Event Indexing Systems for Efficient Selection and Analysis of HERA Data

The design and implementation of two software systems introduced to improve the efficiency of offline analysis of event data taken with the ZEUS Detector at the HERA electron-proton collider at DESY are presented. Two different approaches were made, one using a set of event directories and the other using a tag database based on a commercial object-oriented database management system. These are described and compared. Both systems provide quick direct access to individual collision events in a sequential data store of several terabytes, and they both considerably improve the event analysis efficiency. In particular the tag database provides a very flexible selection mechanism and can dramatically reduce the computing time needed to extract small subsamples from the total event sample. Gains as large as a factor 20 have been obtained.Comment: Accepted for publication in Computer Physics Communication

Multitask learning without label correspondences

We propose an algorithm to perform multitask learning where each task has potentially distinct label sets and label correspondences are not readily available. This is in contrast with existing methods which either assume that the label sets shared by different tasks are the same or that there exists a label mapping oracle. Our method directly maximizes the mutual information among the labels, and we show that the resulting objective function can be efficiently optimized using existing algorithms. Our proposed approach has a direct application for data integration with different label spaces for the purpose of classification, such as integrating Yahoo! and DMOZ web directories