Sheila Alemany

According to our database, Sheila Alemany authored at least 9 papers between 2018 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2023

Towards Parametric Robust Activation Functions in Adversarial Machine Learning.

Sheila Alemany, Alberto Luis Dominguez, Ilan Grapel, Niki Pissinou

Proceedings of the First Tiny Papers Track at ICLR 2023, 2023

2022

The Dilemma Between Data Transformations and Adversarial Robustness for Time Series Application Systems.

Sheila Alemany, Niki Pissinou

Proceedings of the Workshop on Artificial Intelligence Safety 2022 (SafeAI 2022) co-located with the Thirty-Sixth AAAI Conference on Artificial Intelligence (AAAI2022), 2022

2021

Jespipe: A Plugin-Based, Open MPI Framework for Adversarial Machine Learning Analysis.

Sheila Alemany, Jason Nucciarone, Niki Pissinou

Proceedings of the 2021 IEEE International Conference on Big Data (Big Data), 2021

2020

The Dilemma Between Dimensionality Reduction and Adversarial Robustness.

Sheila Alemany, Niki Pissinou

CoRR, 2020

2019

Quantifying location privacy in permissioned blockchain-based internet of things (IoT).

Abdur R. Shahid, Niki Pissinou, Laurent Njilla, Sheila Alemany, Ahmed Imteaj, Kia Makki, Edwin Aguilar

Proceedings of the MobiQuitous 2019, 2019

Predicting Hurricane Trajectories Using a Recurrent Neural Network.

Sheila Alemany, Jonathan Beltran, Adrián Pérez, Sam Ganzfried

Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

2018

A Dynamic Trust Weight Allocation Technique for Data Reconstruction in Mobile Wireless Sensor Networks.

Concepcion Sanchez Aleman, Niki Pissinou, Sheila Alemany, Georges A. Kamhoua

Proceedings of the 17th IEEE International Conference On Trust, 2018

Context-Aware Data Cleaning for Mobile Wireless Sensor Networks: A Diversified Trust Approach.

Concepcion Sanchez Aleman, Niki Pissinou, Sheila Alemany, Kianoosh G. Boroojeni, Jerry Miller, Ziqian Ding

Proceedings of the 2018 International Conference on Computing, 2018

Using Candlestick Charting and Dynamic Time Warping for Data Behavior Modeling and Trend Prediction for MWSN in IoT.

Concepcion Sanchez Aleman, Niki Pissinou, Sheila Alemany, Georges A. Kamhoua

Proceedings of the IEEE International Conference on Big Data (IEEE BigData 2018), 2018