(KAIST-IBM) J. Yun, A. Lozano, E. Yang
Adaptive Proximal Gradient Methods for Structured Neural Networks,
Conference on Neural Information Processing Systems (NeurIPS) (2021)
(Chosun Univeristy-University of Ottawa) E. S-. Ko, M. McDonald
The efficacy of book reading in infants’ word learning is mediated by child-directed speech,
Asia Pacific Babylab Constellation (ABC) (2021)
(Chosun Univeristy-University of Ottawa) E. S-. Ko, M. McDonald
The eyes of preverbal infants reveal the effects of book reading on word learning,
The Society for Research in Child Development (SRCD) (2021)
(Chosun Univeristy-The University of Plymouth-Purdue University) E. S-. Ko, et al.
Mothers’ use of tactile cues for word learning is attuned to infants’ development,
Boston University Conference on Language Development (BUCLD46) (2021)
(KAIST-Caltech) Kim, D., Park, G. Y., O’Doherty J. P.*, Lee S. W.*
Task complexity interacts with state-space uncertainty in the arbitration process between model-based and model-free reinforcement-learning at both behavioral and neural levels.
Nature Communications. 10, 5738 (2019).
(KAIST-Caltech) O’Doherty J. P.*, Lee S. W., TadayonNejad R., Cockburn J., Iigaya K., Chrpentier C.
Why and how the brain weights contributions from a mixture of experts.
Neuroscience and Biobehavioral Reviews (2020)
(KAIST-NYU Shanghai) Zuo, S., Wang, L., Shin, J. H., Cai, Y., Lee, S. W., Appiah, K., Zhou, Y., Kwok S. C.
Behavioral evidence for memory replay of video episodes in the macaque.
eLife. 9, e54519 (2020).
(KAIST-U Zurich) Weissengruber S.+, Lee S. W.+, O'Doherty J, Ruff C.
Neurostimulation reveals context-dependent arbitration between model-based and model-free learning.
Cerebral Cortex . 29 (2019).
(KAIST-UCL) S. J. An, B. D. Martino, and S. W. Lee*
Metacognitive exploration in reinforcement learning.
4th Multi-disciplinary Conference on Reinforcement Learning and Decision Making (RLDM) (2019).
(KAIST-IBM) J. Yun, P. Zheng, A. Lozano, A. Aravkin and E. Yang
Trimming the l-1 Regularizer: Statistical Analysis, Optimization, and Applications to Deep Learning.
International Conference on Machine Learning (ICML) 36 (2019) (Oral, acceptance rate = 4.64%) .
(KAIST-IBM) J. Yun, A. Lozano and E. Yang
Stochastic Gradient Methods with Block Diagonal Matrix Adaptation.
arXiv preprint arXiv:1905.10757 (2019).
(KAIST-IBM) J. Yun, A. Lozano, E. Yang
A General Family of Stochastic Proximal Gradient Methods for Deep Learning.
arXiv preprint arXiv:2007.07484 (2020).
(고려대-Technische Universität Berlin) D.-O. Won, K.-R. Müller, and S.-W. Lee
An adaptive deep reinforcement learning framework enables curling robots with human-like performance in real world conditions.
Science Robotics. Vol. 5, Issue 46 (2020).
(KAIST-Columnbia) Sang-Eon Park, Tamara Gedankein, Joshua Jacobs, Sang Ah Lee
What human intracranial EEG reveals about the effects of aging on neurocognitive function.
한국뇌신경과학회 (2020)
