IFML Seminar
IFML Seminar: 10/25/24 - Representation-based Reinforcement Learning
Abstract: Reinforcement learning often faces a trade-off between model flexibility and computational tractability. Flexible models can capture complex dynamics and policy but often introduce nonlinearity, making planning and exploration challenging. In this talk, we...
Upcoming Events
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October412:15 - 1 pm
IFML Seminar
Abstract: Sequential decision-making (SDM) is crucial for adapting machine learning to dynamic real-world scenarios such as fluctuating markets or…
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October2512:15 - 1 pm
IFML Seminar
Abstract: Reinforcement learning often faces a trade-off between model flexibility and computational tractability. Flexible models can capture complex…
Past Events
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September2712:15 - 1 pm
IFML Seminar
Abstract: One of the most natural approaches to reinforcement learning (RL) with function approximation is value iteration, which inductively generates…
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September1312:15 - 1 pm
IFML Seminar
Abstract: We consider the problem of model selection in a high-dimensional sparse linear regression model under privacy constraints. We propose...
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September612:15 - 1 pm
IFML Seminar
Abstract: From the moment we open our eyes, we are surrounded by people. By observing the people around us, we...
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August2312:15 - 1 pm
IFML Seminar
Abstract: Distribution shifts, where deployment conditions differ from the training environment, are pervasive in real-world AI applications and often…
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August5All day
IFML Director Adam Klivans and IFML Co-director Alex Dimakis discuss DataComp , UT Austin's new Center for Generative AI, and...
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July21throughJuly26
IFML has partnered with UT Computer Science Summer Academies to launch the Academy for Machine Learning