer
Verified email at llnl.gov
Title
Cited by
Cited by
Year
Multi-prize lottery ticket hypothesis: Finding accurate binary neural networks by pruning a randomly weighted network
J Diffenderfer, B Kailkhura
arXiv preprint arXiv:2103.09377, 2021
802021
Error analysis of zfp compression for floating-point data
J Diffenderfer, AL Fox, JA Hittinger, G Sanders, PG Lindstrom
SIAM Journal on Scientific Computing 41 (3), A1867-A1898, 2019
712019
A winning hand: Compressing deep networks can improve out-of-distribution robustness
J Diffenderfer, B Bartoldson, S Chaganti, J Zhang, B Kailkhura
Advances in neural information processing systems 34, 664-676, 2021
552021
Stability analysis of inline ZFP compression for floating-point data in iterative methods
A Fox, J Diffenderfer, J Hittinger, G Sanders, P Lindstrom
SIAM Journal on Scientific Computing 42 (5), A2701-A2730, 2020
182020
HPAC: evaluating approximate computing techniques on HPC OpenMP applications
K Parasyris, G Georgakoudis, H Menon, J Diffenderfer, I Laguna, ...
Proceedings of the International Conference for High Performance Computing …, 2021
112021
QDOT: Quantized dot product kernel for approximate high-performance computing
J Diffenderfer, D Osei-Kuffuor, H Menon
arXiv preprint arXiv:2105.00115, 2021
52021
Variable precision computing
JA Hittinger, PG Lindstrom, H Bhatia, PT Bremer, DM Copeland, ...
Lawrence Livermore National Lab.(LLNL), Livermore, CA (United States), 2019
52019
Deepzero: Scaling up zeroth-order optimization for deep model training
A Chen, Y Zhang, J Jia, J Diffenderfer, J Liu, K Parasyris, Y Zhang, ...
arXiv preprint arXiv:2310.02025, 2023
32023
Zeroth-order sciml: Non-intrusive integration of scientific software with deep learning
I Tsaknakis, B Kailkhura, S Liu, D Loveland, J Diffenderfer, AM Hiszpanski, ...
arXiv preprint arXiv:2206.02785, 2022
32022
A bijection between two classes of restricted compositions
J Diffenderfer
Fibonacci Quart 50 (4), 360-365, 2012
32012
Gtbench: Uncovering the strategic reasoning limitations of llms via game-theoretic evaluations
J Duan, R Zhang, J Diffenderfer, B Kailkhura, L Sun, E Stengel-Eskin, ...
arXiv preprint arXiv:2402.12348, 2024
22024
Algorithm 1035: a gradient-based implementation of the polyhedral active set algorithm
WW Hager, H Zhang
ACM Transactions on Mathematical Software 49 (2), 1-13, 2023
22023
Approximate High-Performance Computing: A Fast and Energy-Efficient Computing Paradigm in the Post-Moore Era
H Menon, J Diffenderfer, G Georgakoudis, I Laguna, MO Lam, ...
IT Professional 25 (2), 7-15, 2023
22023
Approximate computing through the lens of uncertainty quantification
K Parasyris, J Diffenderfer, H Menon, I Laguna, J Vanover, R Vogt, ...
SC22: International Conference for High Performance Computing, Networking …, 2022
22022
Benchmarking test-time unsupervised deep neural network adaptation on edge devices
K Bhardwaj, J Diffenderfer, B Kailkhura, M Gokhale
2022 IEEE International Symposium on Performance Analysis of Systems and …, 2022
22022
Unsupervised test-time adaptation of deep neural networks at the edge: a case study
K Bhardwaj, J Diffenderfer, B Kailkhura, M Gokhale
2022 Design, Automation & Test in Europe Conference & Exhibition (DATE), 412-417, 2022
12022
A framework for error-bounded approximate computing, with an application to dot products
J Diffenderfer, D Osei-Kuffuor, H Menon
SIAM Journal on Scientific Computing 44 (3), A1290-A1314, 2022
12022
Decoding Compressed Trust: Scrutinizing the Trustworthiness of Efficient LLMs Under Compression
J Hong, J Duan, C Zhang, Z Li, C Xie, K Lieberman, J Diffenderfer, ...
arXiv preprint arXiv:2403.15447, 2024
2024
When Bio-Inspired Computing meets Deep Learning: Low-Latency, Accurate, & Energy-Efficient Spiking Neural Networks from Artificial Neural Networks
G Datta, Z Liu, J Diffenderfer, B Kailkhura, PA Beerel
arXiv preprint arXiv:2312.06900, 2023
2023
Neural Image Compression: Generalization, Robustness, and Spectral Biases
K Lieberman, J Diffenderfer, C Godfrey, B Kailkhura
ICML 2023 Workshop Neural Compression: From Information Theory to Applications, 2023
2023
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