Artikel mit Open-Access-Mandaten - Dixin Luo 罗迪新Weitere Informationen
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Self-supervised Video Summarization Guided by Semantic Inverse Optimal Transport
Y Wang, H Xu, D Luo
Proceedings of the 31st ACM International Conference on Multimedia, 6611-6622, 2023
Mandate: National Natural Science Foundation of China
Verfügbar: 17
Gromov-wasserstein learning for graph matching and node embedding
H Xu, D Luo, H Zha, LC Duke
International conference on machine learning, 6932-6941, 2019
Mandate: US National Science Foundation, US Department of Energy, US Department of …
Scalable Gromov-Wasserstein learning for graph partitioning and matching
H Xu, D Luo, L Carin
Advances in neural information processing systems 32, 2019
Mandate: US National Science Foundation, US Department of Energy, US Department of …
Learning Hawkes processes from short doubly-censored event sequences
H Xu, D Luo, H Zha
International Conference on Machine Learning, 3831-3840, 2017
Mandate: US National Science Foundation, US National Institutes of Health, National …
Multi-task multi-dimensional hawkes processes for modeling event sequences
D Luo, H Xu, Y Zhen, X Ning, H Zha, X Yang, W Zhang
ACM, 2015
Mandate: US National Institutes of Health, National Natural Science Foundation of China
Learning autoencoders with relational regularization
H Xu, D Luo, R Henao, S Shah, L Carin
International Conference on Machine Learning, 10576-10586, 2020
Mandate: US National Science Foundation, US Department of Energy, US Department of …
Learning graphons via structured gromov-wasserstein barycenters
H Xu, D Luo, L Carin, H Zha
Proceedings of the AAAI Conference on Artificial Intelligence 35 (12), 10505 …, 2021
Mandate: US National Science Foundation, US Department of Energy, US Department of …
Benefits from superposed hawkes processes
H Xu, D Luo, X Chen, L Carin
International Conference on Artificial Intelligence and Statistics, 623-631, 2018
Mandate: US National Science Foundation, US Department of Energy, US Department of …
Representing graphs via Gromov-Wasserstein factorization
H Xu, J Liu, D Luo, L Carin
IEEE Transactions on Pattern Analysis and Machine Intelligence 45 (1), 999-1016, 2022
Mandate: National Natural Science Foundation of China
Learning mixtures of markov chains from aggregate data with structural constraints
D Luo, H Xu, Y Zhen, B Dilkina, H Zha, X Yang, W Zhang
IEEE Transactions on Knowledge and Data Engineering 28 (6), 1518-1531, 2016
Mandate: US National Science Foundation, US National Institutes of Health, National …
Online Continuous-Time Tensor Factorization Based on Pairwise Interactive Point Processes.
H Xu, D Luo, L Carin
IJCAI, 2905-2911, 2018
Mandate: US National Science Foundation, US Department of Energy, US Department of …
Differentiable hierarchical optimal transport for robust multi-view learning
D Luo, H Xu, L Carin
IEEE Transactions on Pattern Analysis and Machine Intelligence 45 (6), 7293-7307, 2022
Mandate: National Natural Science Foundation of China
Weakly-supervised temporal action alignment driven by unbalanced spectral fused Gromov-Wasserstein distance
D Luo, Y Wang, A Yue, H Xu
Proceedings of the 30th ACM International Conference on Multimedia, 728-739, 2022
Mandate: National Natural Science Foundation of China
Dictionary learning with mutually reinforcing group-graph structures
H Xu, L Yu, D Luo, H Zha, Y Xu
Proceedings of the AAAI Conference on Artificial Intelligence 29 (1), 2015
Mandate: National Natural Science Foundation of China
Group Sparse Optimal Transport for Sparse Process Flexibility Design.
D Luo, T Yu, H Xu
IJCAI, 6121-6129, 2023
Mandate: National Natural Science Foundation of China
Inferring iterated function systems approximately from fractal images
H Liu, D Luo, H Xu
33rd International Joint Conference on Artificial Intelligence, IJCAI 2024 …, 2024
Mandate: National Natural Science Foundation of China
Coupled Point Process-based Sequence Modeling for Privacy-preserving Network Alignment.
D Luo, H Cheng, Q Li, H Xu
IJCAI, 6112-6120, 2023
Mandate: National Natural Science Foundation of China
Privacy-preserved evolutionary graph modeling via Gromov-Wasserstein autoregression
Y Xiang, D Luo, H Xu
Proceedings of the AAAI Conference on Artificial Intelligence 37 (12), 14566 …, 2023
Mandate: National Natural Science Foundation of China
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