Lung cancer is one of the main reasons for death globally, with an impressive rate of about five million deadly cases per year. Detection of lung cancer at an early stage is necessary to prevent deaths and increase th...
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In this paper, we present an initial work on a method for comparing expert profiles within the context of expert networks by measuring expertise similarity between experts. We introduce the concept of expertise sphere...
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One of the most significant issues facing the data mining community is that of low-quality data. Real-world datasets are often inundated with various types of data integrity issues, particularly noisy data. In respons...
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Due to the inconvenience and safety issues caused by exposed plugs and damaged cables, wireless charging of electric vehicles (EV) has gained popularity. Inductive wireless power transfer has been successfully applied...
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We consider the problem of estimating the policy gradient in Partially Observable Markov Decision Processes (POMDPs) with a special class of policies that are based on Predictive State Representations (PSRs). We compa...
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ISBN:
(纸本)9781605585161
We consider the problem of estimating the policy gradient in Partially Observable Markov Decision Processes (POMDPs) with a special class of policies that are based on Predictive State Representations (PSRs). We compare PSR policies to Finite-State Controllers (FSCs), which are considered as a standard model for policy gradient methods in POMDPs. We present a general Actor-Critic algorithm for learning both FSCs and PSR policies. The critic part computes a value function that has as variables the parameters of the policy. These latter parameters are gradually updated to maximize the value function. We show that the value function is polynomial for both FSCs and PSR policies, with a potentially smaller degree in the case of PSR policies. Therefore, the value function of a PSR policy can have less local optima than the equivalent FSC, and consequently, the gradient algorithm is more likely to converge to a global optimal solution.
In recent years, the use of mobile device is growing fast. The prevalence of mobile devices and the rapid growth of mobile threats have resulted in a shortage of personnel trained to handle mobile security As mobile p...
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Image segmentation is still one of nowadays problems in image processing, in which there is no ideal or optimal solution due to the large variety of images, their characteristics, and the type of information we try to...
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This paper describes a novel database of video images containing artificial (superimposed) Urdu text with a semi-automatic text line labeling scheme. The main objective of this study is to provide the community with a...
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ISBN:
(纸本)9781612081953
This paper describes a novel database of video images containing artificial (superimposed) Urdu text with a semi-automatic text line labeling scheme. The main objective of this study is to provide the community with a standard dataset together with an auto-labeling scheme for algorithmic development and evaluation of textual content based indexing and retrieval systems. We have specifically focused on Urdu text which is increasingly gaining research interest in recent years. The data set comprises 1000 video images collected from 19 different channels of 5 different categories. An attempt is made to capture the maximum possible variation in the text in terms of size, location, appearance and background. The data set is completely labeled by finding the bounding rectangle of each text occurrence facilitating the evaluation of text detection and localization systems. Based on our previous work on text localization, an automatic text labeling scheme is also proposed and the obtained results are compared with manual labeling. Ground truth data, supporting tasks like text recognition and word spotting will be considered in the next version of the data set.
It's a significant problem to find the densest subgraph in many research areas. Now, there are so many groups in the WeChat, QQ and other online chat softwares. In order to find the closely connected subgraphs wit...
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Complex software systems typically involve-features like time, concurrency and probability, where probabilistic computations play an increasing role. It is challenging to formalize languages comprising all these featu...
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ISBN:
(纸本)9780769526249
Complex software systems typically involve-features like time, concurrency and probability, where probabilistic computations play an increasing role. It is challenging to formalize languages comprising all these features. In this paper we integrate probability, time and concurrency in one single model, where the concurrency-feature is modelled using shared-variable based communication. The probability feature is represented by a probabilistic nondeterministic choice, probabilistic guarded choice and a probabilistic version of parallel composition. We formalize an operational semantics for such an integration. Based on this model we define a bisimulation relation, from which an observational equivalence between probabilistic programs is investigated and a collection of algebraic laws are explored. We also implement a prototype of the operational semantics to animate the execution of probabilistic programs.
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