Tensor Kernel Recovery for Spatio-Temporal Hawkes Processes. - Heejune Sheen; Xiaonan Zhu; Yao Xie (CoRR, 2020)

Exploiting aggregate sparsity in second-order cone relaxations for quadratic constrained quadratic programming problems. - Heejune Sheen; Makoto Yamashita (Optim. Methods Softw., 2022)

Tensor Kernel Recovery for Discrete Spatio-Temporal Hawkes Processes. - Heejune Sheen; Xiaonan Zhu; Yao Xie 002 (IEEE Trans. Signal Process., 2022)

Training Dynamics of Multi-Head Softmax Attention for In-Context Learning: Emergence, Convergence, and Optimality (extended abstract). - Siyu Chen 001; Heejune Sheen; Tianhao Wang 002; Zhuoran Yang (COLT, 2024)

Unveiling Induction Heads: Provable Training Dynamics and Feature Learning in Transformers. - Siyu Chen 001; Heejune Sheen; Tianhao Wang 002; Zhuoran Yang (NeurIPS, 2024)

Training Dynamics of Multi-Head Softmax Attention for In-Context Learning: Emergence, Convergence, and Optimality. - Siyu Chen 001; Heejune Sheen; Tianhao Wang 002; Zhuoran Yang (CoRR, 2024)

Implicit Regularization of Gradient Flow on One-Layer Softmax Attention. - Heejune Sheen; Siyu Chen 001; Tianhao Wang 002; Harrison H. Zhou (CoRR, 2024)

Taming Polysemanticity in LLMs: Provable Feature Recovery via Sparse Autoencoders. - Siyu Chen 001; Heejune Sheen; Xuyuan Xiong; Tianhao Wang 002; Zhuoran Yang (CoRR, 2025)