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The year 1988 was notable for being the centennial of playwright Eugene O'Neill's birth and a time of unprecedented democratization in the People's Republic of China and rapprochement with the West. In this optimal climate, a remarkable festival and conference devoted to O'Neill was held in Nanjing, China, orchestrated mainly by Haiping Liu, who secured the funds and cooperation necessary to lure noted O'Neill scholars and theatre artists from around the world. Liu selected and edited papers for publication after the conference, but he realized that this would be a difficult task conducted...

Due to advances in sensor, storage, and networking technologies, data is being generated on a daily basis at an ever-increasing pace in a wide range of applications, including cloud computing, mobile Internet, and medical imaging. This large multidimensional data requires more efficient dimensionality reduction schemes than the traditional techniques. Addressing this need, multilinear subspace learning (MSL) reduces the dimensionality of big data directly from its natural multidimensional representation, a tensor.

Multilinear Subspace Learning: Dimensionality Reduction of...

Chinese Women Writers and the Feminist Imagination, 1905-1948 provides a compelling study of leading women writers in modern China, charting their literary works and life journeys to examine the politics and poetics of Chinese transcultural feminism that exceed the boundaries of bourgeois feminist selfhood.

Unlike recent literary studies that focus on the discursive formation of the modern Chinese nation state and its gendering effects, Haiping Yan explores the radical degrees to which Chinese women writers re-invented their lives alongside their writings in distinctly...

This book highlights a comprehensive introduction to the fundamental statistical mechanics underneath the inner workings of neural networks. The book discusses in details important concepts and techniques including the cavity method, the mean-field theory, replica techniques, the Nishimori condition, variational methods, the dynamical mean-field theory, unsupervised learning, associative memory models, perceptron models, the chaos theory of recurrent neural networks, and eigen-spectrums of neural networks, walking new learners through the theories and must-have skillsets to understand and...