We establish minimax optimal rates of convergence for estimation in a high dimensional additive model assuming that it is approximately sparse. Our results reveal an interesting phase transition behavior universal to this class of high dimensional problems. In the sparse regime when the components are sufficiently smooth or the dimensionality is sufficiently large, the optimal rates are identic...

We propose to tackle the cost-sensitive learning problem, where each feature is associated to a particular acquisition cost. We propose a new model with the following key properties: (i) it acquires features in an adaptive way, (ii) features can be acquired per block (several at a time) so that this model can deal with high dimensional data, and (iii) it relies on representation-learning ideas....

In recent years, production of text documents has seen an exponential growth, which is the reason why their proper classification seems necessary for better access. One of the main problems of classifying text documents is working in high-dimensional feature space. Feature Selection (FS) is one of the ways to reduce the number of text attributes. So, working with a great bulk of the feature spa...

in this paper, the researchers have proposed a multi-dimensional knapsack model for project capital budgeting problem in uncertain situation which has been modeled through fuzzy sets. the optimistic and pessimistic situations were considered and associated deterministic models were yielded. numerical example has been supplied toillustrate the performance of proposed model. the results were prom...

The goal of this study was to create and demonstrate a system perform fast inexpensive quality dimensional inspection for industrial assembly line applications with submillimeter uncertainty. Our focus is on the positional errors assembled pieces larger part as it assembled. This achieved by using an open-source photogrammetry architecture gather point cloud data then comparing computer-aided d...

At present, many cloud services are managed by using open source software, such as OpenStack and Eucalyptus, because of the unification management of data, cost reduction, quick delivery and work savings. The operation phase of cloud computing has a unique feature, such as the provisioning processes, the network-based operation and the diversity of data, because the operation phase of cloud com...

Anderson, James Robert M.S.E.E., Purdue University, May, 1997. Multidimensional Network Performance. Major Professor: Seth Abraham. The interconnection network in a parallel processing system can have a profound impact on the success of a system in terms of performance or cost. The ability to clearly determine the trade-offs between performance and cost during the design of a network is critica...