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“A Veteran and Spectacular Politician – Singapore’s Mr. Chan Chee Seng
Professor (Dr) HO Kim Hin, David PhD (University of Cambridge), MPhil (1st Cl Hons with Distinction) (University of Cambridge); Honorary Professor (Development Economics & Land Economy) (University of Hertfordshire); Honorary Doctorate of Letters (International Biographical Centre) (Cambridge); Systems Engineering (US Naval Postgraduate School), MRES (UK), AM NCREIF (US), FARES (US), MAEA (US), MESS, MSIM.Retiree (31 May 2019 aged 62 years) (School of Design and Environment) (National University of Singapore). Professor (Dr) HO Kim Hin, David, spent 31 years across several sectors, including the military, oil refining, aerospace engineering, public housing, resettlement, land acquisition, re...
Singapore Struggle for Success
Singapore: Struggle for Success is the definitive account of the events that resurrected Singapore—events that continue to shape the life of every Singaporean. Within a single generation Singaporeans underwent an extraordinary transformation. During three decades of violence and instability, Singapore was nearly torn apart by foreign occupation, political upheaval and communist urban revolution. Yet today this island state is a haven of tranquility and one of the most prosperous nations in Asia. How Lee Kuan Yew and his political colleagues persuaded the British government in the 1950s to take a gamble with home rule; how they outwitted the Communist in the 1960s; how they transformed an underdeveloped, disparate Chinese, Malay, Indian and Caucasian community from a state of poverty and political unrest into a thriving, modern nation of the 1990s—this is the theme of this meticulously researched and very readable work. Explaining Singapore’s transformation, the author describes the dramatic events that brought about the very best and the very worst in the leading personalities of the time: honour and treachery, courage and cowardice, selflessness and venality
Neural Information Processing. Theory and Algorithms
The two volume set LNCS 6443 and LNCS 6444 constitutes the proceedings of the 17th International Conference on Neural Information Processing, ICONIP 2010, held in Sydney, Australia, in November 2010. The 146 regular session papers presented were carefully reviewed and selected from 470 submissions. The papers of part I are organized in topical sections on neurodynamics, computational neuroscience and cognitive science, data and text processing, adaptive algorithms, bio-inspired algorithms, and hierarchical methods. The second volume is structured in topical sections on brain computer interface, kernel methods, computational advance in bioinformatics, self-organizing maps and their applications, machine learning applications to image analysis, and applications.
The Singapore Lion
"Irene Ng has written a book that gives a comprehensive portrayal of Mr Rajaratnam - one of Singapore's outstanding leaders who played a crucial part in the momentous and crisis-ridden transition to iindependence. This is a book about the man and his wisdom. One would fail to appreciate him until one reads this absorbing book and reflects on the acuity and breadth of his insights and his wisdom." - S. R. Nathan, President of Singapore "In the course of a thirty-three year career in diplomacy, I met many great leaders. Having done so, I can confidently assert that S. Rajaratnam was one of the greatest leaders I met. Sadly, few in Singapore understand how great Rajaratnam was. This well-resear...
Advances in Neural Networks- ISNN 2013
The two-volume set LNCS 7951 and 7952 constitutes the refereed proceedings of the 10th International Symposium on Neural Networks, ISNN 2013, held in Dalian, China, in July 2013. The 157 revised full papers presented were carefully reviewed and selected from numerous submissions. The papers are organized in following topics: computational neuroscience, cognitive science, neural network models, learning algorithms, stability and convergence analysis, kernel methods, large margin methods and SVM, optimization algorithms, varational methods, control, robotics, bioinformatics and biomedical engineering, brain-like systems and brain-computer interfaces, data mining and knowledge discovery and other applications of neural networks.
Neural Information Processing
The six volume set LNCS 10634, LNCS 10635, LNCS 10636, LNCS 10637, LNCS 10638, and LNCS 10639 constitues the proceedings of the 24rd International Conference on Neural Information Processing, ICONIP 2017, held in Guangzhou, China, in November 2017. The 563 full papers presented were carefully reviewed and selected from 856 submissions. The 6 volumes are organized in topical sections on Machine Learning, Reinforcement Learning, Big Data Analysis, Deep Learning, Brain-Computer Interface, Computational Finance, Computer Vision, Neurodynamics, Sensory Perception and Decision Making, Computational Intelligence, Neural Data Analysis, Biomedical Engineering, Emotion and Bayesian Networks, Data Mining, Time-Series Analysis, Social Networks, Bioinformatics, Information Security and Social Cognition, Robotics and Control, Pattern Recognition, Neuromorphic Hardware and Speech Processing.
Computer Vision – ECCV 2022
The 39-volume set, comprising the LNCS books 13661 until 13699, constitutes the refereed proceedings of the 17th European Conference on Computer Vision, ECCV 2022, held in Tel Aviv, Israel, during October 23–27, 2022. The 1645 papers presented in these proceedings were carefully reviewed and selected from a total of 5804 submissions. The papers deal with topics such as computer vision; machine learning; deep neural networks; reinforcement learning; object recognition; image classification; image processing; object detection; semantic segmentation; human pose estimation; 3d reconstruction; stereo vision; computational photography; neural networks; image coding; image reconstruction; object recognition; motion estimation.
Federated Learning
This book provides a comprehensive and self-contained introduction to federated learning, ranging from the basic knowledge and theories to various key applications. Privacy and incentive issues are the focus of this book. It is timely as federated learning is becoming popular after the release of the General Data Protection Regulation (GDPR). Since federated learning aims to enable a machine model to be collaboratively trained without each party exposing private data to others. This setting adheres to regulatory requirements of data privacy protection such as GDPR. This book contains three main parts. Firstly, it introduces different privacy-preserving methods for protecting a federated lear...
