Shane T. Barratt

27 papers A* 2C 1Journal 22Unranked 2

Year	Rank	Type	Title / Venue / Authors
2023	J	`jnl`	Fitting feature-dependent Markov chains. J. Glob. Optim. Shane T. Barratt, Stephen P. Boyd
2022	J	`jnl`	Stochastic Control With Affine Dynamics and Extended Quadratic Costs. IEEE Trans. Autom. Control. Shane T. Barratt, Stephen P. Boyd
2021	J	`jnl`	A Distributed Method for Fitting Laplacian Regularized Stratified Models. J. Mach. Learn. Res. Jonathan Tuck, Shane T. Barratt, Stephen P. Boyd
2021	J	`jnl`	Covariance Prediction via Convex Optimization. CoRR Shane T. Barratt, Stephen P. Boyd
2021	J	`jnl`	Learning Convex Optimization Models. IEEE CAA J. Autom. Sinica Akshay Agrawal, Shane T. Barratt, Stephen P. Boyd
2021	J	`jnl`	Low Rank Forecasting. CoRR Shane T. Barratt, Yining Dong, Stephen P. Boyd
2021	J	`jnl`	Optimal representative sample weighting. Stat. Comput. Shane T. Barratt, Guillermo Angeris, Stephen P. Boyd
2020	C	`conf`	Fitting a Kalman Smoother to Data. ACC Shane T. Barratt, Stephen P. Boyd
2020	—	`conf`	Fitting a Linear Control Policy to Demonstrations with a Kalman Constraint. L4DC Malayandi Palan, Shane T. Barratt, Alex McCauley, Dorsa Sadigh, Vikas Sindhwani, Stephen P. Boyd
2020	—	`conf`	Learning Convex Optimization Control Policies. L4DC Akshay Agrawal, Shane T. Barratt, Stephen P. Boyd, Bartolomeo Stellato
2020	J	`jnl`	Learning Convex Optimization Models. CoRR Akshay Agrawal, Shane T. Barratt, Stephen P. Boyd
2020	J	`jnl`	Minimizing a sum of clipped convex functions. Optim. Lett. Shane T. Barratt, Guillermo Angeris, Stephen P. Boyd
2020	J	`jnl`	Optimal Representative Sample Weighting. CoRR Shane T. Barratt, Guillermo Angeris, Stephen P. Boyd
2019	J	`jnl`	A Distributed Method for Fitting Laplacian Regularized Stratified Models. CoRR Jonathan Tuck, Shane T. Barratt, Stephen P. Boyd
2019	A*	`conf`	Differentiable Convex Optimization Layers. NeurIPS Akshay Agrawal, Brandon Amos, Shane T. Barratt, Stephen P. Boyd, Steven Diamond, J. Zico Kolter
2019	J	`jnl`	Differentiable Convex Optimization Layers. CoRR Akshay Agrawal, Brandon Amos, Shane T. Barratt, Stephen P. Boyd, Steven Diamond, J. Zico Kolter
2019	J	`jnl`	Learning Convex Optimization Control Policies. CoRR Akshay Agrawal, Shane T. Barratt, Stephen P. Boyd, Bartolomeo Stellato
2019	J	`jnl`	Learning Probabilistic Trajectory Models of Aircraft in Terminal Airspace From Position Data. IEEE Trans. Intell. Transp. Syst. Shane T. Barratt, Mykel J. Kochenderfer, Stephen P. Boyd
2019	J	`jnl`	Least Squares Auto-Tuning. CoRR Shane T. Barratt, Stephen P. Boyd
2018	J	`jnl`	A Note on the Inception Score. CoRR Shane T. Barratt, Rishi Sharma
2018	J	`jnl`	Cooperative Multi-Agent Reinforcement Learning for Low-Level Wireless Communication. CoRR Colin de Vrieze, Shane T. Barratt, Daniel Tsai, Anant Sahai
2018	J	`jnl`	Improved Training with Curriculum GANs. CoRR Rishi Sharma, Shane T. Barratt, Stefano Ermon, Vijay S. Pande
2018	J	`jnl`	Learning Probabilistic Trajectory Models of Aircraft in Terminal Airspace from Position Data. CoRR Shane T. Barratt, Mykel J. Kochenderfer, Stephen P. Boyd
2018	J	`jnl`	Optimizing for Generalization in Machine Learning with Cross-Validation Gradients. CoRR Shane T. Barratt, Rishi Sharma
2017	J	`jnl`	Active Robotic Mapping through Deep Reinforcement Learning. CoRR Shane T. Barratt
2017	J	`jnl`	InterpNET: Neural Introspection for Interpretable Deep Learning. CoRR Shane T. Barratt
2015	A*	`conf`	A non-rigid point and normal registration algorithm with applications to learning from demonstrations. ICRA Alex X. Lee, Max A. Goldstein, Shane T. Barratt, Pieter Abbeel