This paper discusses a new approach to contingent claim valuation in general incomplete market models. We determine the neutral derivative price which occurs if investors maximize their local utility and if derivative demand and supply are balanced. We also introduce the sensitivity process of a contingent claim. This process quantifies the reliability of the neutral derivative price and it can...

We present a fully automated framework to estimate derivatives nonparametrically without estimating the regression function. Derivative estimation plays an important role in the exploration of structures in curves (jump detection and discontinuities), comparison of regression curves, analysis of human growth data, etc. Hence, the study of estimating derivatives is equally important as regressio...

In [19], we gave global convergence results for a second-derivative SQP method for minimizing the exact l1-merit function for a fixed value of the penalty parameter. To establish this result, we used the properties of the so-called Cauchy step, which was itself computed from the so-called predictor step. In addition, we allowed for the computation of a variety of (optional) SQP steps that were ...

Background: With the increasing concern for health and nutrition, dietary fat has attracted considerable attention. The composition of fatty acids in the diet is important because they are associated with major diseases including cancers, diabetes, and cardiovascular disease. The fatty acid synthase (FASN) and stearoyl-CoA desaturase (delta-9-desaturase) (SCD) genes affect fatty acid compositio...

Memory and computation efficient deep learning architectures are crucial to continued proliferation of machine learning capabilities to new platforms and systems. Binarization of operations in convolutional neural networks has shown promising results in reducing model size and computing efficiency. In this paper, we tackle the problem using a strategy different from the existing literature by p...

This paper describes the Local Serialization pattern which decouples object concurrency control policies from objectspecific algorithm semantics and concurrency generation policies. The pattern was designed in the context of a development process for distributed applications which considers concerns and abstractions. Concerns are the distribution issues that should be solved during the developm...

Dynamic time warping (DTW) has been widely used in various pattern recognition and time series data mining applications. However, as examples will illustrate, both the classic DTW and its later alternative, derivative DTW, may fail to align a pair of sequences on their common trends or patterns. Furthermore, the learning capability of any supervised learning algorithm based on classic/derivativ...

Pattern recognition is a very powerful tool in automated data analysis and it is widely used in many different applications (Chou & Juang, 2003; Jiang,1994; Blue et al., 1994; Milosavljević, 1994; Moreels & Smrekar, 2003). However, the application of such a tool can be a difficult task in some cases. For example, in a correlation-type scheme, the basic idea is to correlate the signal being anal...

The paper concerns a new method to obtain a direct proof of the openness at linear rate/metric regularity of composite set-valued maps on metric spaces by the uni…cation and re…nement of several methods developed somehow separately in several works of the authors. In fact, this work is a synthesis and a precise specialization to a general situation of some techniques explored in the last years ...