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The basic paradigm of asset pricing is in vibrant f lux. The purely rational approach is being subsumed by a broader approach based upon the psychology of investors. In this approach, security expected returns are determined by both risk and misvaluation. This survey sketches a framework for understanding decision biases, evaluates the a priori arguments(More)
In region-based image annotation, keywords are usually associated with images instead of individual regions in the training data set. This poses a major challenge for any learning strategy. In this paper, we formulate image annotation as a supervised learning problem under Multiple-Instance Learning (MIL) framework. We present a novel Asymmetrical Support(More)
In this paper, we consider two important problems for distributed fault-tolerant detection in wireless sensor networks: 1) how to address both the noise-related measurement error and sensor fault simultaneously in fault-tolerant detection and 2) how to choose a proper neighborhood size n for a sensor node in fault correction such that the energy could be(More)
This paper tests the hypothesis that irrational market misvaluation affects firms’ takeover behavior. We employ two contemporaneous proxies for market misvaluation, pre-takeover book/price ratios and pre-takeover ratios of residual income model value to price. Misvaluation of bidders and targets influences the means of payment chosen, the mode of(More)
Biological invasions have become a significant threat to the global environment. Unfortunately, to date there is no consensus on invasion mechanisms and predictive models. Controversies range from whether we can reliably predict which species may become invasive to which species characteristics (e.g., life history, taxonomic groups, or geographic origin)(More)
BACKGROUND AND AIMS Many notorious alien invasive plants are clonal, but little is known about some roles and aspects of clonal integration. Here, the hypothesis is tested that clonal integration affects growth, photosynthetic efficiency, biomass allocation and competitive ability of the exotic invasive weed Alternanthera philoxeroides (Amaranthaceae). (More)
Coclustering heterogeneous data has attracted extensive attention recently due to its high impact on various important applications, such us text mining, image retrieval, and bioinformatics. However, data coclustering without any prior knowledge or background information is still a challenging problem. In this paper, we propose a Semisupervised Non-negative(More)
Conventional techniques of estimating takeover value improvements measure only a fraction of the total gain, and include revelation about bidder stand-alone value. To address these biases, we develop the Probability Scaling Method, which rescales announcement date returns; and the Intervention Method, which uses returns at intervening events. Perceived(More)
Traditional clustering algorithms are inapplicable to many real-world problems where limited knowledge from domain experts is available. Incorporating the domain knowledge can guide a clustering algorithm, consequently improving the quality of clustering. In this paper, we propose SS-NMF: a semi-supervised non-negative matrix factorization framework for(More)
In an annotated image database, keywords are usually associated with images instead of individual regions, which poses a major challenge for any region based image annotation algorithm. In this paper, we propose to learn the correspondence between image regions and keywords through Multiple-Instance Learning (MIL). After a representative image region has(More)