1.1k citations · 3.2k across the 78 of their papers we have counts for
7 papers · 1 filter
Unsupervised Detection of Sub-events in Large Scale Disasters
Chidubem Arachie, Manas Gaur, Sam Anzaroot +3
Social media plays a major role during and after major natural disasters (e.g., hurricanes, large-scale fires, etc.), as people ``on the ground'' post useful information on what is…
DeepAuto: A Hierarchical Deep Learning Framework for Real-Time Prediction in Cellular Networks
Abhijeet Bhorkar, Ke Zhang, Jin Wang
Accurate real-time forecasting of key performance indicators (KPIs) is an essential requirement for various LTE/5G radio access network (RAN) automation. However, an accurate predi…
Competing Ratio Loss for Discriminative Multi-class Image Classification
Ke Zhang, Yurong Guo, Xinsheng Wang +4
The development of deep convolutional neural network architecture is critical to the improvement of image classification task performance. Many image classification studies use dee…
Nanoconfined, dynamic electrolyte gating and memory effects in multilayered graphene-based membranes
Jing Xiao, Hualin Zhan, Zaiquan Xu +6
Multilayered graphene-based nanoporous membranes with electrolyte incorporated between individual sheets is a unique nano-heterostructure system in which nanoconfined electrons in…
Universal precursor seismicity pattern before locked-segment rupture
Chen Hongran, Qin Siqing, Xue Lei +2
Despite the enormous efforts towards searching for precursors, no precursors have exhibited real predictive power with respect to an earthquake thus far. Seismogenic locked segment…
Controllable Length Control Neural Encoder-Decoder via Reinforcement Learning
Junyi Bian, Baojun Lin, Ke Zhang +3
Controlling output length in neural language generation is valuable in many scenarios, especially for the tasks that have length constraints. A model with stronger length control c…
Competing Ratio Loss for Discriminative Multi-class Image Classification
Ke Zhang, Xinsheng Wang, Yurong Guo +3
The development of deep convolutional neural network architecture is critical to the improvement of image classification task performance. A lot of studies of image classification…