Exploring the Use of Synthetic Gradients for Distributed Deep Learning across Cloud and Edge Resources. - Yitao Chen; Kaiqi Zhao 002; Baoxin Li; Ming Zhao 002 (HotEdge, 2019)

KnowledgeNet: Disaggregated and Distributed Training and Serving of Deep Neural Networks. - Saman Biookaghazadeh; Yitao Chen; Kaiqi Zhao 002; Ming Zhao 002 (OpML, 2019)

Knowledge Distillation via Module Replacing for Automatic Speech Recognition with Recurrent Neural Network Transducer. - Kaiqi Zhao 002; Hieu Nguyen; Animesh Jain; Nathan Susanj; Athanasios Mouchtaris; Lokesh Gupta; Ming Zhao 002 (INTERSPEECH, 2022)

Iterative Activation-based Structured Pruning. - Kaiqi Zhao 002; Animesh Jain; Ming Zhao 002 (CoRR, 2022)

Adaptive Activation-based Structured Pruning. - Kaiqi Zhao 002; Animesh Jain; Ming Zhao 002 (CoRR, 2022)

Enabling Deep Learning on Edge Devices through Filter Pruning and Knowledge Transfer. - Kaiqi Zhao 002; Yitao Chen; Ming Zhao 002 (CoRR, 2022)

Automatic Attention Pruning: Improving and Automating Model Pruning using Attentions. - Kaiqi Zhao 002; Animesh Jain; Ming Zhao 002 (AISTATS, 2023)

A Contrastive Knowledge Transfer Framework for Model Compression and Transfer Learning. - Kaiqi Zhao 002; Yitao Chen; Ming Zhao 002 (ICASSP, 2023)

Poster: Self-Supervised Quantization-Aware Knowledge Distillation. - Kaiqi Zhao 002; Ming Zhao 002 (SEC, 2023)

Self-Supervised Quantization-Aware Knowledge Distillation. - Kaiqi Zhao 002; Ming Zhao 002 (AISTATS, 2024)