- Multimedia Multimodal Signal Analysis and Enhancement Laboratory | INRS
The Multimedia Multimodal Signal Analysis and Enhancement Laboratory (MuSAE Lab) conducts research at the crossroads of biomedical engineering and telecommunications The MuSAE Lab develops award-winning, biologically inspired signal processing techniques with applications in three areas: multimedia communications, health diagnosis, and human machine interaction Data is used to develop human
- The Art of Deception: Robust Backdoor Attack using Dynamic Stacking of . . .
ORSON MENGARA1 1INRS-EMT, University of Québec, Montréal, QC, Canada Corresponding author: Orson Mengara (e-mail: orson mengara@inrs ca) ABSTRACT MachineLearningasaService(MLaaS)isexperiencingincreasedimplementationowingtorecentadvance- ments in the Artificial Intelligence (AI) industry
- Trading Devil: Robust backdoor attack via Stochastic investment models . . .
Trading Devil: Robust backdoor attack via Stochastic investment models and bayesian approach Orson Mengara1 1 INRS-EMT, University of Québec, Montréal, QC, Canada {orson mengara@inrs ca}
- The Art of Deception: Robust Backdoor Attack using Dynamic Stacking of . . .
The Art of Deception: Robust Backdoor Attack using Dynamic Stacking of triggers ORSON MENGARA1 INRS-EMT, University of Québec, Montréal, QC, Canada
- The Art of Quantum Computing for Finance: Brief Overview and Prospects
Authored by Orson Mengara Abstract This review article discusses the application of quantum computing to financial problems while presenting current approaches and their future prospects We also talk about quantum machine learning and deep learning in finance In the banking industry, we look at the most recent developments and the state of the art in quantum computing Following a quick
- Great day with Orson Typhanel MENGARA, Mahsa Abdollahi . . . - LinkedIn
Great day with Orson Typhanel MENGARA, Mahsa Abdollahi, Tiago Falk, and Pierre Giovenazzo PhD's research group!
- Trading Devil Final: Backdoor attack via Stock market and Bayesian . . .
Trading Devil Final: Backdoor attack via Stock market and Bayesian Optimization Orson Mengara1 1 INRS-EMT, University of Québec, Montréal, QC, Canada {orson mengara@inrs ca, msoftwaretools2024@gmail com+priority}
- [2402. 05967] The last Dance : Robust backdoor attack via diffusion . . .
View a PDF of the paper titled The last Dance : Robust backdoor attack via diffusion models and bayesian approach, by Orson Mengara
- Trading Devil RL: Backdoor attack via Stock market, Bayesian . . .
View a PDF of the paper titled Trading Devil RL: Backdoor attack via Stock market, Bayesian Optimization and Reinforcement Learning, by Orson Mengara
- The Art of Deception: Robust Backdoor Attack using Dynamic Stacking of . . .
ORSON MENGARA1 1INRS-EMT, University of Québec, Montréal, QC, Canada Corresponding author: Orson Mengara (e-mail: orson mengara@inrs ca) ABSTRACT MachineLearningasaService(MLaaS)isexperiencingincreasedimplementationowingtorecentadvance- ments in the Artificial Intelligence (AI) industry
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The Art of Quantum Computing for Finance: Brief Overview and Prospects Orson Mengara 1,2 INRS-EMT, University of Québec, Montréal, QC, Canada; typhanel orson mengara@umontreal ca University of Montreal, Québec, Canada
- Backdoor Attacks to Deep Neural Networks: A Survey of the Literature . . .
Abstract Read online Deep neural network (DNN) classifiers are potent instruments that can be used in various security-sensitive applications Nonetheless, they are vulnerable to certain attacks that impede or distort their learning process For example, backdoor attacks involve polluting the DNN learning set with a few samples from one or more source classes, which are then labeled as target
- Trading Devil Final: Backdoor attack via Stock market and Bayesian . . .
View a PDF of the paper titled Trading Devil Final: Backdoor attack via Stock market and Bayesian Optimization, by Orson Mengara
- arXiv:2402. 05967v3 [cs. LG] 14 Apr 2024
{orson mengara@inrs ca} ssive addition of noise and denoising In this paper, we aim to fool audio-based DNN models, such as those from the Hugging Face framework, primarily those that focus on audio, in particular transformer-based artificial intelligence models, which are powerful machine learning models that save time and achi
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