Follow
Li-Ping Liu
Li-Ping Liu
Verified email at tufts.edu
Title
Cited by
Cited by
Year
A conditional multinomial mixture model for superset label learning
L Liu, T Dietterich
Advances in neural information processing systems 25, 2012
1732012
Learnability of the superset label learning problem
L Liu, T Dietterich
International Conference on Machine Learning, 1629-1637, 2014
742014
Incorporating boosted regression trees into ecological latent variable models
R Hutchinson, LP Liu, T Dietterich
Proceedings of the AAAI Conference on Artificial Intelligence 25 (1), 1343-1348, 2011
662011
Least square incremental linear discriminant analysis
LP Liu, Y Jiang, ZH Zhou
2009 Ninth IEEE International Conference on Data Mining, 298-306, 2009
532009
Gan ensemble for anomaly detection
X Han, X Chen, LP Liu
Proceedings of the AAAI Conference on Artificial Intelligence 35 (5), 4090-4097, 2021
342021
Tefe: A time-efficient approach to feature extraction
LP Liu, Y Yu, Y Jiang, ZH Zhou
2008 Eighth IEEE International Conference on Data Mining, 423-432, 2008
242008
Kriging convolutional networks
G Appleby, L Liu, LP Liu
Proceedings of the AAAI Conference on Artificial Intelligence 34 (04), 3187-3194, 2020
192020
Context selection for embedding models
L Liu, F Ruiz, S Athey, D Blei
Advances in Neural Information Processing Systems 30, 2017
172017
Transductive optimization of top k precision
LP Liu, TG Dietterich, N Li, ZH Zhou
arXiv preprint arXiv:1510.05976, 2015
172015
Gaussian approximation of collective graphical models
L Liu, D Sheldon, T Dietterich
International Conference on Machine Learning, 1602-1610, 2014
152014
Predicting physics in mesh-reduced space with temporal attention
X Han, H Gao, T Pffaf, JX Wang, LP Liu
arXiv preprint arXiv:2201.09113, 2022
112022
Zero-inflated exponential family embeddings
LP Liu, DM Blei
International Conference on Machine Learning, 2140-2148, 2017
102017
Stochastic iterative graph matching
L Liu, MC Hughes, S Hassoun, L Liu
International Conference on Machine Learning, 6815-6825, 2021
92021
Pathway-activity likelihood analysis and metabolite annotation for untargeted metabolomics using probabilistic modeling
R Hosseini, N Hassanpour, LP Liu, S Hassoun
Metabolites 10 (5), 183, 2020
82020
Amortized variational inference with graph convolutional networks for gaussian processes
L Liu, L Liu
The 22nd International Conference on Artificial Intelligence and Statistics …, 2019
82019
Constructing training sets for outlier detection
LP Liu, XZ Fern
Proceedings of the 2012 SIAM International Conference on Data Mining, 919-929, 2012
82012
Learning graph representations of biochemical networks and its application to enzymatic link prediction
J Jiang, LP Liu, S Hassoun
Bioinformatics 37 (6), 793-799, 2021
72021
Bayesian active clustering with pairwise constraints
Y Pei, LP Liu, XZ Fern
Machine Learning and Knowledge Discovery in Databases: European Conference …, 2015
62015
Order matters: Probabilistic modeling of node sequence for graph generation
X Chen, X Han, J Hu, FJR Ruiz, L Liu
arXiv preprint arXiv:2106.06189, 2021
52021
Using graph neural networks for mass spectrometry prediction
H Zhu, L Liu, S Hassoun
arXiv preprint arXiv:2010.04661, 2020
52020
The system can't perform the operation now. Try again later.
Articles 1–20