16 citations · 21 across the 4 of their papers we have counts for
5 papers
PBScaler: A Bottleneck-aware Autoscaling Framework for Microservice-based Applications
Shuaiyu Xie, Jian Wang, Bing Li +3
Autoscaling is critical for ensuring optimal performance and resource utilization in cloud applications with dynamic workloads. However, traditional autoscaling technologies are ty…
Speaker Diarization: Using Recurrent Neural Networks
Vishal Sharma, Zekun Zhang, Zachary Neubert +1
Speaker Diarization is the problem of separating speakers in an audio. There could be any number of speakers and final result should state when speaker starts and ends. In this pro…
Adversarial Distillation for Ordered Top-k Attacks
Zekun Zhang, Tianfu Wu
Deep Neural Networks (DNNs) are vulnerable to adversarial attacks, especially white-box targeted attacks. One scheme of learning attacks is to design a proper adversarial objective…
Knowledge Distillation for Human Action Anticipation
Vinh Tran, Yang Wang, Minh Hoai
We consider the task of training a neural network to anticipate human actions in video. This task is challenging given the complexity of video data, the stochastic nature of the fu…
Unsupervised Abstractive Meeting Summarization with Multi-Sentence Compression and Budgeted Submodular Maximization
Guokan Shang, Wensi Ding, Zekun Zhang +4
We introduce a novel graph-based framework for abstractive meeting speech summarization that is fully unsupervised and does not rely on any annotations. Our work combines the stren…