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IFML Seminar
Computationally Efficient Reinforcement Learning with Linear Bellman Completeness
Abstract: One of the most natural approaches to reinforcement learning (RL) with function approximation is value iteration, which inductively generates approximations to the optimal value function by solving a sequence of regression problems. To...
Upcoming Events
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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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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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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…
Past Events
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August302 - 3 pm
Foundational Research Seminar
The talk will cover two complexity-theoretic results from optimization. We will review work on an accelerated algorithm (à la Nesterov)...
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August23throughAugust31
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July810 - 11 am
ML+ X Seminar
How can we design AI to benefit society? In this talk, I will discuss the stakes involved in ensuring that...
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June2810 - 11 am
ML+ X Seminar
Computers that can understand and communicate in human language is a foundational goal of AI and has many applications that...
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June1410 - 11 am
ML+ X Seminar
Artificial Intelligence and Machine Learning have grown in popularity recently, fueled by recent successes in several domains, including image…