Partially Supervised Learning - Second IAPR International Workshop, PSL 2013, Nanjing, China, May 13-14, 2013, Revised Selected Papers

This book constitutes the thoroughly refereed revised selected papers from the Second IAPR International Workshop, PSL 2013, held in Nanjing, China, in May 2013. The 10 papers included in this volume were carefully reviewed and selected from 26 submissions. Partially supervised learning is a rapidly evolving area of machine learning. It generalizes many kinds of learning paradigms including supervised and unsupervised learning, semi-supervised learning for classification and regression, transductive learning, semi-supervised clustering, multi-instance learning, weak label learning, policy learning in partially observable environments, etc.

List of contents

Partially Supervised Anomaly Detection using Convex Hulls on a 2D Parameter Space.- Self-Practice Imitation Learning from Weak Policy.- Semi-Supervised Dictionary Learning of Sparse Representations for Emotion Recognition.- Adaptive Graph Constrained NMF for Semi-Supervised Learning.- Kernel Parameter Optimization in Stretched Kernel-based Fuzzy Clustering.- Conscientiousness Measurement from Weibo's Public Information.- Meta-Learning of Exploration and Exploitation Parameters with Replacing Eligibility Traces.- Neighborhood Co-regularized Multi-view Spectral Clustering of Microbiome Data.- A Robust Image Watermarking Scheme Based on BWT and ICA.- A New Weighted Sparse Representation Based on MSLBP and Its Application to Face Recognition.

Product details

• Assisted by: Schwenker (Editor), Schwenker (Editor), Friedhelm Schwenker (Editor), Zhi-Hu Zhou (Editor), Zhi-Hua Zhou (Editor)
• Publisher: Springer, Berlin
• Languages: English
• Product format: Paperback / Softback
• Released: 02.08.2013
• EAN: 9783642407048
• ISBN: 978-3-642-40704-8
• No. of pages: 117
• Dimensions: 154 mm x 11 mm x 236 mm
• Weight: 207 g
• Illustrations: IX, 117 p. 34 illus.
• Series: Lecture Notes in Computer Science; Lecture Notes in Artificial Intelligence; Lecture Notes in Computer Science / Lecture Notes in Artificial Intelligence; Lecture Notes in Computer Science; Lecture Notes in Artificial Intelligence
• Subjects: Natural sciences, medicine, IT, technology > IT, data processing > IT; C, Data Mining, Artificial Intelligence, computer science, pattern recognition, Data Mining and Knowledge Discovery, Automated Pattern Recognition, Expert systems / knowledge-based systems