A. Raglin

发表

On Uncertainty and Robustness in Large-Scale Intelligent Data Fusion Systems

Mani Srivastava, Lance Kaplan, Lance M. Kaplan, 2020, 2020 IEEE Second International Conference on Cognitive Machine Intelligence (CogMI).

Performance and Saliency Analysis of Data from the Anomaly Detection Task Study

A. Raglin, Andre V Harrison, 2017 .

Reasoning with an uncertainty of information measure: decision making for military and non-military applications

Andre Harrison, Adrienne Raglin, A. Raglin, 2018, Defense + Security.

A↵ective Computing of Constitutional States for Human Information Interaction

Brian Jalaian, A. Raglin, H. Samani, 2017 .

Metareasoning for multi-criteria decision making using complex information sources

Justine P. Caylor, J. Herrmann, A. Raglin, 2022, Defense + Commercial Sensing.

Preliminary Evaluation of Multi-criteria Decision-Making Methodology for Emergency Management

Robert J. Hammell, Justine P. Caylor, Adrienne J. Raglin, 2021, AHFE.

Between Multi-Attribute Utility Decision Making and Recommender Systems: Transparent, Instantaneous, Local Recommendations for Sparse Data

James Michaelis, Adrienne Raglin, Stephen Russell, 2018, FLAIRS Conference.

Recent advances in multi-modal data fusion: status, challenges and perspectives

D. Rawat, A. Raglin, Brian M. Sadler, 2022, Defense + Commercial Sensing.

A Practical Data Repository for Causal Learning with Big Data

Ruocheng Guo, Huan Liu, Adrienne Raglin, 2019, Bench.

Secrecy-Preserving Reasoning and Query Answering in Probabilistic Description Logic Prob-EL > 0 , = 1 − > KBs

G. Slutzki, A. Raglin, Gopalakrishnan Krishnasamy-Sivaprakasam, 2017 .

Domain Generalization -- A Causal Perspective

K. Candan, A. Raglin, Huan Liu, 2022, 2209.15177.

Domain Generalization - A Causal Perspective

K. Candan, A. Raglin, Huan Liu, 2022, ArXiv.

Image segmentation utilizing the winner-take-all dynamics in a large-array opto-electronic feedback circuit

Mohamed F. Chouikha, Adrienne Jeanisha Raglin, M. Chouikha, 2007, J. Electronic Imaging.

IoT: Smart City Parking Solutions with Metric-Chisini-Jensen-Shannon Divergence based Kernels

Adrienne Raglin, Piyush K. Sharma, A. Raglin, 2019, MILCOM 2019 - 2019 IEEE Military Communications Conference (MILCOM).

IoT in Smart Cities: Exploring Information Theoretic and Deep Learning Models to Improve Parking Solutions

Adrienne Raglin, Piyush Sharma, A. Raglin, 2019, 2019 IEEE SmartWorld, Ubiquitous Intelligence & Computing, Advanced & Trusted Computing, Scalable Computing & Communications, Cloud & Big Data Computing, Internet of People and Smart City Innovation (SmartWorld/SCALCOM/UIC/ATC/CBDCom/IOP/SCI).

Efficacy of Nonlinear Manifold Learning in Malware Image Pattern Analysis

Adrienne Raglin, Piyush Sharma, A. Raglin, 2018, 2018 17th IEEE International Conference on Machine Learning and Applications (ICMLA).

Image-Audio Encoding for Information Camouflage and Improving Malware Pattern Analysis

Adrienne Raglin, Piyush Sharma, A. Raglin, 2018, 2018 17th IEEE International Conference on Machine Learning and Applications (ICMLA).

The Analysis and Prediction of Eye Gaze When Viewing Statistical Graphs

Andre Harrison, Mark A. Livingston, Adrienne Raglin, 2017, HCI.

Causal Interpretability for Machine Learning - Problems, Methods and Evaluation

Ruocheng Guo, Adrienne Raglin, Raha Moraffah, 2020, SIGKDD Explor..

Causal Adversarial Network for Learning Conditional and Interventional Distributions.

Huan Liu, Adrienne Raglin, Bahman Moraffah, 2020, 2008.11376.

I can do better than your AI: expertise and explanations

James Michaelis, Tobias Höllerer, Adrienne Raglin, 2019, IUI.

Causal inference for time series analysis: problems, methods and evaluation

Adrienne Raglin, Raha Moraffah, Paras Sheth, 2021, Knowledge and Information Systems.

Understanding theoretical human information interaction, the development of a standard model using an agent based modeling framework

Adrienne Raglin, Somiya Metu, Christianna Howard, 2018, Defense + Security.

MxR Framework for Uncertainty Based Explanation for Uncovering Adversarial Behavior

Andre Harrison, James Michaelis, Adrienne Raglin, 2018, HCI.

Explainability and causality for robust, fair, and trustworthy artificial reasoning

D. Rawat, A. Raglin, Brian M. Sadler, 2023, Defense + Commercial Sensing.

Robust, fair, and trustworthy artificial reasoning systems via quantitative causal learning and explainability

D. Rawat, A. Raglin, Brian M. Sadler, 2023, Defense + Commercial Sensing.

Enhanced visual perception through tone mapping

Andre Harrison, Ralph Etienne-Cummings, Adrienne Raglin, 2016, SPIE Defense + Security.

Implementing Internet of Things in a military command and control environment

Adrienne Raglin, Stephen Russell, Peter Budulas, 2017, Defense + Security.

Socially Responsible Machine Learning: A Causal Perspective

A. Raglin, Amir-Hossein Karimi, Huan Liu, 2023, KDD.

Trustworthy agents under a veil of misinformation: mechanism design under adversarial upstream conditions

Mark R. Mittrick, John P. Dickerson, A. Raglin, 2023, Defense + Commercial Sensing.

A survey of feature space reduction methods for context aware processing in IoBT networks

Andre Harrison, Adrienne Raglin, Michael S. Lee, 2018 .

CAN: A Causal Adversarial Network for Learning Observational and Interventional Distributions pdf

Huan Liu, Adrienne Raglin, Bahman Moraffah, 2020, ArXiv.

ARL Battlespace: a platform for developing novel AI for complex adversarial reasoning in MDO

Sue E. Kase, A. Raglin, B. Rinderspacher, 2022, Defense + Commercial Sensing.