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Presents the introductory welcome message from the conference proceedings. May include the conference officers' congratulations to all involved with the conference event and publication of the proceedings record.
Provides an abstract for each of the keynote presentations and a brief professional biography of each presenter. The complete presentations were not made available for publication as part of the conference proceedings.
Presents the introductory welcome message from the conference proceedings. May include the conference officers' congratulations to all involved with the conference event and publication of the proceedings record.
A key problem in large-scale reinforcement learning is to deal with big data, in terms of a very large number of environment states and many possible actions. Function approximation can improve the ability of a reinforcement learner to solve large-scale problems. Tile coding and Kanerva coding are two classical methods for implementing function approximation, but these methods may give poor performance...
An increasing number of online news triggers wide academic concern for the prediction of news popularity, which is affected by users' behaviors and not easy to predict. However, existing methods that predict the popularity of online news after publication are not timely enough, and predicting before publication lacks discriminatory features. This paper explores the variables which may affect news...
In order to reduce imaging time of complex targets in a large scene, an efficient strip-mode microwave correlated imaging method with data fusion is proposed. Due to its rangegate feature, while random radiation radar array transmits narrow-pulse random signals synchronously, the whole imaging area can be divided into multiple imaging strips in the range direction. By analyzing the temporal-spatial...
Classification of text documents is commonly carried out using various models of bag-of-words that are generated using feature selection methods. In these models, selected features are used as input to well-known classifiers such as Support Vector Machines (SVM) and neural networks. In recent years, a technique called word embeddings has been developed for text mining and, deep learning models using...
The connectivity of large scale complex networks relies on a specific small set of structural nodes which is called the core of the whole network. The influence maximization problem is to identify such set of nodes, known as influencers, who can trigger the maximum range of information propagation in a network, which is one of the most important problems in network science. In this paper, we introduce...
Cloud computing usage has increased in recent years as a consequence of its benefits such as agility on resource provisioning, elasticity, and reduced costs. However, once organizations migrate to cloud environments they lose control of the underlying structure of their applications such as physical networking, storage, and servers. Therefore, the cloud may pose privacy threats to sensitive data that...
Social robots are regarded as convenient tools in education due to their capabilities of improving knowledge acquisition. Using cognitive dissonance as a teaching tool has been popular in STEM learning too. This paper presents a design for a cutting-edge different experiments where we describe a procedure that induces cognitive dissonance and different conditions that may boost the student's ability...
Nowadays applications need to deal with a large number of concurrent requests. These systems must be stress tested to ensure that they can function correctly under a load. In this context, a research field called Search-based Software Testing has become increasingly important. Most of the search-based test methods are based on single objective optimization. In the case of multi-objective optimization...
Passive spectrum monitoring is important for network diagnosis and radio frequency management in spectrum-sharing wireless networks, i.e., cognitive radio network. Most of the related work focused on the sniffer-channel assignment problem, i.e, assigning proper operational channel to wireless sniffers with the aim of tracking and capturing the target signals or data packets. These approaches were...
This paper studied downlink multicasting in a wirelessly powered communication network, where multiple energy-constrained relay nodes collaboratively assist the transmissions from a multi-antenna hybrid access point (HAP) to multiple receivers in the downlink. Each relay is equipped with a single antenna and capable of energy harvesting (EH) from the HAP's RF signals in a power splitting protocol...
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