Towards recognition of pleural effusion images
Higher School of Economics (HSE) and supported by the Information Retrieval Specialist Group at the British Computer Society (BCS–IRSG). The conference was held during March 24–27, 2013, in Moscow, Russia – the easternmost location in the history of the ECIR series. ECIR 2013 received a total of 287 submissions in three categories: 191 full papers, 78 posters, and 18 demonstrations. The geographical distribution of the submissions is as follows: 70% were from Europe (including 9% from Russia), 17% from Asia, 12% from North and South America, and 3% from the rest of the world. All submissions were reviewed by at least three members of an international two-tier Program Committee. Of the papers submitted to the main research track, 30 were selected for oral presentation and 25 for poster/short presentation (16% and 13%, respectively, hence a 29% acceptance rate). In addition, 38 posters (49%) and 10 demonstrations (56%) were accepted. The accepted contributions represent the state of the art in information retrieval, cover a diverse range of topics, propose novel applications, and indicate promising directions for future research. Out of accepted contributions, 66% have a student as the primary author. We gratefully thank all Program Committee members for their time and efforts ensuring a high-quality level of the ECIR 2013 program. Additionally, ECIR 2013 hosted four tutorials and two workshops covering various IR-related topics. We express our gratitude to the Workshop Chair, Evgeniy Gabrilovich, and the Tutorial Chair, Djoerd Hiemstra, and the members of their committees.
– Searching the Web of Data
– Practical Online Retrieval Evaluation
– Cross-Lingual Probabilistic Topic Modeling and Its Applications in Information
– Distributed Information Retrieval and Applications
– From Republicans to Teenagers: Group Membership and Search (GRUMPS)
– Integrating IR Technologies for Professional Search
The conference included a Mentoring Program and Doctoral Consortium.
We thank Mikhail Ageev and Hideo Joho and Dmitriy Ignatov, respectively, for coordinating these activities.
We would like to thank our invited speakers – Mor Naaman (Rutgers University, Social Media Information Lab) and the winner of the Karen Sparck Jones award. The Industry Day took place on the final day of the conference and featured a bright assortment of talks given by prominent researchers and practitioners: Paul Ogilvie (LinkedIn), Hilary Mason (bitly), Antonio Gulli (Bing), Andrey Kalinin (Mail.Ru), Jimmy Lin (Twitter/University of Maryland), Marc Najork (Microsoft Research), and Andrey Styskin (Yandex), to whom we express our gratitude. We appreciate generous financial support from Yandex and HSE, as well as from our sponsorsMail.Ru and Russian Foundation for Basic Research (platinum level), Google and ABBYY
В статье дается краткое введение в ансамбли классификаторов в машинном обучении и описывается алгоритм, повышающий качество классификации за счет рекомендации классификаторов объектам. Гипотеза, заложенная в основу алгоритма, состоит в том, что классификатор скорее правильно классифицирует объект, если он правильно предсказал метки соседей этого объекта из обучающей выборки. Автор иллюстрирует принцип алгоритма на простом примере и описывает тестирование на реальных данных.
В статье рассмотрена проблема прогнозирования численности клиентской базы компании в рамках решения задачи управления клиентами. Автором предложен новый подход к сегментоориентированному прогнозированию численности клиентов, в основе которого лежит адаптация модели движения кадров О.В. Староверова. Также в статье рассмотрены условия применимости данной модели и модификация основных положений в зависимости от характера взаимоотношений клиента и компании.
This book constitutes the refereed proceedings of the 6th IAPR TC3 International Workshop on Artificial Neural Networks in Pattern Recognition, ANNPR 2014, held in Montreal, QC, Canada, in October 2014. The 24 revised full papers presented were carefully reviewed and selected from 37 submissions for inclusion in this volume. They cover a large range of topics in the field of learning algorithms and architectures and discussing the latest research, results, and ideas in these areas.
In this paper, we use robust optimization models to formulate the support vector machines (SVMs) with polyhedral uncertainties of the input data points. The formulations in our models are nonlinear and we use Lagrange multipliers to give the first-order optimality conditions and reformulation methods to solve these problems. In addition, we have proposed the models for transductive SVMs with input uncertainties.
This volume is the first of its kind to offer a detailed, monographic treatment of Semitic genealogical classification. The introduction describes the author's methodological framework and surveys the history of the subgrouping discussion in Semitic linguistics, and the first chapter provides a detailed description of the proto-Semitic basic vocabulary. Each of its seven main chapters deals with one of the key issues of the Semitic subgrouping debate: the East/West dichotomy, the Central Semitic hypothesis, the North West Semitic subgroup, the Canaanite affiliation of Ugaritic, the historical unity of Aramaic, and the diagnostic features of Ethiopian Semitic and of Modern South Arabian. The book aims at a balanced account of all evidence pertinent to the subgrouping discussion, but its main focus is on the diagnostic lexical features, heavily neglected in the majority of earlier studies dealing with this subject. The author tries to assess the subgrouping potential of the vocabulary using various methods of its diachronic stratification. The hundreds of etymological comparisons given throughout the book can be conveniently accessed through detailed lexical indices.