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Ying Zhao 0006
Person information
- affiliation: Naval Postgraduate School, Monterey, CA, USA
- affiliation (former): Quantum Intelligence, Inc., Santa Clara, CA, USA
- affiliation (former): MIT, Artificial Intelligence Laboratory, Cambridge, MA, USA
- affiliation (former): BBN Systems and Technologies, Cambridge, MA, USA
Other persons with the same name
- Ying Zhao — disambiguation page
- Ying Zhao 0001
— Central South University, School of Information Science and Engineering, Changsha, China
- Ying Zhao 0002
- Ying Zhao 0003
- Ying Zhao 0004
- Ying Zhao 0005 — University of Wollongong, School of Software Engineering and Computer Science, NSW, Australia
- Ying Zhao 0007
- Ying Zhao 0008 — Tsinghua University, Beijing, China (and 1 more)
- Ying Zhao 0009
- Ying Zhao 0010
- Ying Zhao 0011 — Beijing University of Chemical Technology, Beijing, China
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2020 – today
- 2023
- [c34]Ying Zhao
Quantum Theoretic Values of Collaborative and Self-organizing Agents. ASONAM 2023: 678-685 - 2022
- [c33]Ying Zhao, Erik Hemberg, Nate Derbinsky, Gabino Mata, Una-May O'Reilly:
Using domain knowledge in coevolution and reinforcement learning to simulate a logistics enterprise. GECCO Companion 2022: 514-517 - 2021
- [c32]Ying Zhao, Erik Hemberg, Nate Derbinsky, Gabino Mata, Una-May O'Reilly:
Simulating a logistics enterprise using an asymmetrical wargame simulation with soar reinforcement learning and coevolutionary algorithms. GECCO Companion 2021: 1907-1915 - [c31]Claire Dyer, Brian Wood, Ying Zhao, Douglas J. MacKinnon:
Determining Policy Communication Effectiveness: A Lexical Link Analysis Approach. KDIR 2021: 103-109 - 2020
- [c30]Ying Zhao, Gabe E. Mata:
Leverage Artificial Intelligence to Learn, Optimize, and Win (LAILOW) for the Marine Maintenance and Supply Complex System. ASONAM 2020: 678-684 - [c29]Ying Zhao
Deep Analytics for Management and Cybersecurity of the National Energy Grid. ICCS (5) 2020: 302-315
2010 – 2019
- 2019
- [j5]Ying Zhao, Arjuna Flenner:
Deep Models, Machine Learning, and Artificial Intelligence Applications in National and International Security. AI Mag. 40(1): 35-36 (2019) - [j4]Ying Zhao, Arjuna Flenner:
Deep Models, Machine Learning, and Artificial Intelligence Applications in National and International Security Part Two. AI Mag. 40(2): 29-30 (2019) - [c28]Ying Zhao, Charles C. Zhou, Sihui Huang:
Theory and use case of game-theoretic lexical link analysis. ASONAM 2019: 717-720 - [c27]Ying Zhao, Tony Kendall, Riqui Schwamm:
Measures of Effectiveness (MoEs) for MarineNet: A Case Study for a Smart e-Learning Organization. KMIS 2019: 146-156 - [c26]Ying Zhao, Jacob Jones, Douglas J. MacKinnon:
Causal Learning to Discover Supply Chain Vulnerability. KDIR 2019: 305-309 - [c25]Ying Zhao, Ralucca Gera
Visualization Techniques for Network Analysis and Link Analysis Algorithms. KDIR 2019: 561-568 - [c24]Ying Zhao
Collaborative Learning Agents (CLA) for Swarm Intelligence and Applications to Health Monitoring of System of Systems. ICCS (3) 2019: 706-718 - 2018
- [j3]Arjuna Flenner, Marlena R. Fraune, Laura M. Hiatt, Tony Kendall, John E. Laird
Reports of the AAAI 2017 Fall Symposium Series. AI Mag. 39(2): 81-86 (2018) - [c23]Ying Zhao, Andrew Polk, Shaun Kallis, Lauren Jones, Riqui Schwamm, Tony Kendall:
Data and Deep Models Applied to Cyber Security Data Analysis. AAAI Fall Symposium: ALEC 2018: 36-40 - [c22]Ying Zhao, Charles C. Zhou:
A Game-Theoretic Lexical Link Analysis for Discovering High-Value Information from Big Data. ASONAM 2018: 621-625 - [c21]Ying Zhao, Charles C. Zhou, Jennie K. Bellonio:
Multilayer Value Metrics Using Lexical Link Analysis and Game Theory for Discovering Innovation from Big Data and Crowd-Sourcing. ASONAM 2018: 1145-1151 - [c20]Ying Zhao, Charles Zhou, Jennie K. Bellonio:
New Value Metrics using Unsupervised Machine Learning, Lexical Link Analysis and Game Theory for Discovering Innovation from Big Data and Crowd-sourcing. KEOD 2018: 325-332 - 2017
- [c19]Quinn Halpin, Ying Zhao, Anthony Kendall:
Using D3 to Visualize Lexical Link Analysis (LLA) and ADS-B Data. AAAI Fall Symposia 2017: 206-209 - [c18]Ryan Salcido, Anthony Kendall, Ying Zhao:
Analysis of Automatic Dependent Surveillance-Broadcast Data. AAAI Fall Symposia 2017: 225-230 - [c17]Richard Wu, Ying Zhao, Alan Clarke, Anthony Kendall:
A Framework Using Machine Vision and Deep Reinforcement Learning for Self-Learning Moving Objects in a Virtual Environment. AAAI Fall Symposia 2017: 231-237 - [c16]Ying Zhao, Douglas J. MacKinnon, Charles C. Zhou:
Discovering High-Value Information from Crowdsourcing. ASONAM 2017: 585-588 - [c15]Ying Zhao, Emily Mooren, Nate Derbinsky:
Reinforcement Learning for Modeling Large-Scale Cognitive Reasoning. KEOD 2017: 233-238 - 2016
- [c14]Ying Zhao, Tony Kendall, Bonnie Johnson:
Big Data and Deep Analytics Applied to the Common Tactical Air Picture (CTAP) and Combat Identification (CID). KDIR 2016: 443-449 - [c13]Ying Zhao, Charles C. Zhou:
System self-awareness towards deep learning and discovering high-value information. UEMCON 2016: 1-8
2000 – 2009
- 2009
- [c12]Shelley P. Gallup, Douglas J. MacKinnon, Ying Zhao, John Robey, Chris Odell:
Facilitating Decision Making, Re-use and Collaboration - A Knowledge Management Approach for System Self-Awareness. KMIS 2009: 236-241 - [c11]Charles Zhou, Ying Zhao, Chetan Kotak:
The Collaborative Learning Agent (CLA) in Trident Warrior 08 Exercise. KDIR 2009: 323-328 - 2005
- [c10]Ying Zhao, Charles Zhou, Ian Oglesby, Cliff Zhou:
Large-scale Drug Function Prediction by Integrating QIS D2 and BioSpice. CSB Workshops 2005: 391-394 - [c9]Ying Zhao, Charles Zhou:
Drug Characteristics Prediction. CSB Workshops 2005: 395-398
1990 – 1999
- 1996
- [j2]Ying Zhao, Christopher G. Atkeson:
Implementing projection pursuit learning. IEEE Trans. Neural Networks 7(2): 362-373 (1996) - [c8]Christopher LaPre, Ying Zhao, Christopher Raphael, Richard M. Schwartz, John Makhoul:
Multi-font recognition of printed Arabic using the BBN BYBLOS speech recognition system. ICASSP 1996: 2136-2139 - [c7]Richard M. Schwartz, Christopher LaPre, John Makhoul, Christopher Raphael, Ying Zhao:
Language-independent OCR using a continuous speech recognition system. ICPR 1996: 99-103 - 1995
- [c6]Ying Zhao, Richard M. Schwartz, Jason J. Sroka, John Makhoul:
Hierarchical mixtures of experts methodology applied to continuous speech recognition. ICASSP 1995: 3443-3446 - 1994
- [j1]George Zavaliagkos, Ying Zhao, Richard M. Schwartz, John Makhoul:
A hybrid segmental neural net/hidden Markov model system for continuous speech recognition. IEEE Trans. Speech Audio Process. 2(1): 151-160 (1994) - [c5]Long Nguyen, Richard M. Schwartz, Ying Zhao, George Zavaliagkos:
Is N-Best Dead? HLT 1994 - [c4]Ying Zhao, Richard M. Schwartz, Jason J. Sroka, John Makhoul:
Hierarchical Mixtures of Experts Methodology Applied to Continuous Speech Recognition. NIPS 1994: 859-865 - 1993
- [c3]Ying Zhao, Richard M. Schwartz, John Makhoul, George Zavaliagkos:
Segmental Neural Net Optimization for Continuous Speech Recognition. NIPS 1993: 1059-1066 - 1992
- [c2]George Zavaliagkos, Ying Zhao, Richard M. Schwartz, John Makhoul:
A Hybrid Neural Net System for State-of-the-Art Continuous Speech Recognition. NIPS 1992: 704-711 - 1991
- [c1]Ying Zhao, Christopher G. Atkeson:
Some Approximation Properties of Projection Pursuit Learning Networks. NIPS 1991: 936-943
Coauthor Index
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