Demo: Hands-Free Human Activity Recognition Using Millimeter-Wave Sensors. - Soo Min Kwon; Song Yang; Jian Liu 001; Xin Yang; Wesam Saleh; Shreya Patel; Christine Mathews; Yingying Chen 001 (DySPAN, 2019)

Low-Rank Phase Retrieval with Structured Tensor Models. - Soo Min Kwon; Xin Li; Anand D. Sarwate (ICASSP, 2022)

Efficient Compression of Overparameterized Deep Models through Low-Dimensional Learning Dynamics. - Soo Min Kwon; Zekai Zhang; Dogyoon Song; Laura Balzano; Qing Qu 001 (CoRR, 2023)

Efficient Low-Dimensional Compression of Overparameterized Models. - Soo Min Kwon; Zekai Zhang; Dogyoon Song; Laura Balzano; Qing Qu 001 (AISTATS, 2024)

Solving Inverse Problems with Latent Diffusion Models via Hard Data Consistency. - Bowen Song; Soo Min Kwon; Zecheng Zhang; Xinyu Hu; Qing Qu 001; Liyue Shen (ICLR, 2024)

BLAST: Block-Level Adaptive Structured Matrices for Efficient Deep Neural Network Inference. - Changwoo Lee 001; Soo Min Kwon; Qing Qu 001; Hun-Seok Kim (NeurIPS, 2024)

Decoupled Data Consistency with Diffusion Purification for Image Restoration. - Xiang Li; Soo Min Kwon; Ismail R. Alkhouri; Saiprasad Ravishankar; Qing Qu 001 (CoRR, 2024)

Learning Dynamics of Deep Matrix Factorization Beyond the Edge of Stability. - Avrajit Ghosh; Soo Min Kwon; Rongrong Wang; Saiprasad Ravishankar; Qing Qu 001 (ICLR, 2025)

Learning Dynamics of Deep Linear Networks Beyond the Edge of Stability. - Avrajit Ghosh; Soo Min Kwon; Rongrong Wang; Saiprasad Ravishankar; Qing Qu 001 (CoRR, 2025)

An Overview of Low-Rank Structures in the Training and Adaptation of Large Models. - Laura Balzano; Tianjiao Ding; Benjamin D. Haeffele; Soo Min Kwon; Qing Qu 001; Peng Wang 098; Zhangyang Wang; Can Yaras (CoRR, 2025)

Out-of-Distribution Generalization of In-Context Learning: A Low-Dimensional Subspace Perspective. - Soo Min Kwon; Alec S. Xu; Can Yaras; Laura Balzano; Qing Qu 001 (CoRR, 2025)