The mathematical theory of computation has given rise to two important ap proaches to the informal notion of "complexity" Kolmogorov complexity, usu ally a complexity measure for a single object such as a string, a sequence etc., measures the amount of information necessary to describe the object. Compu tational complexity, usually a complexity measure for a set of objects, measures the compuational resources necessary to recognize or produce elements of the set. The relation between these two complexity measures has been considered for more than two decades, and may interesting and deep observations have been obtained. In March 1990, the Symposium on Theory and Application of Minimal Length Encoding was held at Stanford University as a part of the AAAI 1990 Spring Symposium Series. Some sessions of the symposium were dedicated to Kolmogorov complexity and its relations to the computational complexity the ory, and excellent expository talks were given there. Feeling that, due to the importance of the material, some way should be found to share these talks with researchers in the computer science community, I asked the speakers of those sessions to write survey papers based on their talks in the symposium. In response, five speakers from the sessions contributed the papers which appear in this book."

This book constitutes the refereed proceedings of the 22nd International Symposium on Algorithms and Computation, ISAAC 2011, held in Yokohama, Japan in December 2011. The 76 revised full papers presented together with two invited talks were carefully reviewed and selected from 187 submissions for inclusion in the book. This volume contains topics such as approximation algorithms; computational geometry; computational biology; computational complexity; data structures; distributed systems; graph algorithms; graph drawing and information visualization; optimization; online and streaming algorithms; parallel and external memory algorithms; parameterized algorithms; game theory and internet algorithms; randomized algorithms; and string algorithms.

In 1996 the International Federation for Information Processing (IFIP) establ- hed its rst Technical Committee on foundations of computer science, TC1. The aim of IFIP TC1 is to support the development of theoretical computer science as a fundamental science and to promote the exploration of fundamental c- cepts, models, theories, and formal systems in order to understand laws, limits, and possibilities of information processing. This volume constitutes the proceedings of the rst IFIP International C- ference on Theoretical Computer Science (IFIP TCS 2000) { Exploring New Frontiers of Theoretical Informatics { organized by IFIP TC1, held at Tohoku University, Sendai, Japan in August 2000. The IFIP TCS 2000 technical program consists of invited talks, contributed talks, and a panel discussion. In conjunction with this program there are two special open lectures by Professors Jan van Leeuwen and Peter D. Mosses. The decision to hold this conference was made by IFIP TC1 in August 1998, and since then IFIP TCS 2000 has bene ted from the e orts of many people; in particular, the TC1 members and the members of the Steering Committee, the Program Committee, and the Organizing Committee of the conference. Our special thanks go to the Program Committee Co-chairs: Track (1): Jan van Leeuwen (U. Utrecht), Osamu Watanabe (Tokyo Inst. Tech.) Track (2): Masami Hagiya (U. Tokyo), Peter D. Mosses (U. Aarhus).

ThisvolumecontainsallthepaperspresentedattheInternationalConferenceon Algorithmic Learning Theory 1999 (ALT'99), held at Waseda University Int- nationalConferenceCenter, Tokyo, Japan, December 6?8,1999.Theconference was sponsored by the Japanese Society for Arti cial Intelligence (JSAI). In response to the call for papers, 51 papers on all aspects of algorithmic learning theory and related areas were submitted, of which 26 papers were - lected for presentation by the program committee based on their originality, quality, and relevance to the theory of machine learning. In addition to these regular papers, this volume contains three papers of invited lectures presented byKatharinaMorikoftheUniversityofDortmund, RobertE.SchapireofAT&T Labs, Shannon Lab., and Kenji Yamanishi of NEC, C&C Media Research Lab. ALT'99 is not just one of the ALT conference series, but this conference marks the tenth anniversary in the series that was launched in Tokyo, in Oc- ber 1990, for the discussion of research topics on all areas related to algorithmic learning theory. The ALT series was renamedlast year from\ALT workshop"to \ALT conference,"expressing its wider goalof providing an ideal forum to bring together researchers from both theoretical and practical learning communities, producing novel concepts and criteria that would bene t both. This movement wasre?ectedinthepaperspresentedatALT'99, wheretherewereseveralpapers motivated by application oriented problems such as noise, data precision, etc. Furthermore, ALT'99 benet ed from being held jointly with the 2nd Inter- tional Conference on Discovery Science (DS'99), the conference for discussing, among other things, more applied aspects of machine learning. Also, we could celebrate the tenth anniversary of the ALT series with researchers from both theoretical and practical communities.

This book constitutes the refereed proceedings of the 5th International Symposium on Stochastic Algorithms, Foundations and Applications, SAGA 2009, held in Sapporo, Japan, in October 2009.

The 15 revised full papers presented together with 2 invited papers were carefully reviewed and selected from 22 submissions. The papers are organized in topical sections on learning, graphs, testing, optimization and caching, as well as stochastic algorithms in bioinformatics.