A Methodology for Discovering how to Adaptively Personalize to Users using Experimental Comparisons

We explain and provide examples of a formalism that supports the methodology of discovering how to adapt and personalize technology by combining randomized experiments with variables associated with user models. We characterize a formal relationship between the use of technology to conduct A/B experiments and use of technology for adaptive personalization. The MOOClet Formalism [11] captures the equivalence between experimentation and personalization in its conceptualization of modular components of a technology. This motivates a unified software design pattern that enables technology components that can be compared in an experiment to also be adapted based on contextual data, or personalized based on user characteristics. With the aid of a concrete use case, we illustrate the potential of the MOOClet formalism for a methodology that uses randomized experiments of alternative micro-designs to discover how to adapt technology based on user characteristics, and then dynamically implements these personalized improvements in real time

Variable grouping in multivariate time series via correlation

The decomposition of high-dimensional multivariate time series (MTS) into a number of low-dimensional MTS is a useful but challenging task because the number of possible dependencies between variables is likely to be huge. This paper is about a systematic study of the “variable groupings” problem in MTS. In particular, we investigate different methods of utilizing the information regarding correlations among MTS variables. This type of method does not appear to have been studied before. In all, 15 methods are suggested and applied to six datasets where there are identifiable mixed groupings of MTS variables. This paper describes the general methodology, reports extensive experimental results, and concludes with useful insights on the strength and weakness of this type of grouping metho

Beta Reduction is Invariant, Indeed (Long Version)

Slot and van Emde Boas' weak invariance thesis states that reasonable machines can simulate each other within a polynomially overhead in time. Is $\lambda$-calculus a reasonable machine? Is there a way to measure the computational complexity of a $\lambda$-term? This paper presents the first complete positive answer to this long-standing problem. Moreover, our answer is completely machine-independent and based over a standard notion in the theory of $\lambda$-calculus: the length of a leftmost-outermost derivation to normal form is an invariant cost model. Such a theorem cannot be proved by directly relating $\lambda$-calculus with Turing machines or random access machines, because of the size explosion problem: there are terms that in a linear number of steps produce an exponentially long output. The first step towards the solution is to shift to a notion of evaluation for which the length and the size of the output are linearly related. This is done by adopting the linear substitution calculus (LSC), a calculus of explicit substitutions modelled after linear logic and proof-nets and admitting a decomposition of leftmost-outermost derivations with the desired property. Thus, the LSC is invariant with respect to, say, random access machines. The second step is to show that LSC is invariant with respect to the $\lambda$-calculus. The size explosion problem seems to imply that this is not possible: having the same notions of normal form, evaluation in the LSC is exponentially longer than in the $\lambda$-calculus. We solve such an impasse by introducing a new form of shared normal form and shared reduction, deemed useful. Useful evaluation avoids those steps that only unshare the output without contributing to $\beta$-redexes, i.e., the steps that cause the blow-up in size.Comment: 29 page

Distilling Abstract Machines (Long Version)

It is well-known that many environment-based abstract machines can be seen as strategies in lambda calculi with explicit substitutions (ES). Recently, graphical syntaxes and linear logic led to the linear substitution calculus (LSC), a new approach to ES that is halfway between big-step calculi and traditional calculi with ES. This paper studies the relationship between the LSC and environment-based abstract machines. While traditional calculi with ES simulate abstract machines, the LSC rather distills them: some transitions are simulated while others vanish, as they map to a notion of structural congruence. The distillation process unveils that abstract machines in fact implement weak linear head reduction, a notion of evaluation having a central role in the theory of linear logic. We show that such a pattern applies uniformly in call-by-name, call-by-value, and call-by-need, catching many machines in the literature. We start by distilling the KAM, the CEK, and the ZINC, and then provide simplified versions of the SECD, the lazy KAM, and Sestoft's machine. Along the way we also introduce some new machines with global environments. Moreover, we show that distillation preserves the time complexity of the executions, i.e. the LSC is a complexity-preserving abstraction of abstract machines.Comment: 63 page

R&D Subsidies and Climate Policy: Is There a "Free Lunch"?

Because of the long-term nature of the climate problem, technological advances are often seen as an important component of any solution. However, when considering the potential for technology to help solve the climate problem, two market failures exist which lead to underinvestment in climate-friendly R&D: environmental externalities and the public goods nature of new knowledge. As a result, government subsidies to climate-friendly R&D projects are often proposed as part of a policy solution. Using the ENTICE model, I analyze the effectiveness of such subsidies, both with and without other climate policies, such as a carbon tax. While R&D subsidies do lead to significant increases in climate-friendly R&D, this R&D has little impact on the climate itself. Subsidies address the problem of knowledge as a public good, but they do not address the environmental externality, and thus offer no additional incentive to adopt new technologies. Moreover, high opportunity costs to R&D limit the potential role that subsidies can play. While R&D subsidies can improve efficiency, policies that directly affect the environmental externality have a much larger impact on both atmospheric temperature and economic welfare.

Existence and Magnitude of Health-related Externalities: Evidence from a Choice Experiment

Health-related external benefits are of potentially large importance for public policy. This paper investigates health-related external benefits using a stated-preference discrete-choice experiment framed in a health care context and including choice scenarios dened by six attributes related to the a recipient and the recipient's condition: communicability, severity, medical necessity, relationship to respondent, location, and amount of contribution requested. Subjects also completed a set of own-treatment scenarios and a values-orientation instrument. We find evidence of substantial health-related external benefits that vary as expected with the scenario attributes and subjects' value orientations. The results are consistent with a number of hypotheses offered by the general theoretical analysis of health-related externalities and the analysis of externalities specific to health care.externalities; altruism; health care financing; program evaluation