James Diffenderfer

Publication Activity (10 Years)

Years Active: 2017-2024
Publications (10 Years): 31

Top Topics

Top Venues

SIAM J. Sci. Comput.

Publications

Brian R. Bartoldson, James Diffenderfer, Konstantinos Parasyris, Bhavya Kailkhura
Adversarial Robustness Limits via Scaling-Law and Human-Alignment Studies. CoRR (2024)
Aochuan Chen, Yimeng Zhang, Jinghan Jia, James Diffenderfer, Konstantinos Parasyris, Jiancheng Liu, Yihua Zhang, Zheng Zhang, Bhavya Kailkhura, Sijia Liu
DeepZero: Scaling Up Zeroth-Order Optimization for Deep Model Training. ICLR (2024)
Shaocong Ma, James Diffenderfer, Bhavya Kailkhura, Yi Zhou
End-to-End Mesh Optimization of a Hybrid Deep Learning Black-Box PDE Solver. CoRR (2024)
Jinhao Duan, Shiqi Wang, James Diffenderfer, Lichao Sun, Tianlong Chen, Bhavya Kailkhura, Kaidi Xu
ReTA: Recursively Thinking Ahead to Improve the Strategic Reasoning of Large Language Models. NAACL-HLT (2024)
Jinghan Jia, Yihua Zhang, Yimeng Zhang, Jiancheng Liu, Bharat Runwal, James Diffenderfer, Bhavya Kailkhura, Sijia Liu
SOUL: Unlocking the Power of Second-Order Optimization for LLM Unlearning. CoRR (2024)
Jinhao Duan, Renming Zhang, James Diffenderfer, Bhavya Kailkhura, Lichao Sun, Elias Stengel-Eskin, Mohit Bansal, Tianlong Chen, Kaidi Xu
GTBench: Uncovering the Strategic Reasoning Limitations of LLMs via Game-Theoretic Evaluations. CoRR (2024)
Junyuan Hong, Jinhao Duan, Chenhui Zhang, Zhangheng Li, Chulin Xie, Kelsey Lieberman, James Diffenderfer, Brian R. Bartoldson, Ajay Jaiswal, Kaidi Xu, Bhavya Kailkhura, Dan Hendrycks, Dawn Song, Zhangyang Wang, Bo Li
Decoding Compressed Trust: Scrutinizing the Trustworthiness of Efficient LLMs Under Compression. CoRR (2024)
Kelsey Lieberman, James Diffenderfer, Charles Godfrey, Bhavya Kailkhura
Neural Image Compression: Generalization, Robustness, and Spectral Biases. CoRR (2023)
Kelsey Lieberman, James Diffenderfer, Charles Godfrey, Bhavya Kailkhura
Neural Image Compression: Generalization, Robustness, and Spectral Biases. NeurIPS (2023)
Aochuan Chen, Yimeng Zhang, Jinghan Jia, James Diffenderfer, Jiancheng Liu, Konstantinos Parasyris, Yihua Zhang, Zheng Zhang, Bhavya Kailkhura, Sijia Liu
DeepZero: Scaling up Zeroth-Order Optimization for Deep Model Training. CoRR (2023)
Harshitha Menon, James Diffenderfer, Giorgis Georgakoudis, Ignacio Laguna, Michael O. Lam, Daniel Osei-Kuffuor, Konstantinos Parasyris, Jackson Vanover
Approximate High-Performance Computing: A Fast and Energy-Efficient Computing Paradigm in the Post-Moore Era. IT Prof. 25 (2) (2023)
Gourav Datta, Zeyu Liu, James Diffenderfer, Bhavya Kailkhura, Peter A. Beerel
When Bio-Inspired Computing meets Deep Learning: Low-Latency, Accurate, & Energy-Efficient Spiking Neural Networks from Artificial Neural Networks. CoRR (2023)
Sara Fridovich-Keil, Brian R. Bartoldson, James Diffenderfer, Bhavya Kailkhura, Timo Bremer
Models Out of Line: A Fourier Lens on Distribution Shift Robustness. NeurIPS (2022)
Kshitij Bhardwaj, James Diffenderfer, Bhavya Kailkhura, Maya B. Gokhale
Unsupervised Test-Time Adaptation of Deep Neural Networks at the Edge: A Case Study. DATE (2022)
Sara Fridovich-Keil, Brian R. Bartoldson, James Diffenderfer, Bhavya Kailkhura, Peer-Timo Bremer
Models Out of Line: A Fourier Lens on Distribution Shift Robustness. CoRR (2022)
James Diffenderfer, Daniel Osei-Kuffuor, Harshitha Menon
A Framework for Error-Bounded Approximate Computing, with an Application to Dot Products. SIAM J. Sci. Comput. 44 (3) (2022)
Kshitij Bhardwaj, James Diffenderfer, Bhavya Kailkhura, Maya B. Gokhale
Benchmarking Test-Time Unsupervised Deep Neural Network Adaptation on Edge Devices. ISPASS (2022)
Ioannis C. Tsaknakis, Bhavya Kailkhura, Sijia Liu, Donald Loveland, James Diffenderfer, Anna Maria Hiszpanski, Mingyi Hong
Zeroth-Order SciML: Non-intrusive Integration of Scientific Software with Deep Learning. CoRR (2022)
Konstantinos Parasyris, James Diffenderfer, Harshitha Menon, Ignacio Laguna, Jackson Vanover, Ryan Vogt, Daniel Osei-Kuffuor
Approximate Computing Through the Lens of Uncertainty Quantification. SC (2022)
Hao Cheng, Pu Zhao, Yize Li, Xue Lin, James Diffenderfer, Ryan A. Goldhahn, Bhavya Kailkhura
Efficient Multi-Prize Lottery Tickets: Enhanced Accuracy, Training, and Inference Speed. CoRR (2022)
Kshitij Bhardwaj, James Diffenderfer, Bhavya Kailkhura, Maya B. Gokhale
Benchmarking Test-Time Unsupervised Deep Neural Network Adaptation on Edge Devices. CoRR (2022)
James Diffenderfer, Brian R. Bartoldson, Shreya Chaganti, Jize Zhang, Bhavya Kailkhura
A Winning Hand: Compressing Deep Networks Can Improve Out-Of-Distribution Robustness. CoRR (2021)
James Diffenderfer, Bhavya Kailkhura
Multi-Prize Lottery Ticket Hypothesis: Finding Accurate Binary Neural Networks by Pruning A Randomly Weighted Network. CoRR (2021)
Konstantinos Parasyris, Giorgis Georgakoudis, Harshitha Menon, James Diffenderfer, Ignacio Laguna, Daniel Osei-Kuffuor, Markus Schordan
HPAC: evaluating approximate computing techniques on HPC OpenMP applications. SC (2021)
James Diffenderfer, Daniel Osei-Kuffuor, Harshitha Menon
QDOT: Quantized Dot Product Kernel for Approximate High-Performance Computing. CoRR (2021)
James Diffenderfer, Bhavya Kailkhura
Multi-Prize Lottery Ticket Hypothesis: Finding Accurate Binary Neural Networks by Pruning A Randomly Weighted Network. ICLR (2021)
James Diffenderfer, Brian R. Bartoldson, Shreya Chaganti, Jize Zhang, Bhavya Kailkhura
A Winning Hand: Compressing Deep Networks Can Improve Out-of-Distribution Robustness. NeurIPS (2021)
Alyson Fox, James Diffenderfer, Jeffrey Hittinger, Geoffrey Sanders, Peter Lindstrom
Stability Analysis of Inline ZFP Compression for Floating-Point Data in Iterative Methods. SIAM J. Sci. Comput. 42 (5) (2020)
Alyson Fox, James Diffenderfer, Jeffrey Hittinger, Geoffrey Sanders, Peter Lindstrom
Stability Analysis of Inline ZFP Compression for Floating-Point Data in Iterative Methods. CoRR (2020)
James Diffenderfer, Alyson Fox, Jeffrey A. F. Hittinger, Geoffrey Sanders, Peter G. Lindstrom
Error Analysis of ZFP Compression for Floating-Point Data. SIAM J. Sci. Comput. 41 (3) (2019)
Xiezhang Li, James Diffenderfer, Jiehua Zhu
Construction of a full row-rank matrix system for multiple scanning directions in discrete tomography. J. Comput. Appl. Math. 311 (2017)