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, TG Dietterich
Advances in neural information processing systems, 548-556, 2012
1122012
Least square incremental linear discriminant analysis
LP Liu, Y Jiang, ZH Zhou
2009 Ninth IEEE International Conference on Data Mining, 298-306, 2009
482009
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), 2011
432011
Learnability of the superset label learning problem
L Liu, T Dietterich
International Conference on Machine Learning, 1629-1637, 2014
422014
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
212008
Transductive optimization of top k precision
LP Liu, TG Dietterich, N Li, ZH Zhou
arXiv preprint arXiv:1510.05976, 2015
152015
Gaussian approximation of collective graphical models
L Liu, D Sheldon, T Dietterich
International Conference on Machine Learning, 1602-1610, 2014
152014
Context selection for embedding models
LP Liu, FJR Ruiz, S Athey, DM Blei
Proceedings of the 31st International Conference on Neural Information …, 2017
102017
Zero-inflated exponential family embeddings
LP Liu, DM Blei
International Conference on Machine Learning, 2140-2148, 2017
62017
Bayesian active clustering with pairwise constraints
Y Pei, LP Liu, XZ Fern
Joint European Conference on Machine Learning and Knowledge Discovery in …, 2015
62015
Constructing training sets for outlier detection
LP Liu, XZ Fern
Proceedings of the 2012 SIAM International Conference on Data Mining, 919-929, 2012
62012
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
32020
Amortized variational inference with graph convolutional networks for gaussian processes
L Liu, L Liu
The 22nd International Conference on Artificial Intelligence and Statistics …, 2019
22019
Linear transformation of multivariate normal distribution: marginal, joint and posterior
LP Liu, Σ Σxat, A Aσxat
22019
Kriging Convolutional Networks
G Appleby, L Liu, LP Liu
Proceedings of the AAAI Conference on Artificial Intelligence 34 (04), 3187-3194, 2020
12020
Learning graph representations of biochemical networks and its application to enzymatic link prediction
J Jiang, LP Liu, S Hassoun
arXiv preprint arXiv:2002.03410, 2020
12020
GAN Ensemble for Anomaly Detection
X Han, X Chen, LP Liu
arXiv preprint arXiv:2012.07988, 2020
2020
Using Graph Neural Networks for Mass Spectrometry Prediction
H Zhu, L Liu, S Hassoun
arXiv preprint arXiv:2010.04661, 2020
2020
Localizing and Amortizing: Efficient Inference for Gaussian Processes
L Liu, L Liu
Asian Conference on Machine Learning, 823-836, 2020
2020
Pathway Activity Analysis and Metabolite Annotation for Untargeted Metabolomics using Probabilistic Modeling.
R Hosseini, N Hassanpour, LP Liu, S Hassoun
CoRR, 2019
2019
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Articles 1–20