Publications

Journal Papers

Conference Papers

2024

  • Nicholas Eliopoulos, Purvish Jajal, James Davis, Gaowen Liu, George Thiruvathukal, Yung-Hsiang Lu, “Pruning One More Token is Enough: Leveraging Latency-Workload Non-Linearities for Vision Transformers on the Edge”, IEEE/CVF Winter Conference on Applications of Computer Vision 2025

  • Purvish Jajal, Nicholas Eliopoulos, Benjamin Chou, George Thiruvathukal, James Davis, Yung-Hsiang Lu, “Token Turing Machines are Efficient Vision Models”, IEEE/CVF Winter Conference on Applications of Computer Vision 2025

  • Cheng-Yun Yang, Gowri Ramshankar, Sudarshan Nambiar, Evan Miller,Xun Zhang, Nicholas Eliopoulos, Purvish Jajal, Dave Jing Tian, Shuo-Han Chen, Chiy-Ferng Perng, Yung-Hsiang Lu, “Securing Deep Neural Networks on Edge from Membership Inference Attacks Using Trusted Execution Environments” , IEEE/ACM International Symposium on Low Power Electronics and Design 2024.

  • Brian Ng, Samantha Sudhoff, Haichang Li, Josh Kamphuis, Tim Nadolsky, Yingjie Chen, Kristen Yun, Yung-Hsiang Lu, “Visualize Music Using Generative Arts”, IEEE Conference on Artificial Intelligence 2024. DOI: https://10.1109/CAI59869.2024.00273

  • Caleb Tung, Nicholas Eliopoulos, Purvish Jajal, Gowri Ramshankar, Chen-Yun Yang, Nicholas Synovic, Xuecen Zhang, Vipin Chaudhary, George K. Thiruvathukal, Yung-Hsiang Lu, “An automated approach for improving the inference latency and energy efficiency of pretrained CNNs by removing irrelevant pixels with focused convolutions”, Asia and South Pacific Design Automation Conference 2024. DOI: http://10.1109/ASP-DAC58780.2024.10473884

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Book Chapters

Technical Reports

Book

PhD Thesis

Yung-Hsiang Lu, “Doctoral Thesis: Power-aware operating systems for interactive systems”, Primary Advisor: Giovanni De Micheli, Department of Electrical Engineering, Stanford University, 2001.