Publications & Contributions

Preprints

• Prompt-prompted Mixture of Experts for Efficient LLM Generation, Harry Dong, Beidi Chen, Yuejie Chi, 2024.

• Get More with LESS: Synthesizing Recurrence with KV Cache Compression for Efficient LLM Inference, Harry Dong, Xinyu Yang, Zhenyu Zhang, Zhangyang Wang, Yuejie Chi, Beidi Chen, 2024.

Journals

• A Lightweight Transformer for Faster and Robust EBSD Data Collection, H. Dong, S. Donegan, M. Shah, Y. Chi, Scientific Reports, 2024.

  • Oral presentation at the Machine Learning for Scientific Imaging Conference at Electronic Imaging, 2024.

  • Poster presentation at the Joint Workshop at the Intersection of Materials Science and Machine Learning, 2023.

• Fast and Provable Tensor Robust Principal Component Analysis via Scaled Gradient Descent, H. Dong, T. Tong, C. Ma, Y. Chi, Information and Inference: A Journal of the IMA, 2023.

  • Contributed talk at SIAM Conference on Mathematics of Data Science, 2022.

Conference Papers

• Deep Unfolded Tensor Robust PCA with Self-supervised Learning, H. Dong, M. Shah, S. Donegan, Y. Chi, IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), 2023.

  • Also presented at the Third Workshop on Seeking Low‑Dimensionality in Deep Neural Networks, 2023.

• Learning Optimal Traffic Routing Behaviors using Markovian Framework in Microscopic Simulation, T. Cabannes, J. Li, F. Wu, H. Dong, A. Bayen, TRB 99th Annual Meeting, 2020.

Workshops

• Towards Structured Sparsity in Transformers for Efficient Inference, H. Dong, B. Chen, Y. Chi, ICML Workshop on Efficient Systems for Foundation Models, 2023.