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Cloud computing is a whole new paradigm that offers a non-traditional computing model for organizations to adopt Information Technology and related functions and aspects without upfront investment and with lower Total Cost of Ownership (TCO). Cloud computing opens doors to multiple, unlimited venues from elastic computing to on demand provisioning to(More)
Many tasks in computer vision, such as action classification and object detection, require us to rank a set of samples according to their relevance to a particular visual category. The performance of such tasks is often measured in terms of the average precision (AP). Yet it is common practice to employ the support vector machine (SVM) classifier, which(More)
The problem of ranking a set of visual samples according to their relevance to a query plays an important role in computer vision. The traditional approach for ranking is to train a binary classifier such as a support vector machine (svm). Binary classifiers suffer from two main deficiencies: (i) they do not optimize a ranking-based loss function, for(More)
Recent years have witnessed amazing progress in AI related fields such as computer vision, machine learning and autonomous vehicles. As with any rapidly growing field, however, it becomes increasingly difficult to stay up-to-date or enter the field as a beginner. While several topic specific survey papers have been written, to date no general survey on(More)
The problem of ranking a set of visual samples according to their relevance to a query plays an important role in computer vision. The traditional approach for ranking is to train a binary classifier such as a support vector machine (svm). Binary classifiers suffer from two main deficiencies: (i) they do not optimize a ranking-based loss function, for(More)
Briefly, the algorithm starts by specifying no constraints (step 1 of Algorithm 1: W is initialized to the null set). At each iteration, it adds a single constraint, which corresponds to the most violated ranking (step 4 of Algorithm 1: solving problem (1)). Intuitively, problem (1) finds a ranking that differs significantly from the ground-truth ranking in(More)
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