Reducing Reasons

Reasons are considerations that figure in sound reasoning. This is considered by many philosophers to be little more than a platitude. I argue that it actually has surprising and far-reaching metanormative implications. The view that reasons are linked to sound reasoning seems platitudinous only because we tend to assume that soundness is a normative property, in which case the view merely relates one normative phenomenon (reasons) to another (soundness). I argue that soundness is also a descriptive phenomenon, one we can pick out with purely descriptive terms, and that the connection between normative reasons and sound reasoning therefore provides the basis for a reductive account of reasons. Like all proposed reductions, this one must confront some version of G. E. Moore’s open question argument. I argue that a reductive view rooted in the idea that reasons figure in sound reasoning is well-equipped to meet the open question challenge head on

Reducing Penguin Pollution

The most common decay used for measuring 2beta_s, the phase of Bs-Bsbar mixing, is Bs -> J/psi phi. This decay is dominated by the colour-suppressed tree diagram, but there are other contributions due to gluonic and electroweak penguin diagrams. These are often referred to as "penguin pollution" (PP) because their inclusion in the amplitude leads to a theoretical error in the extraction of 2beta_s from the data. In the standard model (SM), it is estimated that the PP is negligible, but there is some uncertainty as to its exact size. Now, phi_s^{c\bar{c}s} (the measured value of 2beta_s) is small, in agreement with the SM, but still has significant experimental errors. When these are reduced, if one hopes to be able to see clear evidence of new physics (NP), it is crucial to have the theoretical error under control. In this paper, we show that, using a modification of the angular analysis currently used to measure phi_s^{c\bar{c}s} in Bs -> J/psi phi, one can reduce the theoretical error due to PP. Theoretical input is still required, but it is much more modest than entirely neglecting the PP. If phi_s^{c\bar{c}s} differs from the SM prediction, this points to NP in the mixing. There is also enough information to test for NP in the decay. This method can be applied to all Bs/Bsbar -> V1 V2 decays.Comment: 17 pages, latex, extensive discussion of theoretical error added, reference added. Further revision: even more detailed discussion of theoretical error added, as well as an explanation of why the NP strong phase is negligibl

Reducing Students' Foreign Language Anxiety in Speaking Class Through Cooperative Learning

One of the challenges in teaching English as a foreign language to students in Indonesia is the existence of Foreign Language Anxiety (FLA) that are faced by students at any level of education. FLA has hindered the students in mastering English, especially in Speaking Skill, it is shown by their performances in the class which are too nervous, shy, unwilling to participate and lack of confidence.Gardner and McIntyre,(1987) stated that FLA negatively impacts the quality of learning and is a critical factor in learners' success or failure in learning a foreign language. Based on the aforementioned statements, it means reducing students' language anxiety can enhance their overall learning experience and improve motivation and achievement.Thus, for many years, some researchers have attempted to find the most suitable techniques and methods to help students overcome this problem. Some of which is by providing them a conducive learning environment, the culture of caring and of course, a non-threatening atmosphere in the classroom. For that reason, this paper isintended to propose a technique to reduce the students' anxiety; that is cooperative learning. By using cooperative learning, it is expected that it can overcome this problem, as this technique offers a good language-learning environment in which the process of learning dealing with cooperativeness rather than competitiveness. This is in line with Krashen (1982). He, through his Affective Filter Hypothesis, contends that one of the factors of language acquisition to happen is in a low-filter language-learning environment

Reducing Audible Spectral Discontinuities

In this paper, a common problem in diphone synthesis is discussed, viz., the occurrence of audible discontinuities at diphone boundaries. Informal observations show that spectral mismatch is most likely the cause of this phenomenon.We first set out to find an objective spectral measure for discontinuity. To this end, several spectral distance measures are related to the results of a listening experiment. Then, we studied the feasibility of extending the diphone database with context-sensitive diphones to reduce the occurrence of audible discontinuities. The number of additional diphones is limited by clustering consonant contexts that have a similar effect on the surrounding vowels on the basis of the best performing distance measure. A listening experiment has shown that the addition of these context-sensitive diphones significantly reduces the amount of audible discontinuities

Reducing Reparameterization Gradient Variance

Optimization with noisy gradients has become ubiquitous in statistics and machine learning. Reparameterization gradients, or gradient estimates computed via the "reparameterization trick," represent a class of noisy gradients often used in Monte Carlo variational inference (MCVI). However, when these gradient estimators are too noisy, the optimization procedure can be slow or fail to converge. One way to reduce noise is to use more samples for the gradient estimate, but this can be computationally expensive. Instead, we view the noisy gradient as a random variable, and form an inexpensive approximation of the generating procedure for the gradient sample. This approximation has high correlation with the noisy gradient by construction, making it a useful control variate for variance reduction. We demonstrate our approach on non-conjugate multi-level hierarchical models and a Bayesian neural net where we observed gradient variance reductions of multiple orders of magnitude (20-2,000x)

Reducing Dueling Bandits to Cardinal Bandits

We present algorithms for reducing the Dueling Bandits problem to the conventional (stochastic) Multi-Armed Bandits problem. The Dueling Bandits problem is an online model of learning with ordinal feedback of the form "A is preferred to B" (as opposed to cardinal feedback like "A has value 2.5"), giving it wide applicability in learning from implicit user feedback and revealed and stated preferences. In contrast to existing algorithms for the Dueling Bandits problem, our reductions -- named \Doubler, \MultiSbm and \DoubleSbm -- provide a generic schema for translating the extensive body of known results about conventional Multi-Armed Bandit algorithms to the Dueling Bandits setting. For \Doubler and \MultiSbm we prove regret upper bounds in both finite and infinite settings, and conjecture about the performance of \DoubleSbm which empirically outperforms the other two as well as previous algorithms in our experiments. In addition, we provide the first almost optimal regret bound in terms of second order terms, such as the differences between the values of the arms

Reducing Power Consumption in Backbone Networks

Abstract—According to several studies, the power consumption of the Internet accounts for up to 10 % of the worldwide energy consumption, and several initiatives are being put into place to reduce the power consumption of the ICT sector in general. To this goal, we propose a novel approach to switch off network nodes and links while still guaranteeing full connectivity and maximum link utilization. After showing that the problem falls in the class of capacitated multi-commodity flow problems, and therefore it is NP-complete, we propose some heuristic algorithms to solve it. Simulation results in a realistic scenario show that it is possible to reduce the number of links and nodes currently used by up to 30 % and 50 % respectively during off-peak hours, while offering the same service quality