Waveguide Invariant Reverberation Mitigation for Active Sonar. - Ryan A. Goldhahn; Granger Hickman; Jeffrey L. Krolik (ICASSP (2), 2007)

A non-myopic, receding horizon control strategy for an AUV to track an underwater target in a bistatic sonar scenario. - Gabriele Ferri 002; Andrea Munafò; Ryan A. Goldhahn; Kevin D. LePage (CDC, 2014)

Cognitive multistatic AUV networks. - Paolo Braca; Ryan A. Goldhahn; Kevin D. LePage; Stefano Maranò 001; Vincenzo Matta; Peter Willett 001 (FUSION, 2014)

Environmentally sensitive particle filter tracking in multistatic AUV networks with port-starboard ambiguity. - Ryan A. Goldhahn; Paolo Braca; Kevin D. LePage; Peter Willett 001; Stefano Maranò 001; Vincenzo Matta (ICASSP, 2014)

Byzantine-Resilient locally optimum detection using collaborative autonomous networks. - Bhavya Kailkhura; Priyadip Ray; Deepak Rajan; Anton Yen; Peter D. Barnes Jr.; Ryan A. Goldhahn (CAMSAP, 2017)

Robust Federated Learning Using ADMM in the Presence of Data Falsifying Byzantines. - Qunwei Li; Bhavya Kailkhura; Ryan A. Goldhahn; Priyadip Ray; Pramod K. Varshney (CoRR, 2017)

Sequential optimal positioning of mobile sensors using mutual information. - Kathleen L. Schmidt; Ralph C. Smith; Jason M. Hite; John K. Mattingly; Yousry Y. Azmy; Deepak Rajan; Ryan A. Goldhahn (Stat. Anal. Data Min., 2019)

Decentralized Black-Box Variational Inference for Bayesian Learning on Sensor Networks. - Jose Cadena; Priyadip Ray; Ryan A. Goldhahn (ACSCC, 2021)

Certifiably-Robust Federated Adversarial Learning via Randomized Smoothing. - Cheng Chen; Bhavya Kailkhura; Ryan A. Goldhahn; Yi Zhou 017 (MASS, 2021)

Collaborative energy demand response with decentralized actor and centralized critic. - Ruben Glatt; Felipe Leno da Silva; Braden Soper; William A. Dawson; Edward Rusu; Ryan A. Goldhahn (BuildSys, 2021)

Hybrid Information-driven Multi-agent Reinforcement Learning. - William A. Dawson; Ruben Glatt; Edward Rusu; Braden C. Soper; Ryan A. Goldhahn (CoRR, 2021)

Mixture of Robust Experts (MoRE): A Flexible Defense Against Multiple Perturbations. - Hao Cheng 015; Kaidi Xu; Chenan Wang; Xue Lin 001; Bhavya Kailkhura; Ryan A. Goldhahn (CoRR, 2021)

Stochastic Gradient-Based Distributed Bayesian Estimation in Cooperative Sensor Networks. - Jose Cadena; Priyadip Ray; Hao Chen 001; Braden Soper; Deepak Rajan; Anton Yen; Ryan A. Goldhahn (IEEE Trans. Signal Process., 2021)

Bayesian Multiagent Active Sensing and Localization via Decentralized Posterior Sampling. - Braden C. Soper; Priyadip Ray; Jose Cadena; Hao Chen 001; Ryan A. Goldhahn (IEEECONF, 2022)

More or Less (MoL): Defending against Multiple Perturbation Attacks on Deep Neural Networks through Model Ensemble and Compression. - Hao Cheng 015; Kaidi Xu; Zhengang Li; Pu Zhao 001; Chenan Wang; Xue Lin 001; Bhavya Kailkhura; Ryan A. Goldhahn (WACV (Workshops), 2022)

Efficient Multi-Prize Lottery Tickets: Enhanced Accuracy, Training, and Inference Speed. - Hao Cheng 015; Pu Zhao 001; Yize Li; Xue Lin 001; James Diffenderfer; Ryan A. Goldhahn; Bhavya Kailkhura (CoRR, 2022)

Robust Decentralized Learning Using ADMM With Unreliable Agents. - Qunwei Li; Bhavya Kailkhura; Ryan A. Goldhahn; Priyadip Ray; Pramod K. Varshney (IEEE Trans. Signal Process., 2022)

Less is More: Data Pruning for Faster Adversarial Training. - Yize Li; Pu Zhao 001; Xue Lin 001; Bhavya Kailkhura; Ryan A. Goldhahn (SafeAI@AAAI, 2023)

Real-Time Fully Unsupervised Domain Adaptation for Lane Detection in Autonomous Driving. - Kshitij Bhardwaj; Zishen Wan; Arijit Raychowdhury; Ryan A. Goldhahn (DATE, 2023)