93 citations · 100 across the 6 of their papers we have counts for
12 papers
RCT: Resource Constrained Training for Edge AI
Tian Huang, Tao Luo, Ming Yan +2
Neural networks training on edge terminals is essential for edge AI computing, which needs to be adaptive to evolving environment. Quantised models can efficiently run on edge devi…
Natural Language Video Localization: A Revisit in Span-based Question Answering Framework
Hao Zhang, Aixin Sun, Wei Jing +3
Natural Language Video Localization (NLVL) aims to locate a target moment from an untrimmed video that semantically corresponds to a text query. Existing approaches mainly solve th…
Deep N-ary Error Correcting Output Codes
Hao Zhang, Joey Tianyi Zhou, Tianying Wang +2
Ensemble learning consistently improves the performance of multi-class classification through aggregating a series of base classifiers. To this end, data-independent ensemble metho…
EDCompress: Energy-Aware Model Compression for Dataflows
Zhehui Wang, Tao Luo, Joey Tianyi Zhou +1
Edge devices demand low energy consumption, cost and small form factor. To efficiently deploy convolutional neural network (CNN) models on edge device, energy-aware model compressi…
Two-Phase Multi-Party Computation Enabled Privacy-Preserving Federated Learning
Renuga Kanagavelu, Zengxiang Li, Juniarto Samsudin +7
Countries across the globe have been pushing strict regulations on the protection of personal or private data collected. The traditional centralized machine learning method, where…
Feature Lenses: Plug-and-play Neural Modules for Transformation-Invariant Visual Representations
Shaohua Li, Xiuchao Sui, Jie Fu +2
Convolutional Neural Networks (CNNs) are known to be brittle under various image transformations, including rotations, scalings, and changes of lighting conditions. We observe that…