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 | 88 | 2021 |
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 | 79 | 2019 |
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 | 61 | 2021 |
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 | 18 | 2020 |
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 | 14 | 2024 |
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 | 13 | 2021 |
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 | 5 | 2023 |
QDOT: Quantized dot product kernel for approximate high-performance computing J Diffenderfer, D Osei-Kuffuor, H Menon arXiv preprint arXiv:2105.00115, 2021 | 5 | 2021 |
Variable precision computing JA Hittinger, PG Lindstrom, H Bhatia, PT Bremer, DM Copeland, ... Lawrence Livermore National Lab.(LLNL), Livermore, CA (United States), 2019 | 5 | 2019 |
Soul: Unlocking the power of second-order optimization for llm unlearning J Jia, Y Zhang, Y Zhang, J Liu, B Runwal, J Diffenderfer, B Kailkhura, ... arXiv preprint arXiv:2404.18239, 2024 | 4 | 2024 |
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 | 4 | 2023 |
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 | 4 | 2022 |
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 | 3 | 2022 |
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 | 3 | 2022 |
A bijection between two classes of restricted compositions J Diffenderfer Fibonacci Quart 50 (4), 360-365, 2012 | 3 | 2012 |
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 | 2 | 2023 |
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 | 2 | 2022 |
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 | 1 | 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 | 1 | 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 | 1 | 2023 |