Sarah Dean PRO
asst prof in CS at Cornell
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BIRS Workshop: User Dynamics in ML Systems
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16 - Policy Optimization - ML in Feedback Sys F25
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15 - Adaptive Control - ML in Feedback Sys F25
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14 - Control with Partial Observation - ML in Feedback Sys F25
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13 - MPC Safety and Stability - ML in Feedback Sys F25
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12 - MPC - ML in Feedback Sys F25
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11 - Bandits - ML in Feedback Sys F25
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10 - Generalization - ML in Feedback Sys F25
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09 - Hidden Markov Models - ML in Feedback Sys F25
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08 - Stochastic Dynamics and Filtering - ML in Feedback Sys F25
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07 - Linear Autoregressive Models - ML in Feedback Sys F25
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06 - Nonlinear Dynamics and Koopman - ML in Feedback Sys F25
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05 - Nonlinear Dynamics and Linearization - ML in Feedback Sys F25
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04 - Linear Dynamics - ML in Feedback Sys F25
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03 - Sequential Data: Markov Models - ML in Feedback Sys F25
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02 - Supervised Learning: Least Squares - ML in Feedback Sys F25
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01 - Overview - ML in Feedback Sys F25
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Set-based and Machine Learning Perspectives on Control-affine Dynamics
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Learning and decision making under observer effects
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Learning Models of Dynamical Systems from Finite Observations
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OLC Talk: Learning Dynamics from Bilinear Observations
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User Dynamics in Machine Learning Systems
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Online Convex Optimization with Unbounded Memory
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Preference and Participation Dynamics in Learning Systems
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Dissertation Talk
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Certainty Equivalent Perception-Based Control
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Bias in Algorithms
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Measurement-Robust Control Barrier Functions
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Sample Complexity LQR
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Learning Based Control
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Delayed Impact of Fair Machine Learning
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Safe LQR ACC
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Feedback Systems Ch 4: