复旦大学数字信号处理与传输实验室的谌达同学论文"Active Anomaly Detection With Switching Cost"被IEEE International Conference on Acoustics, Speech, and Signal Processing(ICASSP) 2019录用。
论文摘要：The problem of anomaly detection among multiple processes is considered within the framework of sequential design of experiments. The objective is an active inference strategy consisting of a selection rule governing which process to probe at each time, a stopping rule on when to terminate the detection, and a decision rule on the final detection outcome. The performance measure is the Bayes risk that takes into account of not only sample complexity and detection errors, but also costs associated with switching across processes. While the problem is a partially observable Markov decision process to which optimal solutions are generally intractable, a low-complexity deterministic policy is shown to be asymptotically optimal and offer significant performance improvement over existing methods in the finite regime.
论文作者：Da Chen, Qiwei Huang, Hui Feng, Qing Zhao, Bo Hu