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ORCIDKuo-Chu Chang
Person information
- affiliation: George Mason University, Fairfax, VA, USA
- affiliation (PhD 1986): University of Connecticut, Storrs, CT, USA
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2020 – today
- 2024
[j15]Zhengyang Fan, Wanru Li, Kathryn Blackmond Laskey
, Kuo-Chu Chang:
Investigation of Phishing Susceptibility with Explainable Artificial Intelligence. Future Internet 16(1): 31 (2024)- [j14]Zhengyang Fan, Wanru Li, Kuo-Chu Chang:
A Two-Stage Attention-Based Hierarchical Transformer for Turbofan Engine Remaining Useful Life Prediction. Sensors 24(3): 824 (2024) - 2023
- [c54]Huong N. Dang, Kuo-Chu Chang, Genshe Chen, Hua-mei Chen, Simon Khan, Milvio Franco, Erik Blasch:
Scheduling Condition-based Maintenance: An Explainable Deep Reinforcement Learning Approach via Reward Decomposition. FUSION 2023: 1-8 - 2021
- [c53]Ashton E. Harvey, Kathryn B. Laskey, Kuo-Chu Chang:
Bridging Heuristic and Deep Learning Approaches to Sensor Tasking. FUSION 2021: 1-8
2010 – 2019
- 2019
- [j13]Mahendra Mallick, Kuo-Chu Chang, Sanjeev Arulampalam, Yanjun Yan:
Heterogeneous Track-to-Track Fusion in 3-D Using IRST Sensor and Air MTI Radar. IEEE Trans. Aerosp. Electron. Syst. 55(6): 3062-3079 (2019) - [c52]Sabyasachi Guharay, KC Chang, Jie Xu:
Flexible Expected Shortfall Estimation Using Parametric & Non-Parametric Methods with Applications in Finance, Insurance & Climatology. FUSION 2019: 1-8 - [c51]Ran Ji, KC Chang, Zhenlong Jiang:
Risk-Aversion Adjusted Portfolio Optimization with Predictive Modeling. FUSION 2019: 1-8 - [c50]Mahendra Mallick, Kuo-Chu Chang, Sanjeev Arulampalam, Yanjun Yan, Barbara F. La Scala:
Heterogeneous Track-to-Track Fusion in 2D Using Sonar and Radar Sensors. FUSION 2019: 1-8 - [c49]Shozo Mori, Chee-Yee Chong, KC Chang:
Distributed Multiple Hypothesis Tracking in Finite Point Process Formalism: A Simple Two Station Case. FUSION 2019: 1-8 - [c48]Kaipei Yang, Yaakov Bar-Shalom, Kuo-Chu Chang:
Information Matrix Fusion for Nonlinear, Asynchronous and Heterogeneous Systems. FUSION 2019: 1-6 - [c47]Jiayang Yu, Tuan Le, KC Chang, Sabyasachi Guharay:
Fusing Economic Indicators for Portfolio Optimization - A Simulation-Based Approach. FUSION 2019: 1-8 - 2018
- [c46]Chee-Yee Chong, Kuo-Chu Chang, Shozo Mori:
A Review of Forty Years of Distributed Estimation. FUSION 2018: 1-8 - [c45]Sabyasachi Guharay, KC Chang, Jie Xu:
Estimation of Value-at-Risk Using Mixture Copula Model for Heavy-Tailed Operational Risk Losses in Financial, Insurance & Climatological Data. FUSION 2018: 2330-2337 - [c44]Bin Jia, Cailing Dong, Zhijiang Chen, Kuo-Chu Chang, Nichole Sullivan, Genshe Chen:
Pattern Discovery and Anomaly Detection via Knowledge Graph. FUSION 2018: 2392-2399 - 2017
- [c43]Todd W. Martin, Kuo-Chu Chang:
Probabilistic reasoning and risk-constrained dynamic spectrum access. DySPAN 2017: 1-10 - [c42]KC Chang, Zhi Tian, Jiayang Yu:
Dynamic asset allocation - Chasing a moving target. FUSION 2017: 1-8 - [c41]Sabyasachi Guharay, KC Chang, Jie Xu:
Flexible estimation of risk metric using copula model for the joint severity-frequency loss framework. FUSION 2017: 1-6 - [c40]Todd W. Martin, Kuo-Chu Chang:
Risk-based pricing for secondary spectrum access. FUSION 2017: 1-8 - 2016
- [c39]Shozo Mori, Chee-Yee Chong, Kuo-Chu Chang:
Three formalisms of multiple hypothesis tracking. FUSION 2016: 727-734 - [c38]Sabyasachi Guharay, KC Chang, Jie Xu:
Robust estimation of value-at-risk through correlated frequency and severity model. FUSION 2016: 995-1002 - [c37]Todd W. Martin, Kuo-Chu Chang:
Assessing user decision behaviors for Dynamic Spectrum Sharing and pricing models. FUSION 2016: 1011-1018 - [c36]KC Chang, Zhi Tian:
Optimal asset allocation with mutual information. FUSION 2016: 1019-1026 - [c35]Chee-Yee Chong, Kuo-Chu Chang, Shozo Mori:
Comparison of optimal distributed estimation and consensus filtering. FUSION 2016: 1034-1041 - 2015
- [c34]Kelin Lu, KC Chang, Rui Zhou:
The exact algorithm for multi-sensor asynchronous track-to-track fusion. FUSION 2015: 886-892 - [c33]Todd W. Martin, Kuo-Chu Chang:
Development and analysis of a probabilistic reasoning methodology for spectrum situational awareness and parameter estimation in uncertain environments. FUSION 2015: 1475-1482 - [c32]Shozo Mori, Kuo-Chu Chang, Hajime Takahashi, Chee-Yee Chong:
An application of interacting multiple model tracking method to financial modeling and asset allocation. FUSION 2015: 1906-1913 - [c31]Sabyasachi Guharay, KC Chang:
An application of data fusion techniques in quantitative operational risk management. FUSION 2015: 1914-1921 - [c30]KC Chang, Zhi Tian:
Market analysis and trading strategies with Bayesian networks. FUSION 2015: 1922-1929 - [c29]Sabyasachi Guharay, KC Chang:
Application of bayesian simulation framework in quantitatively measuring presence of competition in living species. WSC 2015: 4033-4044 - 2014
- [j12]Shozo Mori, Kuo-Chu Chang, Chee-Yee Chong:
Performance prediction of feature-aided track-to-track association. IEEE Trans. Aerosp. Electron. Syst. 50(4): 2593-2603 (2014) - [c28]Todd W. Martin, Kuo-Chu Chang:
Situational awareness uncertainty impacts on Dynamic Spectrum Access performance. FUSION 2014: 1-8 - 2013
- [j11]Hongda Chen, Kuo-Chu Chang, Craig S. Agate:
UAV Path Planning with Tangent-plus-Lyapunov Vector Field Guidance and Obstacle Avoidance. IEEE Trans. Aerosp. Electron. Syst. 49(2): 840-856 (2013) - [c27]Todd W. Martin, Kuo-Chu Chang:
A causal reasoning approach to DSA situational awareness and decision-making. FUSION 2013: 638-646 - [c26]Todd W. Martin, Kuo-Chu Chang:
An initial study of DSA cost and capacity trades under imperfect awareness. ICNC 2013: 431-436 - [i4]Kuo-Chu Chang, Robert M. Fung:
Symbolic Probabilistic Inference with Continuous Variables. CoRR abs/1303.5712 (2013) - [i3]Kuo-Chu Chang, Robert M. Fung:
Symbolic Probabilistic Inference with Evidence Potential. CoRR abs/1303.5713 (2013) - [i2]Kuo-Chu Chang, Robert M. Fung:
Refinement and Coarsening of Bayesian Networks. CoRR abs/1304.1138 (2013) - [i1]Robert M. Fung, Kuo-Chu Chang:
Weighing and Integrating Evidence for Stochastic Simulation in Bayesian Networks. CoRR abs/1304.1504 (2013) - 2012
- [j10]Rommel N. Carvalho, Kuo-Chu Chang:
A Fusion Analysis and Evaluation Tool for Multi-Sensor Classification Systems. J. Adv. Inf. Fusion 7(2): 141-152 (2012) - [j9]Thomas M. Clemons, Kuo-Chu Chang:
Sensor Calibration using In-Situ Celestial Observations to Estimate Bias in Space-Based Missile Tracking. IEEE Trans. Aerosp. Electron. Syst. 48(2): 1403-1427 (2012) - [c25]Shozo Mori, Kuo-Chu Chang, Chee-Yee Chong:
Comparison of track fusion rules and track association metrics. FUSION 2012: 1996-2003 - [c24]Paulo Cesar G. da Costa, Kathryn B. Laskey, Kuo-Chu Chang, Wei Sun, Cheol Young Park, Shou Matsumoto:
High-Level Information Fusion with Bayesian Semantics. BMA 2012: 8-17 - 2011
- [c23]Rommel N. Carvalho, Richard Haberlin, Paulo Cesar G. da Costa, Kathryn B. Laskey, Kuo-Chu Chang:
Modeling a probabilistic ontology for Maritime Domain Awareness. FUSION 2011: 1-8 - [c22]Shozo Mori, Chee-Yee Chong, Kuo-Chu Chang:
Performance prediction of feature aided track-to-track association. FUSION 2011: 1-8 - 2010
- [c21]Feng Lin, Chunyan Zhou, KC Chang:
Convergence rate analysis of allied genetic algorithm. CDC 2010: 786-791 - [c20]Wei Sun, Kuo-Chu Chang, Kathryn B. Laskey:
Scalable inference for hybrid Bayesian networks with full density estimations. FUSION 2010: 1-8 - [c19]Rommel N. Carvalho, Paulo Cesar G. da Costa, Kathryn B. Laskey, Kuo-Chu Chang:
PROGNOS: Predictive situational awareness with probabilistic ontologies. FUSION 2010: 1-8 - [c18]Paulo Cesar G. da Costa, Kuo-Chu Chang, Kathryn B. Laskey, Tod S. Levitt, Wei Sun:
High-level fusion: Issues in developing a formal theory. FUSION 2010: 1-8 - [c17]Kuo-Chu Chang, Wei Sun:
Scalable fusion with mixture distributions in sensor networks. ICARCV 2010: 1251-1256
2000 – 2009
- 2009
- [c16]Paulo Cesar G. da Costa, Kuo-Chu Chang, Kathryn B. Laskey, Rommel N. Carvalho:
A multi-disciplinary approach to high level fusion in predictive situational awareness. FUSION 2009: 248-255 - [c15]Hongda Chen, Kuo-Chu Chang, Craig S. Agate:
Tracking with UAV using tangent-plus-Lyapunov vector field guidance. FUSION 2009: 363-372 - [c14]Rommel N. Carvalho, Kuo-Chu Chang:
A performance evaluation tool for multi-sensor classification systems. FUSION 2009: 1123-1130 - [c13]Shozo Mori, Chee-Yee Chong, Kuo-Chu Chang:
Track association and fusion using Janossy measure density functions. FUSION 2009: 1634-1641 - [c12]Thomas M. Clemons, Kuo-Chu Chang:
Bias correction using background stars for space-based IR tracking. FUSION 2009: 2028-2035 - 2008
- [c11]Kuo-Chu Chang, Chee-Yee Chong, Shozo Mori:
On scalable distributed sensor fusion. FUSION 2008: 1-8 - 2007
- [c10]Wei Sun, Kuo-Chu Chang:
Unscented Message Passing for Arbitrary Continuous Variables in Bayesian Networks. AAAI 2007: 1902-1903 - [c9]Wei Sun, Kuo-Chu Chang:
Hybrid message passing for mixed bayesian networks. FUSION 2007: 1-8 - 2006
- [j8]Kuo-Chu Chang, Joe P. Hill:
Level I and Level II Target Valuations for Sensor Management. J. Adv. Inf. Fusion 1(2): 95-107 (2006) - [c8]Todd W. Martin, Kuo-Chu Chang:
A Data Fusion Formulation for Decentralized Estimation Predictions under Communications Uncertainty. FUSION 2006: 1-7 - 2002
- [j7]Shulin Yang, Kuo-Chu Chang:
Comparison of score metrics for Bayesian network learning. IEEE Trans. Syst. Man Cybern. Part A 32(3): 419-428 (2002) - 2000
- [j6]Kuo-Chu Chang, Xiaoyan Yin, Rajat K. Saha:
Evaluating a linear predictive algorithm for bandwidth conservation. IEEE Trans. Aerosp. Electron. Syst. 36(4): 1407-1414 (2000)
1990 – 1999
- 1999
- [j5]Jun Liu, Kuo-Chu Chang, Jing Zhou:
Learning Bayesian networks with a hybrid convergent method. IEEE Trans. Syst. Man Cybern. Part A 29(5): 436-449 (1999) - 1998
- [c7]Jun Liu, Kuo-Chu Chang, Jing Zhou:
A Hybrid Convergent Method for Learning Probabilistic Networks. Canadian AI 1998: 393-410 - 1997
- [j4]Andrew Hauter, Kuo-Chu Chang, Sherman Karp:
Polarimetric fusion for synthetic aperture radar target classification. Pattern Recognit. 30(5): 769-775 (1997) - 1995
- [j3]Shozo Mori, Kuo-Chu Chang, Chee-Yee Chong, Keh-Ping Dunn:
Prediction of track purity and track accuracy in dense target environments. IEEE Trans. Autom. Control. 40(5): 953-959 (1995) - [j2]Kuo-Chu Chang, Robert M. Fung:
Symbolic probabilistic inference with both discrete and continuous variables. IEEE Trans. Syst. Man Cybern. 25(6): 910-916 (1995) - 1991
- [c6]Kuo-Chu Chang, Robert M. Fung:
Symbolic Probabilistic Inference with Continuous Variables. UAI 1991: 77-81 - [c5]Kuo-Chu Chang, Robert M. Fung:
Symbolic Probabilistic Inference with Evidence Potential. UAI 1991: 82-85 - 1990
- [c4]Kuo-Chu Chang, Robert M. Fung:
Refinement and coarsening of Bayesian networks. UAI 1990: 435-446
1980 – 1989
- 1989
- [j1]Kuo-Chu Chang, Yaakov Bar-Shalom:
Distributed adaptive estimation with probabilistic data association. Autom. 25(3): 359-369 (1989) - [c3]Kuo-Chu Chang, Robert M. Fung:
Node Aggregation for Distributed Inference in Bayesian Networks. IJCAI 1989: 265-270 - [c2]Yaakov Bar-Shalom, Kuo-Chu Chang, Hemchandra M. Shertukde:
Performance evaluation of a cascaded logic for track formation in clutter. SMC 1989: 13-17 - [c1]Robert M. Fung, Kuo-Chu Chang:
Weighing and Integrating Evidence for Stochastic Simulation in Bayesian Networks. UAI 1989: 209-220
Coauthor Index
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last updated on 2024-03-02 00:00 CET by the dblp team
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