activity
20192022
most citedConsistency-based Semi-supervised Active Learning: Towards Minimizing Labeling Cost

13 citations · 23 across the 5 of their papers we have counts for

collaborators

5 papers

cs.LG2022

An Interpretable Hybrid Predictive Model of COVID-19 Cases using Autoregressive Model and LSTM

Yangyi Zhang, Sui Tang, Guo Yu

The Coronavirus Disease 2019 (COVID-19) has a profound impact on global health and economy, making it crucial to build accurate and interpretable data-driven predictive models for…

cs.NE2022★ 4 cited

Survey on Evolutionary Deep Learning: Principles, Algorithms, Applications and Open Issues

Nan Li, Lianbo Ma, Guo Yu +3

Over recent years, there has been a rapid development of deep learning (DL) in both industry and academia fields. However, finding the optimal hyperparameters of a DL model often n…

cs.LG2021★ 3 cited

Pareto-wise Ranking Classifier for Multi-objective Evolutionary Neural Architecture Search

Lianbo Ma, Nan Li, Guo Yu +3

In the deployment of deep neural models, how to effectively and automatically find feasible deep models under diverse design objectives is fundamental. Most existing neural archite…

cs.LG2021★ 3 cited

Tiny Adversarial Mulit-Objective Oneshot Neural Architecture Search

Guoyang Xie, Jinbao Wang, Guo Yu +2

Due to limited computational cost and energy consumption, most neural network models deployed in mobile devices are tiny. However, tiny neural networks are commonly very vulnerable…

cs.LG2019★ 13 cited

Consistency-based Semi-supervised Active Learning: Towards Minimizing Labeling Cost

Mingfei Gao, Zizhao Zhang, Guo Yu +3

Active learning (AL) combines data labeling and model training to minimize the labeling cost by prioritizing the selection of high value data that can best improve model performanc…