123 citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- Yale UniversityUS14 papers
- Sorbonne UniversitéFR6 papers
- Centre National de la Recherche ScientifiqueFR5 papers
- Université Paris Sciences et LettresFR5 papers
- Laboratório Interinstitucional de e-AstronomiaBR4 papers
- Universidade Estadual Paulista (Unesp)BR4 papers
- Universidade Tecnológica Federal do ParanáBR4 papers
- Valongo ObservatoryBR4 papers
- Akdeniz UniversityTR3 papers
- Instituto de Astrofísica de AndalucíaES3 papers
- Institut Polytechnique des Sciences AvancéesFR3 papers
- Laboratoire d’études spatiales et d’instrumentation en astrophysiqueFR3 papers
4 papers · 1 filter
Mitigation of Adversarial Policy Imitation via Constrained Randomization of Policy (CRoP)
Nancirose Piazza, Vahid Behzadan
Deep reinforcement learning (DRL) policies are vulnerable to unauthorized replication attacks, where an adversary exploits imitation learning to reproduce target policies from obse…
Hack The Box: Fooling Deep Learning Abstraction-Based Monitors
Sara Hajj Ibrahim, Mohamed Nassar
Deep learning is a type of machine learning that adapts a deep hierarchy of concepts. Deep learning classifiers link the most basic version of concepts at the input layer to the mo…
Adversarial Poisoning Attacks and Defense for General Multi-Class Models Based On Synthetic Reduced Nearest Neighbors
Pooya Tavallali, Vahid Behzadan, Peyman Tavallali +1
State-of-the-art machine learning models are vulnerable to data poisoning attacks whose purpose is to undermine the integrity of the model. However, the current literature on data…
Adversarial Attacks on Deep Algorithmic Trading Policies
Yaser Faghan, Nancirose Piazza, Vahid Behzadan +1
Deep Reinforcement Learning (DRL) has become an appealing solution to algorithmic trading such as high frequency trading of stocks and cyptocurrencies. However, DRL have been shown…