University of California, Irvine

About: University of California, Irvine is a education organization based out in Irvine, California, United States. It is known for research contribution in the topics: Population & Galaxy. The organization has 47031 authors who have published 113602 publications receiving 5521832 citations. The organization is also known as: UC Irvine & UCI.

Driven to distraction: Extraneous events and underreaction to earnings news

Abstract: Psychological evidence indicates that it is hard to process multiple stimuli and perform multiple tasks at the same time. This paper tests the INVESTOR DISTRACTION HYPOTHESIS, which holds that the arrival of extraneous news causes trading and market prices to react sluggishly to relevant news about a firm. Our test focuses on the competition for investor attention between a firm's earnings announcements and the earnings announcements of other firms. We find that the immediate stock price and volume reaction to a firm's earnings surprise is weaker, and post-earnings announcement drift is stronger, when a greater number of earnings announcements by other firms are made on the same day. Distracting news has a stronger effect on firms that receive positive than negative earnings surprises. Industry-unrelated news has a stronger distracting effect than related news. A trading strategy that exploits post-earnings announcement drift is unprofitable for announcements made on days with little competing news.

Locally adaptive dimensionality reduction for indexing large time series databases

Abstract: Similarity search in large time series databases has attracted much research interest recently. It is a difficult problem because of the typically high dimensionality of the data.. The most promising solutions involve performing dimensionality reduction on the data, then indexing the reduced data with a multidimensional index structure. Many dimensionality reduction techniques have been proposed, including Singular Value Decomposition (SVD), the Discrete Fourier transform (DFT), and the Discrete Wavelet Transform (DWT). In this work we introduce a new dimensionality reduction technique which we call Adaptive Piecewise Constant Approximation (APCA). While previous techniques (e.g., SVD, DFT and DWT) choose a common representation for all the items in the database that minimizes the global reconstruction error, APCA approximates each time series by a set of constant value segments of varying lengths such that their individual reconstruction errors are minimal. We show how APCA can be indexed using a multidimensional index structure. We propose two distance measures in the indexed space that exploit the high fidelity of APCA for fast searching: a lower bounding Euclidean distance approximation, and a non-lower bounding, but very tight Euclidean distance approximation and show how they can support fast exact searching, and even faster approximate searching on the same index structure. We theoretically and empirically compare APCA to all the other techniques and demonstrate its superiority.

Inotersen Treatment for Patients with Hereditary Transthyretin Amyloidosis

Abstract: Background Hereditary transthyretin amyloidosis is caused by pathogenic single-nucleotide variants in the gene encoding transthyretin (TTR) that induce transthyretin misfolding and systemi...

Artificial Intelligence and Tutoring Systems: Computational and Cognitive Approaches to the Communication of Knowledge

Abstract: From Marie Bienkowski's review : "Upon first encountering Etienne Wenger's book, "Artificial Intelligence and Tutoring Systems: Computational and Cognitive Approaches to the Communication of Knowledge," I assumed that it was the sort of book that would serve only as a reference. To find out about the EXCHECK tutoring system, I would just look it up in the exhaustive subject index. To see what tutoring work Beverly Woolf had done, I would look up her name in the author index. But, upon further examination, Wenger's book was revealed to be a good introductory text, first laying out basic issues in Chapters 1 and 2, then covering systems from SCHOLAR and SOPHIE to GUIDON and ACTP in Chapters 3 through 13. Each review chapter ends with a summary and an excellent set of bibliographic notes, further reinforcing the utility of the book as a reference and introduction to the field. In addition, it became clear that the book had another facet. As John Seely Brown and James Greeno point out in the introduction, "... this book is no mere catalog of programs and techniques... he has also laid out a provocative framework for analyzing and comparing intelligent tutoring systems." This framework is presented in Chapters 14 through 20. Thus, Wenger's book serves three purposes: it acts as a reference, it provides a comprehensive introduction to intelligent tutoring systems, and it develops a coherent framework for thinking about issues in any intelligent system that must communicate its knowledge." (http://dl.acm.org/citation.cfm?id=1059726)