4 papers
Machine Learning for Scheduling: A Paradigm Shift from Solver-Centric to Data-Centric Approaches
Anbang Liu, Shaochong Lin, Jingchuan Chen +2
Scheduling problems are a fundamental class of combinatorial optimization problems that underpin operational efficiency in manufacturing, logistics, and service systems. While oper…
Dato: A Task-Based Programming Model for Dataflow Accelerators
Shihan Fang, Hongzheng Chen, Niansong Zhang +4
Recent deep learning workloads increasingly push computational demand beyond what current memory systems can sustain, with many kernels stalling on data movement rather than comput…
Early Detection of Patient Deterioration from Real-Time Wearable Monitoring System
Lo Pang-Yun Ting, Hong-Pei Chen, An-Shan Liu +3
Early detection of patient deterioration is crucial for reducing mortality rates. Heart rate data has shown promise in assessing patient health, and wearable devices offer a cost-e…
Integrated Offline and Online Learning to Solve a Large Class of Scheduling Problems
Anbang Liu, Zhi-Long Chen, Jinyang Jiang +1
In this paper, we develop a unified machine learning (ML) approach to predict high-quality solutions for single-machine scheduling problems with a non-decreasing min-sum objective…