受强制性开放获取政策约束的文章 - Tsung-Yu Hsieh了解详情
可在其他位置公开访问的文章：10 篇
Adversarial attacks on graph neural networks via node injections: A hierarchical reinforcement learning approach
Y Sun, S Wang, X Tang, TY Hsieh, V Honavar
Proceedings of the Web Conference 2020, 673-683, 2020
强制性开放获取政策： US National Science Foundation, US National Institutes of Health
Explainable multivariate time series classification: a deep neural network which learns to attend to important variables as well as time intervals
TY Hsieh, S Wang, Y Sun, V Honavar
Proceedings of the 14th ACM international conference on web search and data …, 2021
强制性开放获取政策： US National Science Foundation, US National Institutes of Health
Minority oversampling in kernel adaptive subspaces for class imbalanced datasets
CT Lin, TY Hsieh, YT Liu, YY Lin, CN Fang, YK Wang, G Yen, NR Pal, ...
IEEE Transactions on Knowledge and Data Engineering 30 (5), 950-962, 2017
强制性开放获取政策： US Department of Defense, Australian Research Council
Min-redundancy and max-relevance multi-view feature selection for predicting ovarian cancer survival using multi-omics data
Y El-Manzalawy, TY Hsieh, M Shivakumar, D Kim, V Honavar
BMC medical genomics 11, 19-31, 2018
强制性开放获取政策： US National Science Foundation, US National Institutes of Health
Non-target-specific node injection attacks on graph neural networks: A hierarchical reinforcement learning approach
Y Sun, S Wang, X Tang, TY Hsieh, V Honavar
Proc. WWW 3, 2020
强制性开放获取政策： US National Science Foundation, US National Institutes of Health
Multi-view network embedding via graph factorization clustering and co-regularized multi-view agreement
Y Sun, N Bui, TY Hsieh, V Honavar
2018 ieee international conference on data mining workshops (icdmw), 1006-1013, 2018
强制性开放获取政策： US National Science Foundation, US National Institutes of Health
Functional autoencoders for functional data representation learning
TY Hsieh, Y Sun, S Wang, V Honavar
Proceedings of the 2021 SIAM International Conference on Data Mining (SDM …, 2021
强制性开放获取政策： US National Science Foundation, US National Institutes of Health
Adaptive structural co-regularization for unsupervised multi-view feature selection
TY Hsieh, Y Sun, S Wang, V Honavar
2019 IEEE International Conference on Big Knowledge (ICBK), 87-96, 2019
强制性开放获取政策： US National Science Foundation, US National Institutes of Health
SrVARM: State regularized vector autoregressive model for joint learning of hidden state transitions and state-dependent inter-variable dependencies from multi-variate time series
TY Hsieh, Y Sun, X Tang, S Wang, VG Honavar
Proceedings of the Web Conference 2021, 2270-2280, 2021
强制性开放获取政策： US National Science Foundation, US National Institutes of Health
Compositional stochastic average gradient for machine learning and related applications
TY Hsieh, Y El-Manzalawy, Y Sun, V Honavar
Intelligent Data Engineering and Automated Learning–IDEAL 2018: 19th …, 2018
强制性开放获取政策： US National Science Foundation, US National Institutes of Health
出版信息和资助信息由计算机程序自动确定