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AdaBoost has attracted much attention in the machine learning community because of its excellent performance in combining weak classifiers into strong classifiers. However, AdaBoost tends to overfit to the noisy data in many applications. Accordingly, improving the antinoise ability of AdaBoost plays an important role in many applications. The sensitiveness to the noisy data of AdaBoost stems from...
Nowadays, machine learning based methods are among the most popular ones for malware detection. However, most of the previous works use a single type of features, dynamic or static, and take them to build a binary classification model. These methods have limited ability to depict characteristic malware behaviors and suffer from insufficiently sampled benign samples and extremely imbalanced training...
Entrepreneurial firms are faced with challenges of liabilities of newness and liabilities of smallness, which can directly result in a lack of resources. Leveraging resources is a key to resolve these difficulties. To make the best of leveraging resources, entrepreneurial firms need to raise their absorptive capacity by developing the abilities of learning, cooperation and organization. As a result,...
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