13 citations · 16 across the 5 of their papers we have counts for
5 papers
Totoro: An Adaptive and Scalable Edge Federated Learning System
Cheng-Wei Ching, Xin Chen, Taehwan Kim +3
Federated Learning (FL) is an emerging distributed machine learning (ML) technique that enables in-situ model training and inference on decentralized edge devices. We propose Totor…
StraightLine: An End-to-End Resource-Aware Scheduler for Machine Learning Application Requests
Cheng-Wei Ching, Boyuan Guan, Hailu Xu +1
The life cycle of machine learning (ML) applications consists of two stages: model development and model deployment. However, traditional ML systems (e.g., training-specific or inf…
AgileDART: An Agile and Scalable Edge Stream Processing Engine
Cheng-Wei Ching, Xin Chen, Chaeeun Kim +4
Edge applications generate a large influx of sensor data on massive scales, and these massive data streams must be processed shortly to derive actionable intelligence. However, tra…
Decaffe: DHT Tree-Based Online Federated Fake News Detection
Cheng-Wei Ching, Liting Hu
The proliferation of mobile social networks (MSNs) has transformed information dissemination, leading to increased reliance on these platforms for news consumption. However, this s…
OrcoDCS: An IoT-Edge Orchestrated Online Deep Compressed Sensing Framework
Cheng-Wei Ching, Chirag Gupta, Zi Huang +1
Compressed data aggregation (CDA) over wireless sensor networks (WSNs) is task-specific and subject to environmental changes. However, the existing compressed data aggregation (CDA…