Dilated Convolution for Time Series Learning
Wang Zhang, Subhro Das, et al.
ICASSP 2025
We consider packet routing when packets are injected continuously into a network. We develop an adversarial theory of queuing aimed at addressing some of the restrictions inherent in probabilistic analysis and queuing theory based on time-invariant stochastic generation. We examine the stability of queuing networks and policies when the arrival process is adversarial, and provide some preliminary results in this direction. Our approach sheds light on various queuing policies in simple networks, and paves the way for a systematic study of queuing with few or no probabilistic assumptions.
Wang Zhang, Subhro Das, et al.
ICASSP 2025
Victor Akinwande, Megan Macgregor, et al.
IJCAI 2024
Xiaoxiao Guo, Shiyu Chang, et al.
AAAI 2019
Aditya Malik, Nalini Ratha, et al.
CAI 2024