Ryan A. Goldhahn

Publication Activity (10 Years)

Years Active: 2017-2023
Publications (10 Years): 17

Top Topics

Bayesian Learning

Top Venues

IEEE Trans. Signal Process.

Stat. Anal. Data Min.

BuildSys@SenSys

Publications

Kshitij Bhardwaj, Zishen Wan, Arijit Raychowdhury, Ryan A. Goldhahn
Real-Time Fully Unsupervised Domain Adaptation for Lane Detection in Autonomous Driving. CoRR (2023)
Yize Li, Pu Zhao, Xue Lin, Bhavya Kailkhura, Ryan A. Goldhahn
Less is More: Data Pruning for Faster Adversarial Training. SafeAI@AAAI (2023)
Hao Cheng, Kaidi Xu, Zhengang Li, Pu Zhao, Chenan Wang, Xue Lin, Bhavya Kailkhura, Ryan A. Goldhahn
More or Less (MoL): Defending against Multiple Perturbation Attacks on Deep Neural Networks through Model Ensemble and Compression. WACV (Workshops) (2022)
Braden C. Soper, Priyadip Ray, Jose Cadena, Hao Chen, Ryan A. Goldhahn
Bayesian Multiagent Active Sensing and Localization via Decentralized Posterior Sampling. IEEECONF (2022)
Qunwei Li, Bhavya Kailkhura, Ryan A. Goldhahn, Priyadip Ray, Pramod K. Varshney
Robust Decentralized Learning Using ADMM With Unreliable Agents. IEEE Trans. Signal Process. 70 (2022)
Hao Cheng, Pu Zhao, Yize Li, Xue Lin, James Diffenderfer, Ryan A. Goldhahn, Bhavya Kailkhura
Efficient Multi-Prize Lottery Tickets: Enhanced Accuracy, Training, and Inference Speed. CoRR (2022)
Cheng Chen, Bhavya Kailkhura, Ryan A. Goldhahn, Yi Zhou
Certifiably-Robust Federated Adversarial Learning via Randomized Smoothing. CoRR (2021)
Hao Cheng, Kaidi Xu, Chenan Wang, Xue Lin, Bhavya Kailkhura, Ryan A. Goldhahn
Mixture of Robust Experts (MoRE): A Flexible Defense Against Multiple Perturbations. CoRR (2021)
Jose Cadena, Priyadip Ray, Hao Chen, Braden Soper, Deepak Rajan, Anton Yen, Ryan A. Goldhahn
Stochastic Gradient-Based Distributed Bayesian Estimation in Cooperative Sensor Networks. IEEE Trans. Signal Process. 69 (2021)
Ruben Glatt, Felipe Leno da Silva, Braden Soper, William A. Dawson, Edward Rusu, Ryan A. Goldhahn
Collaborative energy demand response with decentralized actor and centralized critic. BuildSys@SenSys (2021)
Jose Cadena, Priyadip Ray, Ryan A. Goldhahn
Decentralized Black-Box Variational Inference for Bayesian Learning on Sensor Networks. ACSCC (2021)
Cheng Chen, Bhavya Kailkhura, Ryan A. Goldhahn, Yi Zhou
Certifiably-Robust Federated Adversarial Learning via Randomized Smoothing. MASS (2021)
William A. Dawson, Ruben Glatt, Edward Rusu, Braden C. Soper, Ryan A. Goldhahn
Hybrid Information-driven Multi-agent Reinforcement Learning. CoRR (2021)
Kathleen L. Schmidt, Ralph Smith, Jason M. Hite, John K. Mattingly, Yousry Y. Azmy, Deepak Rajan, Ryan A. Goldhahn
Sequential optimal positioning of mobile sensors using mutual information. Stat. Anal. Data Min. 12 (6) (2019)
Bhavya Kailkhura, Priyadip Ray, Deepak Rajan, Anton Yen, Peter D. Barnes Jr., Ryan A. Goldhahn
Byzantine-Resilient Locally Optimum Detection Using Collaborative Autonomous Networks. CoRR (2018)
Qunwei Li, Bhavya Kailkhura, Ryan A. Goldhahn, Priyadip Ray, Pramod K. Varshney
Robust Federated Learning Using ADMM in the Presence of Data Falsifying Byzantines. CoRR (2017)
Bhavya Kailkhura, Priyadip Ray, Deepak Rajan, Anton Yen, Peter D. Barnes Jr., Ryan A. Goldhahn
Byzantine-Resilient locally optimum detection using collaborative autonomous networks. CAMSAP (2017)