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Article
Open AccessDenoising autoencoder genetic programming: strategies to control exploration and exploitation in search
Denoising autoencoder genetic programming (DAE-GP) is a novel neural network-based estimation of distribution genetic programming approach that uses denoising autoencoder long short-term memory networks as a p...
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Article
Open AccessResolution enhancement with a task-assisted GAN to guide optical nanoscopy image analysis and acquisition
Super-resolution fluorescence microscopy methods enable the characterization of nanostructures in living and fixed biological tissues. However, they require the adjustment of multiple imaging parameters while ...
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Article
The 5-year longitudinal diagnostic profile and health services utilization of patients treated with electroconvulsive therapy in Quebec: a population-based study
Electroconvulsive therapy (ECT) is effective for treating several psychiatric disorders. However, only a minority of patients are treated with ECT. It is of primary importance to characterize their profile for...
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Article
Open AccessDeep learning of chest X-rays can predict mechanical ventilation outcome in ICU-admitted COVID-19 patients
The COVID-19 pandemic repeatedly overwhelms healthcare systems capacity and forced the development and implementation of triage guidelines in ICU for scarce resources (e.g. mechanical ventilation). These guide...
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Article
Open AccessTracking and predicting COVID-19 radiological trajectory on chest X-rays using deep learning
Radiological findings on chest X-ray (CXR) have shown to be essential for the proper management of COVID-19 patients as the maximum severity over the course of the disease is closely linked to the outcome. As ...
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Article
Open AccessOn the benefits of representation regularization in invariance based domain generalization
A crucial aspect of reliable machine learning is to design a deployable system for generalizing new related but unobserved environments. Domain generalization aims to alleviate such a prediction gap between th...
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Chapter and Conference Paper
Active Learning for Capturing Human Decision Policies in a Data Frugal Context
Modeling human expert decision patterns can potentially help create training and decision support systems when no ground truth data is available. A cognitive modeling approach presented herein uses a combinati...
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Article
Open AccessExploring polypharmacy with artificial intelligence: data analysis protocol
Polypharmacy is common among older adults and it represents a public health concern, due to the negative health impacts potentially associated with the use of several medications. However, the large number of ...
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Article
Open AccessNeuronal activity remodels the F-actin based submembrane lattice in dendrites but not axons of hippocampal neurons
The nanoscale organization of the F-actin cytoskeleton in neurons comprises membrane-associated periodical rings, bundles, and longitudinal fibers. The F-actin rings have been observed predominantly in axons b...
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Chapter and Conference Paper
Improving Policy-Capturing with Active Learning for Real-Time Decision Support
Thales Research and Technology Canada is develo** a decision support system consisting in multiple classification models trained simultaneously online to capture experts’ decision policies based on their pr...
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Chapter and Conference Paper
Toward Adversarial Robustness by Diversity in an Ensemble of Specialized Deep Neural Networks
We aim at demonstrating the influence of diversity in the ensemble of CNNs on the detection of black-box adversarial instances and hardening the generation of white-box adversarial attacks. To this end, we pro...
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Chapter and Conference Paper
Associative Alignment for Few-Shot Image Classification
Few-shot image classification aims at training a model from only a few examples for each of the “novel” classes. This paper proposes the idea of associative alignment for leveraging part of the base data by al...
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Article
Open AccessA machine learning approach for online automated optimization of super-resolution optical microscopy
Traditional approaches for finding well-performing parameterizations of complex imaging systems, such as super-resolution microscopes rely on an extensive exploration phase over the illumination and acquisitio...
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Chapter and Conference Paper
Optimal Scheduling for Smart Charging of Electric Vehicles Using Dynamic Programming
We are proposing a formulation of the smart charging problem that can be solved by dynamic programming. It allows the optimal charging schedule of EVs to be determined in order to minimize the cost considering...
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Article
Controlling code growth by dynamically sha** the genotype size distribution
Genetic programming is a hyperheuristic optimization approach that seeks to evolve various forms of symbolic computer programs, in order to solve a wide range of problems. However, the approach can be severely...
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Article
Describing 3D Geometric Primitives Using the Gaussian Sphere and the Gaussian Accumulator
Most complex object models are composed of basic parts or primitives. Being able to decompose a complex 3D model into such basic primitives is an important step in reverse engineering. Even when an algorithm ...
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Article
Open AccessDabigatran versus warfarin under standard or pharmacogenetic-guided management for the prevention of stroke and systemic thromboembolism in patients with atrial fibrillation: a cost/utility analysis using an analytic decision model
Atrial fibrillation (AF) is the most common form of heart arrhythmia and a leading cause of stroke and systemic embolism. Chronic anticoagulation is recommended for preventing those complications. Our study ai...
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Chapter
A GIS Based Wireless Sensor Network Coverage Estimation and Optimization: A Voronoi Approach
Recent advances in sensor technology have resulted in the design and development of more efficient and low cast sensor networks for environmental monitoring, object surveillance, tracking and controlling of mo...
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Chapter and Conference Paper
Topography-Aware Sensor Deployment Optimization with CMA-ES
Wireless Sensor Networks (WSN) have been studied intensively for various applications such as monitoring and surveillance. Sensor deployment is an essential part of WSN, because it affects both the cost and ca...
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Chapter and Conference Paper
A Statistical Learning Perspective of Genetic Programming
This paper proposes a theoretical analysis of Genetic Programming (GP) from the perspective of statistical learning theory, a well grounded mathematical toolbox for machine learning. By computing the Vapnik-Ch...
