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John and Thomas--Gospels in Conflict?
The hypothesis that the Fourth Gospel is a theological response to the Gospel of Thomas is a recent development in the study of the New Testament and early Christianity. Assuming an early date for the Gospel of Thomas, the proponents of this hypothesis argue that the supposed polemical presentation of Thomas in the Fourth Gospel is evidence of a conflict between the early communities associated respectively with John and Thomas. However, a detailed narrative study reveals that the Fourth Gospel portrays a host of characters--disciples and non-disciples--in an equally unflattering light where an understanding of Jesus's origins, message, and mission are concerned. The present study attempts to demonstrate that the Fourth Gospel's presentation of Thomas is part and parcel of its treatment of uncomprehending characters. If this thesis is correct, it poses a significant challenge to the assumption that the Fourth Gospel contains a polemic against Thomas, or that it was written in response to the Gospel of Thomas or the community associated with Thomas.
The Cases That Haunt Us
Certain criminal cases have a life of their own. Despite the passage of years they continue their hold on the public imagination, either because of the personalities involved, the depravity of the crime, doubts over whether justice was done, or the tantalizing fact that no one was ever caught... Now John Douglas, the foremost investigative analyst and criminal profiler of our time, turns his attention to eight of the greatest mysteries in the history of crime, including those of Jack the Ripper, The Boston Strangler and JonBenet Ramsey. Taking a fresh look at the established facts, Douglas and Olshaker dismantle the conventional wisdom regarding these most notorious of crimes and rebuild them - with astonishing results.
Learning Theory
This book constitutes the refereed proceedings of the 19th Annual Conference on Learning Theory, COLT 2006, held in Pittsburgh, Pennsylvania, USA, June 2006. The book presents 43 revised full papers together with 2 articles on open problems and 3 invited lectures. The papers cover a wide range of topics including clustering, un- and semi-supervised learning, statistical learning theory, regularized learning and kernel methods, query learning and teaching, inductive inference, and more.
Algorithmic Learning Theory
This volume contains papers presented at the 19th International Conference on Algorithmic Learning Theory (ALT 2008), which was held in Budapest, Hungary during October 13–16, 2008. The conference was co-located with the 11th - ternational Conference on Discovery Science (DS 2008). The technical program of ALT 2008 contained 31 papers selected from 46 submissions, and 5 invited talks. The invited talks were presented in joint sessions of both conferences. ALT 2008 was the 19th in the ALT conference series, established in Japan in 1990. The series Analogical and Inductive Inference is a predecessor of this series: it was held in 1986, 1989 and 1992, co-located with ALT in 1994, and s- sequently merged with ALT. ALT maintains its strong connections to Japan, but has also been held in other countries, such as Australia, Germany, Italy, Sin- pore, Spain and the USA. The ALT conference series is supervised by its Steering Committee: Naoki Abe (IBM T. J.
Inductive Logic Programming
This book constitutes the thoroughly refereed post-proceedings of the 12th International Conference on Inductive Logic Programming, ILP 2002, held in Sydney, Australia in July 2002. The 22 revised full papers presented were carefully selected during two rounds of reviewing and revision from 45 submissions. Among the topics addressed are first order decision lists, learning with description logics, bagging in ILP, kernel methods, concept learning, relational learners, description logic programs, Bayesian classifiers, knowledge discovery, data mining, logical sequences, theory learning, stochastic logic programs, machine discovery, and relational pattern discovery.
Inductive Logic Programming
This book constitutes the refereed proceedings of the 13th International Conference on Inductive Logic Programming, ILP 2003, held in Szeged, Hungary in September/October 2003. The 23 revised full papers presented were carefully reviewed and selected from 53 submissions. Among the topics addressed are multirelational data mining, complexity issues, theory revision, clustering, mathematical discovery, relational reinforcement learning, multirelational learning, inductive inference, description logics, grammar systems, and inductive learning.
Logical and Relational Learning
This first textbook on multi-relational data mining and inductive logic programming provides a complete overview of the field. It is self-contained and easily accessible for graduate students and practitioners of data mining and machine learning.
Advanced Methods for Knowledge Discovery from Complex Data
Knowledge discovery takes the raw results from data mining (the process of extracting trends or patterns from data) and transforms them into useful and understandable information. This book covers introductory material on the knowledge discovery process, advanced issues, and tools and techniques.
Advances in Neural Information Processing Systems 19
The annual Neural Information Processing Systems (NIPS) conference is the flagship meeting on neural computation and machine learning. This volume contains the papers presented at the December 2006 meeting, held in Vancouver.
Encyclopedia of Machine Learning
This comprehensive encyclopedia, in A-Z format, provides easy access to relevant information for those seeking entry into any aspect within the broad field of Machine Learning. Most of the entries in this preeminent work include useful literature references.
