Decaying momentum helps neural network training. - John Chen 002; Anastasios Kyrillidis (CoRR, 2019)

Negative Sampling in Semi-Supervised learning. - John Chen 002; Vatsal Shah; Anastasios Kyrillidis (ICML, 2020)

STORM: Foundations of End-to-End Empirical Risk Minimization on the Edge. - Benjamin Coleman; Gaurav Gupta; John Chen 002; Anshumali Shrivastava (CoRR, 2020)

ImCLR: Implicit Contrastive Learning for Image Classification. - John Chen 002; Samarth Sinha; Anastasios Kyrillidis (CoRR, 2020)

Revisiting Consistent Hashing with Bounded Loads. - John Chen 002; Benjamin Coleman; Anshumali Shrivastava (AAAI, 2021)

Mitigating Deep Double Descent by Concatenating Inputs. - John Chen 002; Qihan Wang; Anastasios Kyrillidis (CIKM, 2021)

Demon: Improved Neural Network Training With Momentum Decay. - John Chen 002; Cameron R. Wolfe; Zhao Li; Anastasios Kyrillidis (ICASSP, 2022)

REX: Revisiting Budgeted Training with an Improved Schedule. - John Chen 002; Cameron R. Wolfe; Tasos Kyrillidis (MLSys, 2022)

Stackmix: a complementary mix algorithm. - John Chen 002; Samarth Sinha; Anastasios Kyrillidis (UAI, 2022)

Fast FixMatch: Faster Semi-Supervised Learning with Curriculum Batch Size. - John Chen 002; Chen Dun; Anastasios Kyrillidis (ISIT, 2024)