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Algorithmic Learning Theory
This book constitutes the refereed proceedings of the 14th International Conference on Algorithmic Learning Theory, ALT 2003, held in Sapporo, Japan in October 2003. The 19 revised full papers presented together with 2 invited papers and abstracts of 3 invited talks were carefully reviewed and selected from 37 submissions. The papers are organized in topical sections on inductive inference, learning and information extraction, learning with queries, learning with non-linear optimization, learning from random examples, and online prediction.
You Need a Rocket!
A self-help, motivational book that guides you on how to take action in life to achieve your dreams. Addressing issues like making choices, taking responsibility, taking action, retaining focus, having discipline and making sacrifices, managing money and time, and being aware of associations.
Algorithmic Learning in a Random World
Algorithmic Learning in a Random World describes recent theoretical and experimental developments in building computable approximations to Kolmogorov's algorithmic notion of randomness. Based on these approximations, a new set of machine learning algorithms have been developed that can be used to make predictions and to estimate their confidence and credibility in high-dimensional spaces under the usual assumption that the data are independent and identically distributed (assumption of randomness). Another aim of this unique monograph is to outline some limits of predictions: The approach based on algorithmic theory of randomness allows for the proof of impossibility of prediction in certain situations. The book describes how several important machine learning problems, such as density estimation in high-dimensional spaces, cannot be solved if the only assumption is randomness.
Learning Kernel Classifiers
An overview of the theory and application of kernel classification methods. Linear classifiers in kernel spaces have emerged as a major topic within the field of machine learning. The kernel technique takes the linear classifier—a limited, but well-established and comprehensively studied model—and extends its applicability to a wide range of nonlinear pattern-recognition tasks such as natural language processing, machine vision, and biological sequence analysis. This book provides the first comprehensive overview of both the theory and algorithms of kernel classifiers, including the most recent developments. It begins by describing the major algorithmic advances: kernel perceptron learni...
Perspectives of Neural-Symbolic Integration
When it comes to robotics and bioinformatics, the Holy Grail everyone is seeking is how to dovetail logic-based inference and statistical machine learning. This volume offers some possible solutions to this eternal problem. Edited with flair and sensitivity by Hammer and Hitzler, the book contains state-of-the-art contributions in neural-symbolic integration, covering `loose' coupling by means of structure kernels or recursive models as well as `strong' coupling of logic and neural networks.
Ufos
Exciting, fully documented on-site personal investigations of UFOs.
Rain
John March is having a good day. He doesn't have many. Then it starts to rain. John March runs a struggling bookshop with just one regular customer - Mr. Hill. His life is defined by routine until the day he discovers he is sole beneficiary of a will worth £5 million thanks to the eccentric Mr. Hill's untimely death. But Mr. Hill also leaves behind something else - a lock of hair, a finger bone and a tooth in a jar of water. It's certainly not the worst day of John's life...until the rain comes and the dying starts. There is something in the rain and only John can give it what it wants. And yet, even when people are dying, even in the midst of terror, it's not the hardest thing John's ever faced. He faces horror every day when he locks his shop, drives to August House and opens the door to the room where his wife clings to life. But what he doesn't know could kill her, because if the rain doesn't get what it wants, his wife will serve just as well...*** A novel of the supernatural from the author of A Stranger's Grave, Masters of Blood and Bone, and Left to Darkness.
