Bo Dai
Bo Dai
Research Scientist, Google Brain
Verified email at - Homepage
Cited by
Cited by
Discriminative embeddings of latent variable models for structured data
H Dai, B Dai, L Song
International conference on machine learning, 2702-2711, 2016
Scalable kernel methods via doubly stochastic gradients
B Dai, B Xie, N He, Y Liang, A Raj, MF Balcan, L Song
arXiv preprint arXiv:1407.5599, 2014
Syntax-directed variational autoencoder for structured data
H Dai, Y Tian, B Dai, S Skiena, L Song
arXiv preprint arXiv:1802.08786, 2018
Sbeed: Convergent reinforcement learning with nonlinear function approximation
B Dai, A Shaw, L Li, L Xiao, N He, Z Liu, J Chen, L Song
International Conference on Machine Learning, 1125-1134, 2018
Learning from Conditional Distributions via Dual Embeddings
B Dai, N He, Y Pan, B Boots, L Song
arXiv preprint arXiv:1607.04579, 2016
Deep hyperspherical learning
W Liu, YM Zhang, X Li, Z Yu, B Dai, T Zhao, L Song
arXiv preprint arXiv:1711.03189, 2017
Information-theoretic semi-supervised metric learning via entropy regularization
G Niu, B Dai, M Yamada, M Sugiyama
Neural computation 26 (8), 1717-1762, 2014
Iterative machine teaching
W Liu, B Dai, A Humayun, C Tay, C Yu, LB Smith, JM Rehg, L Song
International Conference on Machine Learning, 2149-2158, 2017
Learning steady-states of iterative algorithms over graphs
H Dai, Z Kozareva, B Dai, A Smola, L Song
International conference on machine learning, 1106-1114, 2018
Learning towards minimum hyperspherical energy
W Liu, R Lin, Z Liu, L Liu, Z Yu, B Dai, L Song
arXiv preprint arXiv:1805.09298, 2018
DualDICE: Behavior-agnostic estimation of discounted stationary distribution corrections
O Nachum, Y Chow, B Dai, L Li
Advances in Neural Information Processing Systems, 2315-2325, 2019
Provable bayesian inference via particle mirror descent
B Dai, N He, H Dai, L Song
Artificial Intelligence and Statistics, 985-994, 2016
Stochastic generative hashing
B Dai, R Guo, S Kumar, N He, L Song
International Conference on Machine Learning, 913-922, 2017
Squared-loss mutual information regularization: A novel information-theoretic approach to semi-supervised learning
G Niu, W Jitkrittum, B Dai, H Hachiya, M Sugiyama
International Conference on Machine Learning, 10-18, 2013
Nonparametric estimation of multi-view latent variable models
L Song, A Anandkumar, B Dai, B Xie
International Conference on Machine Learning, 640-648, 2014
GenDICE: Generalized Offline Estimation of Stationary Values
R Zhang, B Dai, L Li, D Schuurmans
International Conference on Learning Representations, 2020
AlgaeDICE: Policy gradient from arbitrary experience
O Nachum, B Dai, I Kostrikov, Y Chow, L Li, D Schuurmans
arXiv preprint arXiv:1912.02074, 2019
Decoupled networks
W Liu, Z Liu, Z Yu, B Dai, R Lin, Y Wang, JM Rehg, L Song
Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2018
Boosting the actor with dual critic
B Dai, A Shaw, N He, L Li, L Song
arXiv preprint arXiv:1712.10282, 2017
Retrosynthesis prediction with conditional graph logic network
H Dai, C Li, CW Coley, B Dai, L Song
arXiv preprint arXiv:2001.01408, 2020
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