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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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2024 Self-play for human-agent communication
2024 Towards efficient and effective preference alignment for large language models
2024 Generative flow networks : theory and applications to structure learning
2024 Learning optimizers for communication-efficient distributed learning
2024 Intrinsic exploration for reinforcement learning beyond rewards
2024 The role of continual learning and adaptive computation in improving computational efficiency of deep learning
2024 Enhancing agent learning through world dynamics modeling
2024 Towards efficient large language models : training low-bitwidth variants and low-rank decomposition of pretrained models
2024 Enhancing risk-based authentication with federated learning : introducing the F-RBA framework
2024 Advancing adversarial robustness with feature desensitization and synthesized data