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We present a risk-averse multi-dimensional newsvendor model for a class of products whose demands are strongly correlated and subject to fashion trends that are not fully understood at the time when orders are placed. The demand distribution is known to be ...
The 13th November 2015 terrorist attacks in Paris call for a multi-scalar and multimetric geographical analysis. From Paris’ « intimate hypercentre » to the « global low-intensity civil war », this event embraces the entire complexity of the present contem ...
Compressed sensing is a new trend in signal processing for efficient sampling and signal acquisition. The idea is that most real-world signals have a sparse representation in an appropriate basis and this can be exploited to capture the sparse signal by ta ...
This paper tackles the problem of multi-robot odor distribution mapping through time series analysis. Considering the conditions of real world environments where the chemical concentration distribution is patchy, intermittent and time-variant, we propose a ...
In the biometrics community, face and speaker recognition are mature fields in which several systems have been proposed over the past twenty years. While existing systems perform well under controlled recording conditions, mismatch caused by the use of dif ...
For making artificial systems collaborate with group-living animals, the scientific challenge is to build artificial systems that can perceive, communicate to, interact with and adapt to animals. When such capabilities are available then it should be possi ...
While there is a general consensus that autonomous robots should be able to learn continuously over time, the learning process is traditionally envisioned for each specific robot situated in a given environment. This does not consider the fact that robots ...
Some of the next generation massive spectroscopic survey projects, plan to use thousands of fiber positioner robots packed at a focal plane to quickly move in parallel the fiber-ends from the previous to the next target points. The most direct trajectories ...
Novel applications in unstructured and non-stationary human environments require robots that learn from experience and adapt autonomously to changing conditions. Predictive models therefore not only need to be accurate, but should also be updated increment ...
Real time planning strategy is crucial for robots working in dynamic environments. In particular, robot grasping tasks require quick reactions in many applications such as human-robot interaction. In this paper, we propose an approach for grasp learning th ...
