Stebėti
Le Song
Le Song
Biomap, Mohamed bin Zayed University of Artificial Intelligence
Patvirtintas el. paštas biomap.com - Pagrindinis puslapis
Pavadinimas
Cituota
Cituota
Metai
Sphereface: Deep hypersphere embedding for face recognition
W Liu, Y Wen, Z Yu, M Li, B Raj, L Song
Proceedings of the IEEE conference on computer vision and pattern …, 2017
35632017
Learning combinatorial optimization algorithms over graphs
E Khalil, H Dai, Y Zhang, B Dilkina, L Song
Advances in neural information processing systems 30, 2017
18122017
A kernel statistical test of independence
A Gretton, K Fukumizu, C Teo, L Song, B Schölkopf, A Smola
Advances in neural information processing systems 20, 2007
11062007
A Hilbert space embedding for distributions
A Smola, A Gretton, L Song, B Schölkopf
International conference on algorithmic learning theory, 13-31, 2007
10432007
Adversarial attack on graph structured data
H Dai, H Li, T Tian, X Huang, L Wang, J Zhu, L Song
International conference on machine learning, 1115-1124, 2018
8852018
Discriminative embeddings of latent variable models for structured data
H Dai, B Dai, L Song
International conference on machine learning, 2702-2711, 2016
8692016
GRAM: graph-based attention model for healthcare representation learning
E Choi, MT Bahadori, L Song, WF Stewart, J Sun
Proceedings of the 23rd ACM SIGKDD international conference on knowledge …, 2017
7862017
Recurrent marked temporal point processes: Embedding event history to vector
N Du, H Dai, R Trivedi, U Upadhyay, M Gomez-Rodriguez, L Song
Proceedings of the 22nd ACM SIGKDD international conference on knowledge …, 2016
7842016
Neural network-based graph embedding for cross-platform binary code similarity detection
X Xu, C Liu, Q Feng, H Yin, L Song, D Song
Proceedings of the 2017 ACM SIGSAC conference on computer and communications …, 2017
7522017
Scientific discovery in the age of artificial intelligence
H Wang, T Fu, Y Du, W Gao, K Huang, Z Liu, P Chandak, S Liu, ...
Nature 620 (7972), 47-60, 2023
7352023
Learning to explain: An information-theoretic perspective on model interpretation
J Chen, L Song, M Wainwright, M Jordan
International conference on machine learning, 883-892, 2018
7112018
Stochastic training of graph convolutional networks with variance reduction
J Chen, J Zhu, L Song
arXiv preprint arXiv:1710.10568, 2017
6342017
Know-evolve: Deep temporal reasoning for dynamic knowledge graphs
R Trivedi, H Dai, Y Wang, L Song
international conference on machine learning, 3462-3471, 2017
6022017
Variational reasoning for question answering with knowledge graph
Y Zhang, H Dai, Z Kozareva, A Smola, L Song
Proceedings of the AAAI conference on artificial intelligence 32 (1), 2018
5382018
Feature Selection via Dependence Maximization.
L Song, A Smola, A Gretton, J Bedo, K Borgwardt
Journal of Machine Learning Research 13 (5), 2012
5032012
Learning to branch in mixed integer programming
E Khalil, P Le Bodic, L Song, G Nemhauser, B Dilkina
Proceedings of the AAAI conference on artificial intelligence 30 (1), 2016
4822016
Supervised feature selection via dependence estimation
L Song, A Smola, A Gretton, KM Borgwardt, J Bedo
Proceedings of the 24th international conference on Machine learning, 823-830, 2007
4742007
Learning social infectivity in sparse low-rank networks using multi-dimensional hawkes processes
K Zhou, H Zha, L Song
Artificial intelligence and statistics, 641-649, 2013
4602013
Hilbert space embeddings of conditional distributions with applications to dynamical systems
L Song, J Huang, A Smola, K Fukumizu
Proceedings of the 26th Annual International Conference on Machine Learning …, 2009
4122009
Syntax-directed variational autoencoder for structured data
H Dai, Y Tian, B Dai, S Skiena, L Song
arXiv preprint arXiv:1802.08786, 2018
4112018
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