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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
1622012
Learnability of the superset label learning problem
L Liu, T Dietterich
International Conference on Machine Learning, 1629-1637, 2014
682014
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
512009
Gan ensemble for anomaly detection
X Han, X Chen, LP Liu
Proceedings of the AAAI Conference on Artificial Intelligence 35 (5), 4090-4097, 2021
252021
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
232008
Transductive optimization of top k precision
LP Liu, TG Dietterich, N Li, ZH Zhou
arXiv preprint arXiv:1510.05976, 2015
162015
Kriging convolutional networks
G Appleby, L Liu, LP Liu
Proceedings of the AAAI Conference on Artificial Intelligence 34 (04), 3187-3194, 2020
152020
Context selection for embedding models
L Liu, F Ruiz, S Athey, D Blei
Advances in Neural Information Processing Systems 30, 2017
152017
Gaussian approximation of collective graphical models
L Liu, D Sheldon, T Dietterich
International Conference on Machine Learning, 1602-1610, 2014
142014
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
Zero-inflated exponential family embeddings
LP Liu, DM Blei
International Conference on Machine Learning, 2140-2148, 2017
82017
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
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
72020
Bayesian active clustering with pairwise constraints
Y Pei, LP Liu, XZ Fern
Joint European Conference on Machine Learning and Knowledge Discovery in …, 2015
62015
Stochastic Iterative Graph Matching
L Liu, MC Hughes, S Hassoun, L Liu
International Conference on Machine Learning, 6815-6825, 2021
42021
Using Graph Neural Networks for Mass Spectrometry Prediction
H Zhu, L Liu, S Hassoun
arXiv preprint arXiv:2010.04661, 2020
42020
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
32022
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
32021
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