Artificial neural networks, or simply called neural networks, refer to the various mathematical models of human brain functions such as perception, computation and memory. It is a fascinating scientific challenge of our time to understand how the human brain works. Modeling neural networks facilitates us in investigating the...

This monograph presents a comparison of methods for organizing very large amounts of stored data called a very large database to facilitate fast retrieval of desired information on direct access storage devices. In a very large data base involving retrieval and updating, the major factor of immediate concern is the average number of accesses...

Tpreface his book is designed for a two-semester sequence in computer science, beginning with what is typically known as Data Structures and continuing with advanced data structures and algorithm analysis. It is appropriate for the courses from both the two-course and three-course sequences in “B.1 Introductory Tracks,” as...

In the last three decades, machine learning research and practice have focused on batch learning usually using small datasets. In batch learning, the whole training data is available to the algorithm, which outputs a decision model after processing the data eventually (or most of the times) multiple times. The rationale behind this...

In the early 1990s, the establishment of the Internet brought forth a revolutionary viewpoint of information storage, distribution, and processing: the World-Wide Web is becoming an enormous and expanding distributed digital library. Along with the development of the Web, image indexing and retrieval have grown into research areas...

T^his book is designed for a two-semester sequence in computer science, beginning with what is typically known as Data Structures and continuing with advanced data structures and algorithm analysis. It is appropriate for the courses from both the two-course and three-course sequences in "B.l...

Approximation algorithms have developed in response to the impossibility of solving a great variety of important optimization problems. Too frequently, when attempting to get a solution for a problem, one is confronted with the fact that the problem is NP-haid. This, in the words of Garey and Johnson, means "I can't find an...

I became interested in ML programming when I taught CS109, the introduc- tory Computer Science Foundations course at Stanford, starting in 1991. ML was used by several of the instructors of this course, including Stu Reges and Mike Cleron, to introduce concepts such as functional programming and type systems. It was also used for the...

Geographical Information Systems (GIS) are computer systems for storing, displaying and analyzing spatial data. The past twenty years have seen a rapid growth in their use in government, commerce and academia, and they can be used for managing a network of utilities, from handling census data through to planning the location of a new...

A variety of problems m machine learning and digital communication deal with complex but structured natural or artificial systems. Natural patterns mat we wish to automatically classify' are a consequence of a hierarchical causal physical process. Learning about the world m which we live requires mat we extract useful sensor)'...

ICALP 2011, the 38th edition of the International Colloquium on Automata, Languages and Programming, was held in Z¨urich, Switzerland, during July 4–8, 2011. ICALP is a series of annual conferences of the European Association for Theoretical Computer Science (EATCS) which first took place in 1972. This year, the ICALP...

From its inception in the 1930s, the rich and vigorous field of computer science has been concerned with the resources, both in time and in memory, needed to carry out a computation. A number of fundamental theorems were discovered that resorted to a worst-case analysis. The central question was whether a given algorithm could be...