3 papers
cs.RO2023
Constraint Inference in Control Tasks from Expert Demonstrations via Inverse Optimization
Dimitris Papadimitriou, Jingqi Li
Inferring unknown constraints is a challenging and crucial problem in many robotics applications. When only expert demonstrations are available, it becomes essential to infer the u…
cs.LG2021
Data-Driven Low-Rank Neural Network Compression
Dimitris Papadimitriou, Swayambhoo Jain
Despite many modern applications of Deep Neural Networks (DNNs), the large number of parameters in the hidden layers makes them unattractive for deployment on devices with storage…
eess.SY2020
Control of Unknown Nonlinear Systems with Linear Time-Varying MPC
Dimitris Papadimitriou, Ugo Rosolia, Francesco Borrelli
We present a Model Predictive Control (MPC) strategy for unknown input-affine nonlinear dynamical systems. A non-parametric method is used to estimate the nonlinear dynamics from o…