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Osonde Osoba
Person information
- affiliation: RAND Corporation, Santa Monica, CA, USA
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2020 – today
- 2024
- [i8]Saikrishna Badrinarayanan, Osonde Osoba, Miao Cheng, Ryan Rogers, Sakshi Jain, Rahul Tandra, Natesh S. Pillai:
Privacy-Preserving Race/Ethnicity Estimation for Algorithmic Bias Measurement in the U.S. CoRR abs/2409.04652 (2024) - 2021
- [c9]Shiva Navabi, Osonde A. Osoba:
A Generative Machine Learning Approach to Policy Optimization in Pursuit-Evasion Games. CDC 2021: 69-76 - 2020
- [j6]Bart Kosko, Kartik Audhkhasi
, Osonde Osoba:
Noise can speed backpropagation learning and deep bidirectional pretraining. Neural Networks 129: 359-384 (2020) - [c8]Osonde A. Osoba:
Technocultural Pluralism: A "Clash of Civilizations" in Technology? AIES 2020: 132-137 - [c7]Osonde A. Osoba, Benjamin Boudreaux, Douglas Yeung:
Steps Towards Value-Aligned Systems. AIES 2020: 332-336 - [c6]Osonde A. Osoba, Raffaele Vardavas, Justin Grana, Rushil Zutshi, Amber Jaycocks:
Modeling Agent Behaviors for Policy Analysis via Reinforcement Learning. ICMLA 2020: 213-219 - [i7]Osonde A. Osoba, Benjamin Boudreaux, Douglas Yeung:
Steps Towards Value-Aligned Systems. CoRR abs/2002.05672 (2020) - [i6]Osonde A. Osoba, Raffaele Vardavas, Justin Grana, Rushil Zutshi, Amber Jaycocks:
Policy-focused Agent-based Modeling using RL Behavioral Models. CoRR abs/2006.05048 (2020) - [i5]Shiva Navabi, Osonde A. Osoba:
A Generative Machine Learning Approach to Policy Optimization in Pursuit-Evasion Games. CoRR abs/2010.01711 (2020) - [i4]Gavin S. Hartnett, Raffaele Vardavas, Lawrence Baker, Michael Chaykowsky, C. Ben Gibson, Federico Girosi, David P. Kennedy, Osonde A. Osoba:
Deep Generative Modeling in Network Science with Applications to Public Policy Research. CoRR abs/2010.07870 (2020)
2010 – 2019
- 2019
- [i3]Osonde Osoba, Bart Kosko:
Beyond DAGs: Modeling Causal Feedback with Fuzzy Cognitive Maps. CoRR abs/1906.11247 (2019) - 2018
- [i2]Osonde Osoba, Bart Kosko:
Noisy Expectation-Maximization: Applications and Generalizations. CoRR abs/1801.04053 (2018) - 2016
- [j5]Kartik Audhkhasi, Osonde Osoba, Bart Kosko:
Noise-enhanced convolutional neural networks. Neural Networks 78: 15-23 (2016) - 2014
- [i1]Osonde Adekorede Osoba:
Noise Benefits in Expectation-Maximization Algorithms. CoRR abs/1411.6622 (2014) - 2013
- [j4]Osonde Osoba, Bart Kosko:
Noise-enhanced clustering and competitive learning algorithms. Neural Networks 37: 132-140 (2013) - [j3]Osonde Osoba, Bart Kosko:
Corrigendum to "Noise enhanced clustering and competitive learning algorithms" [Neural Networks 37 (2013) 132-140]. Neural Networks 48: 206 (2013) - [c5]Kartik Audhkhasi, Osonde Osoba, Bart Kosko:
Noise benefits in backpropagation and deep bidirectional pre-training. IJCNN 2013: 1-8 - [c4]Kartik Audhkhasi, Osonde Osoba, Bart Kosko:
Noisy hidden Markov models for speech recognition. IJCNN 2013: 1-6 - 2012
- [j2]Osonde Osoba, Sanya Mitaim, Bart Kosko:
Triply fuzzy function approximation for hierarchical Bayesian inference. Fuzzy Optim. Decis. Mak. 11(3): 241-268 (2012) - 2011
- [j1]Osonde Osoba, Sanya Mitaim, Bart Kosko:
Bayesian Inference With Adaptive Fuzzy Priors and Likelihoods. IEEE Trans. Syst. Man Cybern. Part B 41(5): 1183-1197 (2011) - [c3]Osonde Osoba, Sanya Mitaim, Bart Kosko:
Triply fuzzy function approximation for Bayesian inference. IJCNN 2011: 3105-3111 - [c2]Osonde Osoba, Sanya Mitaim, Bart Kosko:
Noise benefits in the expectation-maximization algorithm: Nem theorems and models. IJCNN 2011: 3178-3183
2000 – 2009
- 2009
- [c1]Osonde Osoba, Sanya Mitaim, Bart Kosko:
Adaptive fuzzy priors for Bayesian inference. IJCNN 2009: 2380-2387
Coauthor Index
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