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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 croissant Titre Trier par titre en ordre croissant
2024 Towards efficient large language models : training low-bitwidth variants and low-rank decomposition of pretrained models
2024 The equivalence of contrastive learning and graph convolution in collaborative filtering
2024 Metaheuristics for vehicle routing problems : new methods and performance analysis
2024 Beyond the status quo in deep reinforcement learning
2024 Promoting robustness and compositionality in machine learning with insights from cognitive bottlenecks
2024 Sur la génération d'exemples pour réduire le coût d'annotation
2024 Beyond top line metrics : understanding the trade-off between model size and generalization properties
2024 The shifting landscape of data : learning to tame distributional shifts
2024 A LiDAR and Camera Based Convolutional Neural Network for the Real-Time Identification of Walking Terrain
2024 HarmonyCo : développement d'une bibliothèque Python pour le calcul optimisé de la médiane de permutations
2024 Rule-based data augmentation for document-level medical concept extraction
2024 Distributed fog load balancing to support IoT applications : a reinforcement learning approach
2024 Deep learning applications to climate change mitigation
2024 Learning optimizers for communication-efficient distributed learning
2024 Geometric-aware models for protein design
2024 Generative flow networks : theory and applications to structure learning
2024 Towards systematic generalization through meta-learning modular architectures and improving generative flow networks
2024 The role of continual learning and adaptive computation in improving computational efficiency of deep learning
2024 An investigation of weight perturbation for mitigating Spurious Correlations
2024 Modelling and evolving design-time uncertainty