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We develop tractable semidefinite programming based approximations for distributionally robust individual and joint chance constraints, assuming that only the first- and second-order moments as well as the support of the uncertain parameters are given. It ...
Tolerance analysis is an important step to validate assembly process planning scenario. Simulations are generally performed to evaluate the expected geometrical variations of the assembled product. When the simulation models take into account part complian ...
We examine the problem of learning a set of parameters from a distributed dataset. We assume the datasets are collected by agents over a distributed ad-hoc network, and that the communication of the actual raw data is prohibitive due to either privacy cons ...
We address the problem of learning a classifier from distributed data over a number of arbitrarily connected machines without exchange of the datapoints. Our purpose is to train a neural network at each machine as if the entire dataset was locally availabl ...
Inference from data is of key importance in many applications of informatics. The current trend in performing such a task of inference from data is to utilise machine learning algorithms. Moreover, in many applications that it is either required or is pref ...
The main goal in network information theory is to identify fundamental limits of communication over networks, and design solutions which perform close to such limits. After several decades of effort, many important problems still do not have a characteriza ...
Scene parsing is a technique that consist on giving a label to all pixels in an image according to the class they belong to. To ensure a good visual coherence and a high class accuracy, it is essential for a scene parser to capture image long range depende ...
Abstract Tolerance analysis is an important step to validate assembly process planning scenario. Simulations are generally performed to evaluate the expected geometrical variations of the assembled product. When the simulation models take into account part ...
We apply multilayer perceptron (MLP) based hierarchical Tandem features to large vocabulary continuous speech recognition in Mandarin. Hierarchical Tandem features are estimated using a cascade of two MLP classifiers which are trained independently. The fi ...
We consider the Gaussian N-relay diamond network, where a source wants to communicate to a destination through a layer of N-relay nodes. We investigate the following question: What fraction of the capacity can we maintain by using only k out of the $ ...
