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
972012
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.
RA Hutchinson, LP Liu, TG Dietterich
AAAI 11, 1343-1348, 2011
422011
Learnability of the superset label learning problem
L Liu, T Dietterich
International Conference on Machine Learning, 1629-1637, 2014
352014
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
172008
Gaussian approximation of collective graphical models
L Liu, D Sheldon, T Dietterich
International Conference on Machine Learning, 1602-1610, 2014
142014
Context selection for embedding models
L Liu, F Ruiz, S Athey, D Blei
Advances in Neural Information Processing Systems, 4816-4825, 2017
102017
Transductive optimization of top k precision
LP Liu, TG Dietterich, N Li, ZH Zhou
arXiv preprint arXiv:1510.05976, 2015
102015
Constructing training sets for outlier detection
LP Liu, XZ Fern
Proceedings of the 2012 SIAM International Conference on Data Mining, 919-929, 2012
62012
Zero-inflated exponential family embeddings
LP Liu, DM Blei
International Conference on Machine Learning, 2140-2148, 2017
52017
Bayesian active clustering with pairwise constraints
Y Pei, LP Liu, XZ Fern
Joint European Conference on Machine Learning and Knowledge Discovery in …, 2015
52015
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
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
12020
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
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
2020
Kriging Convolutional Networks.
G Appleby, L Liu, L Liu
AAAI, 3187-3194, 2020
2020
Pathway Activity Analysis and Metabolite Annotation for Untargeted Metabolomics using Probabilistic Modeling
R Hosseini, N Hassanpour, LP Liu, S Hassoun
arXiv preprint arXiv:1912.05753, 2019
2019
Machine Learning Methods for Computational Sustainability
L Liu
2016
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Articles 1–19