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Many robotics problems are formulated as optimization problems. However, most optimization solvers in robotics are locally optimal and the performance depends a lot on the initial guess. For challenging problems, the solver will often get stuck at poor loc ...
For lumped homogeneous reaction systems, this paper presents a kinetic model identification scheme that provides maximum-likelihood parameter estimates and guarantees convergence to global optimality. The use of the extent-based incremental approach allows ...
Multiparty videoconferences, or more generally multiparty video calls, are gaining a lot of popularity as they offer a rich communication experience. These applications have, however, large requirements in terms of both network and computational resources ...
2017
The distribution networks are experiencing important changes driven by the massive integration of renewable energy conversion systems. However, the lack of direct controllability of the Distributed Generations (DGs) supplying Active Distribution Networks ( ...
EPFL2016
Optimization is a fundamental tool in modern science. Numerous important tasks in biology, economy, physics and computer science can be cast as optimization problems. Consider the example of machine learning: recent advances have shown that even the most s ...
EPFL2018
This paper provides expressions for the largest and smallest solution of a global optimization problem using an adjoint variable which represents the available one-sided improvements up to the interval “horizon”. Interpreting the problem in terms of optima ...
2016
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In freight railway networks, commodities are usually transported via hubs, which are called marshaling or shunting yards, depending on their capacity. Consequently, the number and locations of these yards effect the transport costs to a great extent.
The ...
2018
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Omnidirectional video streaming is usually implemented based on the representations of tiles, where the tiles are obtained by splitting the video frame into several rectangular areas and each tile is converted into multiple representations with different r ...
We introduce a novel approach to reduce the computational effort of solving convex chance constrained programs through the scenario approach. Instead of reducing the number of required scenarios, we directly minimize the computational cost of the scenario ...
In this paper we present an adaptive robust optimization framework for the day-ahead scheduling of Active Distribution Networks (ADNs) where the controlled devices are distributed Energy Storage Systems (ESSs). First, the targeted problem is formulated usi ...
