A Two Stage Mechanism For Selling Random Power. - Nathan Dahlin; Rahul Jain 002 (CoRR, 2018)

A Two Stage Stochastic Mechanism for Selling Random Power. - Nathan Dahlin; Rahul Jain 002 (ACC, 2019)

A Two-Stage Market Mechanism for Electricity with Renewable Generation. - Nathan Dahlin; Rahul Jain 002 (CDC, 2019)

A Risk Aware Two-Stage Market Mechanism for Electricity with Renewable Generation. - Nathan Dahlin; Rahul Jain 002 (ACC, 2020)

Scheduling of Flexible Non-Preemptive Loads. - Nathan Dahlin; Rahul Jain 002 (CDC, 2020)

Designing Interpretable Approximations to Deep Reinforcement Learning with Soft Decision Trees. - Nathan Dahlin; Krishna Chaitanya Kalagarla; Nikhil Naik 001; Rahul Jain 002; Pierluigi Nuzzo 002 (CoRR, 2020)

Practical Control Design for the Deep Learning Age: Distillation of Deep RL-Based Controllers. - Nathan Dahlin; Kevin Chang 007; Krishna Chaitanya Kalagarla; Rahul Jain 002; Pierluigi Nuzzo 002 (Allerton, 2022)

Conditional Value at Risk-Sensitive Solar Hosting Capacity Analysis in Distribution Networks. - Avinash N. Madavan; Nathan Dahlin; Subhonmesh Bose; Lang Tong 001 (CoRR, 2022)

Scheduling Flexible Nonpreemptive Loads in Smart-Grid Networks. - Nathan Dahlin; Rahul Jain 002 (IEEE Trans. Control. Netw. Syst., 2022)

Two-Stage Electricity Markets With Renewable Energy Integration: Market Mechanisms and Equilibrium Analysis. - Nathan Dahlin; Rahul Jain 002 (IEEE Trans. Control. Netw. Syst., 2022)

Compressed Decentralized Learning of Conditional Mean Embedding Operators in Reproducing Kernel Hilbert Spaces. - Boya Hou; Sina Sanjari; Nathan Dahlin; Subhonmesh Bose (AAAI, 2023)

Controlling a Markov Decision Process with an Abrupt Change in the Transition Kernel. - Nathan Dahlin; Subhonmesh Bose; Venugopal V. Veeravalli (ACC, 2023)

Exact and Cost-Effective Automated Transformation of Neural Network Controllers to Decision Tree Controllers. - Kevin Chang 007; Nathan Dahlin; Rahul Jain 002; Pierluigi Nuzzo 002 (CDC, 2023)

Sparse Learning of Dynamical Systems in RKHS: An Operator-Theoretic Approach. - Boya Hou; Sina Sanjari; Nathan Dahlin; Subhonmesh Bose; Umesh Vaidya (ICML, 2023)

Markov Balance Satisfaction Improves Performance in Strictly Batch Offline Imitation Learning. - Rishabh Agrawal; Nathan Dahlin; Rahul Jain 002; Ashutosh Nayyar (AAAI, 2025)

Conditional Kernel Imitation Learning for Continuous State Environments. - Rishabh Agrawal; Nathan Dahlin; Rahul Jain 002; Ashutosh Nayyar (L4DC, 2025)

Risk-Sensitive Security-Constrained Economic Dispatch: Pricing and Algorithm Design. - Avinash N. Madavan; Nathan Dahlin; Subhonmesh Bose; Lang Tong 001 (CoRR, 2025)

Sustainable Grid through Distributed Data Centers: Spinning AI Demand for Grid Stabilization and Optimization. - Scott C. Evans; Nathan Dahlin; Ibrahima Ndiaye; Sachini Piyoni Ekanayake; Alexander Duncan; Blake Rose; Hao Huang (CoRR, 2025)