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Thèses et mémoires

Des thèses et mémoires de nos étudiants sont conservés et consultables dans Papyrus, le dépôt institutionnel de l'Université de Montréal.

 

 

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Date Trier par date en ordre décroissant Titre Trier par titre en ordre décroissant
2024 Rule-based data augmentation for document-level medical concept extraction
2024 Génération de données synthétiques pour l'adaptation hors-domaine non-supervisée en réponse aux questions : méthodes basées sur des règles contre réseaux de neurones
2024 A LiDAR and Camera Based Convolutional Neural Network for the Real-Time Identification of Walking Terrain
2024 Evaluating approaches to solving proportional sentence analogies
2024 Metaheuristics for vehicle routing problems : new methods and performance analysis
2024 Learning representations for reasoning : generalizing across diverse structures
2024 An investigation of weight perturbation for mitigating Spurious Correlations
2024 Towards human-AI co-creation for Hindustani music : modeling and interaction
2024 Generative flow networks : theory and applications to structure learning
2024 Advancing adversarial robustness with feature desensitization and synthesized data
2024 Beyond the status quo in deep reinforcement learning
2024 Towards maintainable machine learning development through continual and modular learning
2024 Promoting robustness and compositionality in machine learning with insights from cognitive bottlenecks
2024 Quotient Types in Typer
2024 Embedding cultural diversity in prototype-based recommender systems
2024 Sur la génération d'exemples pour réduire le coût d'annotation
2024 FACTS-ON : Fighting Against Counterfeit Truths in Online social Networks : fake news, misinformation and disinformation
2024 Generative models, theory and applications
2024 Constrained optimization for machine learning : algorithms and applications
2024 Domain adaptation in reinforcement learning via causal representation learning
2024 Mobility anomaly detection with intelligent video surveillance
2024 The shifting landscape of data : learning to tame distributional shifts
2024 Leveraging foundation models towards semantic world representations for robotics
2024 Towards efficient and effective preference alignment for large language models
2024 Beyond the horizon : improved long-range sequence modeling, from dynamical systems to language
2024 Self-supervision for reinforcement learning
2024 On PI controllers for updating lagrange multipliers in constrained optimization
2024 Microservices identification in existing applications using meta-heuristics optimization and machine learning
2024 Building intuitive reinforcement learning algorithms
2024 Dichotomy(?) of fairness and efficiency