Baosen Zhang

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University of Washington

Lyapunov-Regularized Reinforcement Learning for Power System Transient Stability

Transient stability of power systems is becoming increasingly important ...
03/05/2021 ∙ by Wenqi Cui, et al. ∙ 0 ∙ share

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Multi-Agent Reinforcement Learning in Cournot Games

In this work, we study the interaction of strategic agents in continuous...
09/14/2020 ∙ by Yuanyuan Shi, et al. ∙ 0 ∙ share

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Safe Reinforcement Learning of Control-Affine Systems with Vertex Networks

This paper focuses on finding reinforcement learning policies for contro...
03/20/2020 ∙ by Liyuan Zheng, et al. ∙ 5 ∙ share

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Transfer Learning for HVAC System Fault Detection

Faults in HVAC systems degrade thermal comfort and energy efficiency in ...
02/04/2020 ∙ by Chase P. Dowling, et al. ∙ 0 ∙ share

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Learning in Cournot Games with Limited Information Feedback

In this work, we study the interaction of strategic players in continuou...
06/15/2019 ∙ by Yuanyuan Shi, et al. ∙ 0 ∙ share

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Fast Calculation of Probabilistic Power Flow: A Model-based Deep Learning Approach

Probabilistic power flow (PPF) plays a critical role in the analysis of ...
06/14/2019 ∙ by Yan Yang, et al. ∙ 0 ∙ share

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A tractable ellipsoidal approximation for voltage regulation problems

We present a machine learning approach to the solution of chance constra...
03/09/2019 ∙ by Pan Li, et al. ∙ 0 ∙ share

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A Capacity-Price Game for Uncertain Renewables Resources

Renewable resources are starting to constitute a growing portion of the ...
04/17/2018 ∙ by Pan Li, et al. ∙ 0 ∙ share

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Real-Time Prediction of the Duration of Distribution System Outages

This paper addresses the problem of predicting duration of unplanned pow...
04/03/2018 ∙ by Aaron Jaech, et al. ∙ 0 ∙ share

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Bayesian Renewables Scenario Generation via Deep Generative Networks

We present a method to generate renewable scenarios using Bayesian proba...
02/02/2018 ∙ by Yize Chen, et al. ∙ 0 ∙ share

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Uncertainty in Multi-Commodity Routing Networks: When does it help?

We study the equilibrium quality under user uncertainty in a multi-commo...
09/25/2017 ∙ by Shreyas Sekar, et al. ∙ 0 ∙ share

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Distribution System Voltage Control under Uncertainties

Voltage control plays an important role in the operation of electricity ...
04/28/2017 ∙ by Pan Li, et al. ∙ 0 ∙ share

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An Optimal Treatment Assignment Strategy to Evaluate Demand Response Effect

Demand response is designed to motivate electricity customers to modify ...
10/02/2016 ∙ by Pan Li, et al. ∙ 0 ∙ share

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Learning Temporal Dependence from Time-Series Data with Latent Variables

We consider the setting where a collection of time series, modeled as ra...
08/27/2016 ∙ by Hossein Hosseini, et al. ∙ 0 ∙ share

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Online Active Linear Regression via Thresholding

We consider the problem of online active learning to collect data for re...
02/09/2016 ∙ by Carlos Riquelme, et al. ∙ 0 ∙ share

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A Sparse Linear Model and Significance Test for Individual Consumption Prediction

Accurate prediction of user consumption is a key part not only in unders...
11/05/2015 ∙ by Pan Li, et al. ∙ 0 ∙ share

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Baosen Zhang

Featured Co-authors

Pan Li

Mari Ostendorf

Sreeram Kannan

Radha Poovendran

Ram Rajagopal

Alberto Sangiovanni-Vincentelli

Lillian J. Ratliff

Ramesh Johari

Yan Yang

Aaron Jaech

Hossein Hosseini

Lyapunov-Regularized Reinforcement Learning for Power System Transient Stability

Multi-Agent Reinforcement Learning in Cournot Games

Safe Reinforcement Learning of Control-Affine Systems with Vertex Networks

Transfer Learning for HVAC System Fault Detection

Learning in Cournot Games with Limited Information Feedback

Fast Calculation of Probabilistic Power Flow: A Model-based Deep Learning Approach

A tractable ellipsoidal approximation for voltage regulation problems

A Capacity-Price Game for Uncertain Renewables Resources

Real-Time Prediction of the Duration of Distribution System Outages

Bayesian Renewables Scenario Generation via Deep Generative Networks

Uncertainty in Multi-Commodity Routing Networks: When does it help?

Distribution System Voltage Control under Uncertainties

An Optimal Treatment Assignment Strategy to Evaluate Demand Response Effect

Learning Temporal Dependence from Time-Series Data with Latent Variables

Online Active Linear Regression via Thresholding

A Sparse Linear Model and Significance Test for Individual Consumption Prediction