activity
20182021
most citedTowards Self-Adaptive Metric Learning On the Fly

11 citations · 13 across the 2 of their papers we have counts for

collaborators

7 papers

cs.IR20212 cited

SetConv: A New Approach for Learning from Imbalanced Data

Yang Gao, Yi-Fan Li, Yu Lin +2

For many real-world classification problems, e.g., sentiment classification, most existing machine learning methods are biased towards the majority class when the Imbalance Ratio (…

cs.LG202111 cited

Towards Self-Adaptive Metric Learning On the Fly

Yang Gao, Yi-Fan Li, Swarup Chandra +2

Good quality similarity metrics can significantly facilitate the performance of many large-scale, real-world applications. Existing studies have proposed various solutions to learn…

cs.LG2020

A Primal-Dual Subgradient Approachfor Fair Meta Learning

Chen Zhao, Feng Chen, Zhuoyi Wang +1

The problem of learning to generalize to unseen classes during training, known as few-shot classification, has attracted considerable attention. Initialization based methods, such…

cs.CR2020

Secure IoT Data Analytics in Cloud via Intel SGX

Md Shihabul Islam, Mustafa Safa Ozdayi, Latifur Khan +1

The growing adoption of IoT devices in our daily life is engendering a data deluge, mostly private information that needs careful maintenance and secure storage system to ensure da…

cs.IR2020

Deep Learning on Knowledge Graph for Recommender System: A Survey

Yang Gao, Yi-Fan Li, Yu Lin +2

Recent advances in research have demonstrated the effectiveness of knowledge graphs (KG) in providing valuable external knowledge to improve recommendation systems (RS). A knowledg…

cs.LG2018

Co-Representation Learning For Classification and Novel Class Detection via Deep Networks

Zhuoyi Wang, Zelun Kong, Hemeng Tao +2

One of the key challenges of performing label prediction over a data stream concerns with the emergence of instances belonging to unobserved class labels over time. Previously, thi…