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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
2025 Improving lexical diversity of neural machine translation using GAN and knowledge distillation
2025 Learning equivalence hash functions
2025 Robustesse des réseaux neuronaux sur graphes
2025 Leveraging machine reading comprehension to mitigate hallucinations in answer generation by large language models
2025 Towards optimal knowledge transfer for efficient language models
2025 Data-driven large neighbourhood search for combinatorial optimization problems
2025 Machine learning through the sciences of the artificial
2025 Design and implementation of an AI-Driven educating bot for personalized science education in middle school students
2025 Neural architectures for compositional generalisation
2025 Investigating the impact of training data coverage on large language model hallucinations
2025 Uncertainty quantification metrics for scientific application
2025 Strategic capacity planning and pricing : a choice-based approach
2025 Machine learning accelerated stochastic optimization and applications to railway operations
2025 Towards adaptive personalization in conversational search
2025 Matrix theory and hardware implementation of linear recurrences
2025 Evaluating and improving mathematical reasoning in large language models via skill combinations
2024 Rule-based data augmentation for document-level medical concept extraction
2024 Mobility anomaly detection with intelligent video surveillance
2024 Generative models, theory and applications
2024 Aligning language models to code : exploring efficient, temporal, and preference alignment for code generation
2024 Self-supervision for reinforcement learning
2024 Distributed fog load balancing to support IoT applications : a reinforcement learning approach
2024 Microservices identification in existing applications using meta-heuristics optimization and machine learning
2024 Beyond top line metrics : understanding the trade-off between model size and generalization properties
2024 Understanding our 3D world via generative modeling
2024 Domain adaptation in reinforcement learning via causal representation learning
2024 Détection universelle des images synthétiques générées par les modèles de diffusion
2024 Towards systematic generalization through meta-learning modular architectures and improving generative flow networks
2024 Towards human-AI co-creation for Hindustani music : modeling and interaction
2024 Towards maintainable machine learning development through continual and modular learning
2024 Scalable and robust fog-computing design & dimensioning in dynamic, trustless smart cities
2024 Sur la génération d'exemples pour réduire le coût d'annotation
2024 Promoting robustness and compositionality in machine learning with insights from cognitive bottlenecks
2024 Beyond the status quo in deep reinforcement learning
2024 Dynamic capacities and priorities in stable matching
2024 Evaluating approaches to solving proportional sentence analogies
2024 Towards efficient large language models : training low-bitwidth variants and low-rank decomposition of pretrained models
2024 FACTS-ON : Fighting Against Counterfeit Truths in Online social Networks : fake news, misinformation and disinformation
2024 Embedding cultural diversity in prototype-based recommender systems
2024 Quotient Types in Typer
2024 Self-play for human-agent communication
2024 An exploration of approximation chains
2024 Searching for Q*
2024 Enhancing risk-based authentication with federated learning : introducing the F-RBA framework
2024 An investigation of weight perturbation for mitigating Spurious Correlations
2024 Generative flow networks : theory and applications to structure learning
2024 Leveraging foundation models towards semantic world representations for robotics
2024 A LiDAR and Camera Based Convolutional Neural Network for the Real-Time Identification of Walking Terrain
2024 Exploring multivariate adaptations of the Lag-Llama univariate time series forecasting approach
2024 The equivalence of contrastive learning and graph convolution in collaborative filtering