no code implementations • 8 Jan 2024 • Zeinab Ebrahimi, Gustavo Batista, Mohammad Deghat
The main intention of the AA-DLADMM algorithm is to employ Anderson acceleration to ADMM by considering it as a fixed-point iteration and attaining a nearly quadratic convergence rate.
no code implementations • 11 Apr 2023 • Ayyoob Hamza, Hassan Habibi Gharakheili, Theophilus A. Benson, Gustavo Batista, Vijay Sivaraman
(4) We demonstrate how our models scale in environments with a large number of connected IoTs (with datasets collected from a network of IP cameras in our university campus) by considering various training strategies (per device unit versus per device type), and balancing the accuracy of prediction against the cost of models in terms of size and training time.
no code implementations • 17 Jan 2023 • Arman Pashamokhtari, Norihiro Okui, Masataka Nakahara, Ayumu Kubota, Gustavo Batista, Hassan Habibi Gharakheili
Our contributions are three-fold: (1) We collect and analyze network traffic of 24 types of consumer IoT devices from 12 real homes over six weeks to highlight the challenge of temporal and spatial concept drifts in network behavior of IoT devices; (2) We analyze the performance of two inference strategies, namely "global inference" (a model trained on a combined set of all labeled data from training homes) and "contextualized inference" (several models each trained on the labeled data from a training home) in the presence of concept drifts; and (3) To manage concept drifts, we develop a method that dynamically applies the ``closest'' model (from a set) to network traffic of unseen homes during the testing phase, yielding better performance in 20% of scenarios.
no code implementations • 18 Mar 2022 • Arman Pashamokhtari, Gustavo Batista, Hassan Habibi Gharakheili
In this paper, we present AdIoTack, a system that highlights vulnerabilities of decision trees against adversarial attacks, helping cybersecurity teams quantify and refine the resilience of their trained models for monitoring IoT networks.
no code implementations • 9 Mar 2022 • Bo Chen, Ali Bakhshi, Gustavo Batista, Brian Ng, Tat-Jun Chin
In this paper, we consider the scenario where retraining can be done on the server side based on a copy of the DNN model, with only the necessary data transmitted to the edge to update the deployed model.
1 code implementation • 22 Apr 2020 • Denis dos Reis, Marcílio de Souto, Elaine de Sousa, Gustavo Batista
Quantification is the research field that studies methods for counting the number of data points that belong to each class in an unlabeled sample.
no code implementations • 11 Mar 2014 • Yanping Chen, Adena Why, Gustavo Batista, Agenor Mafra-Neto, Eamonn Keogh
The ability to use inexpensive, noninvasive sensors to accurately classify flying insects would have significant implications for entomological research, and allow for the development of many useful applications in vector control for both medical and agricultural entomology.