135 citations · 572 across the 19 of their papers we have counts for
8 papers · 1 filter
Learning to Stop While Learning to Predict
Xinshi Chen, Hanjun Dai, Yu Li +2
There is a recent surge of interest in designing deep architectures based on the update steps in traditional algorithms, or learning neural networks to improve and replace traditio…
RNA Secondary Structure Prediction By Learning Unrolled Algorithms
Xinshi Chen, Yu Li, Ramzan Umarov +2
In this paper, we propose an end-to-end deep learning model, called E2Efold, for RNA secondary structure prediction which can effectively take into account the inherent constraints…
Robust Cost-Sensitive Learning for Recommendation with Implicit Feedback
Peng Yang, Peilin Zhao, Xin Gao +1
Recommendation is the task of improving customer experience through personalized recommendation based on users' past feedback. In this paper, we investigate the most common scenari…
Robust Online Multi-Task Learning with Correlative and Personalized Structures
Peng Yang, Peilin Zhao, Xin Gao
Multi-Task Learning (MTL) can enhance a classifier's generalization performance by learning multiple related tasks simultaneously. Conventional MTL works under the offline or batch…
Regularized maximum correntropy machine
Jim Jing-Yan Wang, Yunji Wang, Bing-Yi Jing +1
In this paper we investigate the usage of regularized correntropy framework for learning of classifiers from noisy labels. The class label predictors learned by minimizing transiti…
Learning manifold to regularize nonnegative matrix factorization
Jim Jing-Yan Wang, Xin Gao
Inthischapterwediscusshowtolearnanoptimalmanifoldpresentationto regularize nonegative matrix factorization (NMF) for data representation problems. NMF,whichtriestorepresentanonnega…