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Adversarial learning is the study of machine learning techniques deployed in non-benign environments. Example applications include classifications for detecting spam email, network intrusion detection and credit card scoring. In fact as the gamut of application domains of machine learning grows, the possibility and opportunity for adversarial behavior will only increase. Till now, the standard assumption...
In this paper, we develop an online real-time system using Kinect and inertial measurement unit (IMU) to recognize and measure stairs for stair climbing tasks of erect mobile robots. This system combines the ideas of statistical characteristics of 3D point cloud data and adjustable geometric models for stair recognition tasks. Through this system, we not only verify the advantages of statistics methods...
In this paper, we describe a method for mining both frequent episodes and rare episodes in multiple data streams. The main issues include episodes mining and data streams relationship processing. Therefore, a mining algorithm together with two dedicated handling mechanisms is presented. We propose the concept of alternative support for discovering frequent and rare episodes, and define the semantic...
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