A novel modification to backpropagation sample selection strategy

Random sample selection method in backpropagation results in convergence on the error (root of mean squared error, RMSE) surface. These problems, which are caused by the extreme (worst-case) errors, can be solved by a different sample selection strategy. A sample selection strategy has been proposed, which provides lower maximal errors and a higher confidence level on the expense of slightly increased RMSE. Applications are presented in the field of spectroscopic ellipsometry (SE), a sensitive, non-destructive but indirect analytical technique. Demonstrative example shows feature common to simulated annealing in the sense of escaping local minima

A Near-Optimal Sampling Strategy for Sparse Recovery of Polynomial Chaos Expansions

Compressive sampling has become a widely used approach to construct polynomial chaos surrogates when the number of available simulation samples is limited. Originally, these expensive simulation samples would be obtained at random locations in the parameter space. It was later shown that the choice of sample locations could significantly impact the accuracy of resulting surrogates. This motivated new sampling strategies or design-of-experiment approaches, such as coherence-optimal sampling, which aim at improving the coherence property. In this paper, we propose a sampling strategy that can identify near-optimal sample locations that lead to improvement in local-coherence property and also enhancement of cross-correlation properties of measurement matrices. We provide theoretical motivations for the proposed sampling strategy along with several numerical examples that show that our near-optimal sampling strategy produces substantially more accurate results, compared to other sampling strategies

Mars Rover Sample Return: A sample collection and analysis strategy for exobiology

For reasons defined elsewhere it is reasonable to search for biological signatures, both chemical and morphological, of extinct life on Mars. Life on Earth requries the presence of liquid water, therefore, it is important to explore sites on Mars where standing bodies of water may have once existed. Outcrops of layered deposits within the Valles Marineris appear to be ancient lake beds. Because the outcrops are well exposed, relatively shallow core samples would be very informative. The most important biological signature to detect would be organics, microfossils, or larger stromato-like structures, although the presence of cherts, carbonates, clays, and shales would be significant. In spite of the limitations of current robotics and pattern recognition, and the limitations of rover power, computation, Earth communication bandwidth, and time delays, a partial scenario was developed to implement such a scientific investigation. The rover instrumentation and the procedures and decisions and IR spectrometer are described in detail. Preliminary results from a collaborative effort are described, which indicate the rover will be able to autonomously detect stratification, and hence will ease the interpretation burden and lead to greater scientific productivity during the rover's lifetime

Business strategy and earnings quality

ABSTRACT: Using the Miles and Snow (1978) strategy typology, this study investigates whether business strategy is associated with the quality of reported earnings. In a sample of U.S. listed firms, we predict and find that defender strategy firms are associated with higher levels of earnings management and prospector-strategy firms are associated with higher levels of accounting conservatism. However, this relation between business strategy and earnings quality is altered during high and low economic growth periods. In high-growth periods, while prospector firms exhibit lesser accounting conservatism, defender firms exhibit lesser earning management. In low-growth periods, the prospector firms become more conservative in reporting while the defender firms engage in more aggressive earnings management. Our findings provide direct evidence of the link between business strategy and earnings quality

Do Business Cycles Exhibit Beneficial Information for Portfolio Management? An Empirical Application of Statistical Arbitrage

An advantageous statistical arbitrage strategy should exhibit a zero-cost trading strategy for which the expected payoff should be positive. In practical applications, however, the abnormal returns often are out-of-sample not significant. The statistical model being suggested here results in an estimated portfolio exhibiting in-sample a cointegration relationship with the artificial stock index. The portfolio returns exhibited out-of-sample a mean of 10.44% p.a., whereas the volatility was one third lower in comparison to the benchmark's volatility. Accounting for trading costs of 2.94% p.a. on average, the annual returns of the estimated portfolio are out-of-sample still 6.83% higher than the market returns. As a result, the model involves implicitly advantageous market timing.