papers
Publications (10)
cs.CV2026
EdgeCompress: Coupling Multidimensional Model Compression and Dynamic Inference for EdgeAI
Hao Kong, Di Liu, Shuo Huai +5
cs.LG2026
Collate: Collaborative Neural Network Learning for Latency-Critical Edge Systems
Shuo Huai, Di Liu, Hao Kong +5
cs.CV2026
Smart Scissor: Coupling Spatial Redundancy Reduction and CNN Compression for Embedded Hardware
Hao Kong, Di Liu, Shuo Huai +5
cs.LG2026
Latency-Constrained DNN Architecture Learning for Edge Systems using Zerorized Batch Normalization
Shuo Huai, Di Liu, Hao Kong +4
cs.AR2026
On Hardware-Aware Design and Optimization of Edge Intelligence
Shuo Huai, Hao Kong, Xiangzhong Luo +5
cs.CV2026
Towards Efficient Convolutional Neural Network for Embedded Hardware via Multi-Dimensional Pruning
Hao Kong, Di Liu, Xiangzhong Luo +5
The paper introduces TECO, a framework that jointly prunes depth, width, and input resolution of convolutional neural networks to improve speed and resource usage on embedded devic…
#model compression#pruning#embedded hardware#convolutional neural networks
cs.AR2026
CRIMP: Compact & Reliable DNN Inference on In-Memory Processing via Crossbar-Aligned Compression and Non-ideality Adaptation
Shuo Huai, Hao Kong, Xiangzhong Luo +5
cs.LG2020
Bringing AI To Edge: From Deep Learning's Perspective
Di Liu, Hao Kong, Xiangzhong Luo +2
cs.CV2026
FedTR: Federated Learning Framework with Transfer Learning for Industrial Visual Inspection
Vikash Sathiamoorthy, Shuo Huai, Hao Kong +7
cs.LG2026
EvoLP: Self-Evolving Latency Predictor for Model Compression in Real-Time Edge Systems
Shuo Huai, Hao Kong, Shiqing Li +5