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Locating Chinese Women
This ground-breaking edited collection draws together Australian historical scholarship on Chinese women, their gendered migrations, and their mobile lives between China and Australia. It considers different aspects of women’s lives, both as individuals and as the wives and daughters of immigrant men. While the number of Chinese women in Australia before 1950 was relatively small, their presence was significant and often subject to public scrutiny. Moving beyond traditional representations of women as hidden and silent, this book demonstrates that Chinese Australian women in the twentieth century expressed themselves in the public eye, whether through writings, in photographs, or in politi...
Ensemble Machine Learning
It is common wisdom that gathering a variety of views and inputs improves the process of decision making, and, indeed, underpins a democratic society. Dubbed “ensemble learning” by researchers in computational intelligence and machine learning, it is known to improve a decision system’s robustness and accuracy. Now, fresh developments are allowing researchers to unleash the power of ensemble learning in an increasing range of real-world applications. Ensemble learning algorithms such as “boosting” and “random forest” facilitate solutions to key computational issues such as face recognition and are now being applied in areas as diverse as object tracking and bioinformatics. Responding to a shortage of literature dedicated to the topic, this volume offers comprehensive coverage of state-of-the-art ensemble learning techniques, including the random forest skeleton tracking algorithm in the Xbox Kinect sensor, which bypasses the need for game controllers. At once a solid theoretical study and a practical guide, the volume is a windfall for researchers and practitioners alike.
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