Visiting Researchers’ Presentations
During the two-month summer program we had the opportunity to host talks by visiting researchers that spent some time with us. This provided an opportunity for our PhD fellows and in general the ARCHIMEDES community to get a good understanding of various areas.
Visiting Researchers’ Presentations
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Efficient Decentralized Multi-Agent Learning in Asymmetric Bipartite Queueing Systems & open directions, networking with speaker |
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Better voting via public spirit |
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The Computational Complexity of Finding Stationary Points in Non-Convex Optimization |
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Debiased Machine Learning for Static and Dynamic Treatment Settings |
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Efficient Neural Scene Representations |
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Contexts can be Cheap: Solving Stochastic Contextual Bandits with Linear Bandit Algorithms |
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A Statistical Framework for Private Personalized Federated Learning and Estimation |
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Generative Models and Computational Imaging Soft Diffusion and Learning from Corrupted |
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Introduction to Diffusion models and Inverse Problems |
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Computational-Statistical Trade-offs in Group Testing (or: how many “pooled tests” are enough?) |
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Modular Data Processing for the Data Science Era |
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Explainable Fact Checking with Structured Data |
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Discovering how agents learn using few data |
