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Sung-Hyun Son
Sung-Hyun Son
MIT Lincoln Laboratory
Verified email at ll.mit.edu
Title
Cited by
Cited by
Year
The value of clustering in distributed estimation for sensor networks
SH Son, M Chiang, SR Kulkarni, SC Schwartz
2005 International Conference on Wireless Networks, Communications and …, 2005
512005
Apprenticeship scheduling: Learning to schedule from human experts
M Gombolay, R Jensen, J Stigile, SH Son, J Shah
AAAI Press/international joint conferences on artificial intelligence, 2016
402016
Optimization methods for interpretable differentiable decision trees applied to reinforcement learning
A Silva, M Gombolay, T Killian, I Jimenez, SH Son
International conference on artificial intelligence and statistics, 1855-1865, 2020
312020
Human-machine collaborative optimization via apprenticeship scheduling
M Gombolay, R Jensen, J Stigile, T Golen, N Shah, SH Son, J Shah
Journal of Artificial Intelligence Research 63, 1-49, 2018
282018
Communication-estimation tradeoffs in wireless sensor networks
SH Son, SR Kulkarni, SC Schwartz, M Roan
Proceedings.(ICASSP'05). IEEE International Conference on Acoustics, Speech …, 2005
172005
Optimization methods for interpretable differentiable decision trees in reinforcement learning
A Silva, T Killian, IDJ Rodriguez, SH Son, M Gombolay
arXiv preprint arXiv:1903.09338, 2019
16*2019
Machine learning techniques for analyzing training behavior in serious gaming
MC Gombolay, RE Jensen, SH Son
IEEE Transactions on Games 11 (2), 109-120, 2017
142017
Learning to infer final plans in human team planning
J Kim, ME Woicik, MC Gombolay, SH Son, JA Shah
International Joint Conferences on Artificial Intelligence, 2018
112018
Learning to tutor from expert demonstrators via apprenticeship scheduling
M Gombolay, R Jensen, J Stigile, SH Son, J Shah
Association for the Advancement of Artificial Intelligence, 2017
42017
Kernelized capsule networks
T Killian, J Goodwin, O Brown, SH Son
arXiv preprint arXiv:1906.03164, 2019
32019
Clustering in distributed incremental estimation in wireless sensor networks
SH Son, M Chiang, SR Kulkarni, SC Schwartz
3
Safe predictors for enforcing input-output specifications
S Mell, O Brown, J Goodwin, SH Son
arXiv preprint arXiv:2001.11062, 2020
22020
Optimization methods for interpretable differentiable decision trees applied to reinforcement learning. volume 108 of Proceedings of Machine Learning Research
A Silva, M Gombolay, T Killian, I Jimenez, SH Son
Online, 2020
12020
Interpretable reinforcement learning via differentiable decision trees
ID Jimenez Rodriguez, T Killian, SH Son, M Gombolay
arXiv preprint arXiv:1903.09338, 2019
12019
Machine Learning for Education: Learning to Teach
MC Gombolay, R Jensen, SH Son
MASSACHUSETTS INST OF TECH LEXINGTON LEXINGTON United States, 2016
12016
Learning Robust Representations for Automatic Target Recognition
JA Goodwin, OM Brown, TW Killian, SH Son
arXiv preprint arXiv:1811.10714, 2018
2018
Learning Robust Representations for Automatic Target Recognition: FY18 Line-Supported Information, Computation and Exploitation Program
JA Goodwin, OM Brown, TW Killian, SH Son
MIT Lincoln Laboratory, 2018
2018
Apprenticeship Learning: Learning to Schedule from Human Experts
MC Gombolay, J Shah, J Stigile, SH Son, RE Jensen
MASSACHUSETTS INST OF TECH LEXINGTON LEXINGTON United States, 2016
2016
Distributed estimation with dependent observations in wireless sensor networks
SH Son, SR Kulkarni, SC Schwartz
2006 14th European Signal Processing Conference, 1-5, 2006
2006
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Articles 1–19