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Ehimwenma Nosakhare
Ehimwenma Nosakhare
Microsoft, MIT EECS
Verified email at mit.edu
Title
Cited by
Cited by
Year
Personalized multitask learning for predicting tomorrow's mood, stress, and health
S Taylor, N Jaques, E Nosakhare, A Sano, R Picard
IEEE Transactions on Affective Computing 11 (2), 200-213, 2017
2612017
Multi-task learning for predicting health, stress, and happiness
N Jaques, S Taylor, E Nosakhare, A Sano, R Picard
NIPS Workshop on Machine Learning for Healthcare 34, 2016
762016
Toward assessing and recommending combinations of behaviors for improving health and well-being
E Nosakhare, R Picard
ACM Transactions on Computing for Healthcare 1 (1), 1-29, 2020
332020
Seagull: An infrastructure for load prediction and optimized resource allocation
O Poppe, T Amuneke, D Banda, A De, A Green, M Knoertzer, ...
arXiv preprint arXiv:2009.12922, 2020
142020
Probabilistic latent variable modeling for assessing behavioral influences on well-being
E Nosakhare, R Picard
Proceedings of the 25th ACM SIGKDD International Conference on Knowledge …, 2019
132019
Share the tensor tea: how databases can leverage the machine learning ecosystem
Y Asada, V Fu, A Gandhi, A Gemawat, L Zhang, D He, V Gupta, ...
arXiv preprint arXiv:2209.04579, 2022
112022
0795 Importance of Sleep Data in Predicting Next-Day Stress, Happiness, and Health in College Students
S Taylor, N Jaques, E Nosakhare, A Sano, EB Klerman, RW Picard
Journal of Sleep and Sleep Disorders Research 40 (suppl_1), A294-A295, 2017
82017
Strategies to improve few-shot learning for intent classification and slot-filling
S Basu, A Sharaf, KIK Chong, A Fischer, V Rohra, M Amoake, ...
Proceedings of the Workshop on Structured and Unstructured Knowledge …, 2022
42022
Semi-supervised few-shot intent classification and slot filling
S Basu, A Sharaf, A Fischer, V Rohra, M Amoake, H El-Hammamy, ...
arXiv preprint arXiv:2109.08754, 2021
42021
Qt interval adaptation to changes in autonomic balance
E Nosakhare, GC Verghese, RC Tasker, T Heldt
Computing in Cardiology 2014, 605-608, 2014
42014
Karine lp Kiun Chong, Amr Sharaf, Alex Fischer, Vishal Rohra, Michael Amoake, Hazem El-Hammamy, Ehi Nosakhare, Vijay Ramani, and Benjamin Han. 2021
S Basu
Semi-supervised few-shot intent classification and slot filling. CoRR, abs …, 0
4
Multi-task Learning for Predicting Health
N Jaques, S Taylor, E Nosakhare, A Sano, R Picard
Stress, and Happiness 38, 2016
32016
Importance of Sleep Data in Predicting Next-Day Stress, Happiness, and Health in College Students
N Jaques, S Taylor, E Nosakhare, A Sano, EB Klerman, R Picard
Journal of Sleep and Sleep Disorders Research 40, 0
1
SLATE: A Sequence Labeling Approach for Task Extraction from Free-form Inked Content
A Gandhi, R Serrao, B Fang, G Antonius, J Hong, TM Nguyen, S Yi, ...
arXiv preprint arXiv:2211.04454, 2022
2022
Strategies to Improve Few-shot Learning for Intent Classification and Slot-Filling
M Amoake, H El-Hammamy, E Nosakhare, V Ramani, B Han
SUKI 2022, 17, 2022
2022
Probabilistic latent variable modeling for predicting future well-being and assessing behavioral influences on mood, stress and health
E Nosakhare
Massachusetts Institute of Technology, 2018
2018
Semi-Supervised Few-Shot Intent Classification and Slot Filling
M Amoake, H El-Hammamy, E Nosakhare, V Ramani, B Han
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