Amos, Brandon

Edge analytics in the internet of things

Satyanarayanan, M., Simoens, P., Xiao, Y., Pillai, P., Chen, Z., Ha, K., Hu, W., & Amos, B. (2015) · IEEE Pervasive Computing

IoT and Edge/Fog ComputingPrivacy-Preserving Technologies in Data

Cited by 430

An empirical study of latency in an emerging class of edge computing applications for wearable cognitive assistance

Chen, Z., Hu, W., Wang, J., Zhao, S., Amos, B., Wu, G., Ha, K., Elgazzar, K., Pillai, P., Klatzky, R., et al. (2017) · Proceedings of the Second ACM/IEEE Symposium on Edge Computing

IoT and Edge/Fog ComputingContext-Aware Activity Recognition Systems

Cited by 213

AdvPrompter: Fast Adaptive Adversarial Prompting for LLMs

Paulus, A., Zharmagambetov, A., Guo, C., Amos, B., & Tian, Y. (2024) · arXiv

Adversarial Robustness in Machine LearningTopic Modeling

Cited by 184

Quantifying the Impact of Edge Computing on Mobile Applications

Hu, W., Gao, Y., Ha, K., Wang, J., Amos, B., Chen, Z., Pillai, P., & Satyanarayanan, M. (2016) · Proceedings of the 7th ACM SIGOPS Asia-Pacific Workshop on Systems

IoT and Edge/Fog ComputingMobile and Web Applications

Cited by 171

Objective Mismatch in Model-based Reinforcement Learning

Lambert, N., Amos, B., Yadan, O., & Calandra, R. (2020) · arXiv

Reinforcement Learning in RoboticsDomain Adaptation and Few-Shot Learning

Cited by 33

Multisample Flow Matching: Straightening Flows with Minibatch Couplings

Pooladian, A.-A., Ben-Hamu, H., Domingo-Enrich, C., Amos, B., Lipman, Y., & Chen, R. T. Q. (2023) · arXiv

Generative Adversarial Networks and Image SynthesisModel Reduction and Neural Networks

Cited by 7