Accelerated Convergence of Nesterov's Momentum for Deep Neural Networks under Partial Strong Convexity
Fangshuo Liao, Anastasios Kyrillidis. ALT, 2024
On the Error-Propagation of Inexact Deflation for Principal Component Analysis
Fangshuo Liao, Junhyung Lyle Kim, Cruz Barnum, Anastasios Kyrillidis. Preprint. Under Review, 2023
Scissorhands: Exploiting the of Importance Hypothesis for LLM KV Cache Compression at Test Time
Zichang Liu, Aditya Desai, Fangshuo Liao, Weitao Wang, Victor Xie, Zhaozhuo Xu, Anastasios Kyrillidis, Anshumali Shrivastava. NeurIPS, 2023
Strong Lottery Ticket Hypothesis with ε-Perturbation
Zheyang Xiong*, Fangshuo Liao*, Anastasios Kyrillidis. AISTATS, 2023
LoFT: Finding Lottery Tickets through Filter-wise Training
Qihan Wang*, Chen Dun*, Fangshuo Liao*, Chris Jermaine, Anastasios Kyrillidis. AISTATS, 2023
GIST: Distributed training for large-scale graph convolutional networks
Cameron R Wolfe*, Jingkang Yang*, Fangshuo Liao*, Arindam Chowdhury, Chen Dun, Artun Bayer, Santiago Segarra, Anastasios Kyrillidis. Journal of Applied and Computational Topology, 2023
On the Convergence of Shallow Neural Network Training with Randomly Masked Neurons
Fangshuo Liao, Anastasios Kyrillidis. TMLR, 2022
How Much Pre-training Is Enough to Discover a Good Subnetwork?
Cameron R Wolfe*, Fangshuo Liao*, Qihan Wang, Junhyung Lyle Kim, Anastasios Kyrillidis. Preprint. Under Review, 2021