高级人工智能6资料.ppt

华东理工大学计算机系 2014.10.31 高级人工智能 第五章 文献阅读 Zhihua Zhang, Cheng Chen, Guang Dai, Wu-Jun Li, Dit-Yan Yeung, Multicategory large margin classification methods: Hinge losses vs. coherence functions, Artificial Intelligence, 215 (2014) 55–78. 第五章 文献阅读 Abstract: Generalization of large margin classi?cation methods from the binary classi?cation setting to the more general multicategory setting is often found to be non-trivial. In this paper, we study large margin classi?cation methods that can be seamlessly applied to both settings, with the binary setting simply as a special case. In particular, we explore the Fisher consistency properties of multicategory majorization losses and present a construction framework of majorization losses of the 0–1 loss. Under this framework, we conduct an in-depth analysis about three widely used multicategory hinge losses. Corresponding to the three hinge losses, we propose three multicategory majorization losses based on a coherence function. The limits of the three coherence losses as the temperature approaches zero are the corresponding hinge losses, and the limits of the minimizers of their expected errors are the minimizers of the expected errors of the corresponding hinge losses. Finally, we develop multicategory large margin classi?cation methods by using a so-called multiclass C -loss. 第五章 文献阅读 aims and scope Artificial Intelligence and Philosophy Automated reasoning and inference Case-based reasoning Cognitive aspects of AI Commonsense reasoning Constraint processing Heuristic search High-level computer vision Intelligent interfaces Intelligent robotics Knowledge representation Machine learning Multiagent systems Natural language processing Planning and theories of action Reasoning under uncertainty or imprecision 第五章 文献阅读 P. Sun, M.D. Reid, Jie Zhou, An improved multiclass LogitBoost using adaptive-one-vs-one, Mach Learn (2014) 97:295–326. 第五章 文献阅读 Michael R. Smith, Tony Martinez, C