In this paper, we present an abstract framework for online approximation of time-series data that yields a unified set of algorithms for several popular models: data streams, amnes...
Abstract—With the price of wireless sensor technologies diminishing rapidly we can expect large numbers of autonomous sensor networks being deployed in the near future. These sen...
In this paper, we present an efficient algorithm for 3D object recognition in presence of clutter and occlusions in noisy, sparse and unsegmented range data. The method uses a robu...
New technologies used in biology are generating huge quantities of data; up to two petabytes of overall data are to be expected by the end of the decade. Modern biology also has t...
This paper proposes a framework for agent-based distributed machine learning and data mining based on (i) the exchange of meta-level descriptions of individual learning processes ...