Supervised learning of a parts-based model can be for-
mulated as an optimization problem with a large (exponen-
tial in the number of parts) set of constraints. We show how
thi...
M. Pawan Kumar, Andrew Zisserman, Philip H.S. Torr
Recent results have suggested that online Model Predictive Control (MPC) can be computed quickly enough to control fast sampled systems. High-speed applications impose a hard real-...
Melanie Nicole Zeilinger, Colin Neil Jones, Davide...
Inverse kinematics is the problem of manipulating the pose of an articulated figure in order to achieve a desired goal disregarding inertia and forces. One can approach the probl...
In this paper, we introduce a new technique for modeling and solving the dynamic power management (DPM) problem for systems with complex behavioral characteristics such as concurr...
Constraint-driven Communication Synthesis enables the automatic design of the communication architecture of a complex system from a library of pre-defined Intellectual Property (I...
Alessandro Pinto, Luca P. Carloni, Alberto L. Sang...