At Airbnb, R has been amongst the most popular tools for doing data science in many different contexts, including generating product insights, interpreting experiments, and building predictive models. Airbnb supports R usage by creating internal R tools and by creating a community of R users. At the end of the post, the authors provide some specific advice for practitioners who wish to incorpor...

This paper considers the micro-econometric analysis of patients’ hospital choice for elective medical procedures when their choice set is pre-selected by a general practitioner (GP). It proposes a two-stage choice model that encompasses both, patient and GP level optimization, and it discusses identification. The empirical analysis demonstrates biases and inconsistencies that arise when strateg...

The connection between kinematics and mechanisms to algebraic constraints is well known. This work presents a general kinematics simulator that allows end users to define planar and/or spatial arrangements, even along freeform curves and surfaces. The mechanical arrangement is then converted into a set of algebraic constraints and the motion of the arrangements is computed with the aid of a mul...

Molecular modelling and simulation of the surface tension of fluids with force fields is discussed. 29 real fluids are studied, including nitrogen, oxygen, carbon dioxide, carbon monoxide, fluorine, chlorine, bromine, iodine, ethane, ethylene, acetylene, propyne, propylene, propadiene, carbon disulfide, sulfur hexafluoride, and many refrigerants. The fluids are represented by two-centre Lennard...

We develop a general framework for social choice problems in which a limited number of alternatives can be recommended to an agent population. In our budgeted social choice model, this limit is determined by a budget, capturing problems that arise naturally in a variety of contexts, and spanning the continuum from pure consensus decision making (i.e., standard social choice) to fully personaliz...

Discusses the implications of the economic valuation of natural resources used for tourism and relates this valuation to the concept of total economic valuation. It demonstrates how applications of the concept of total economic valuation can be supportive of the conservation of natural resources used for tourism. Techniques for valuing tourism’s natural resources are then outlined and criticall...

In the last two decades there have been substantial developments in the mathematical theory of inverse optimization problems, and their applications have expanded greatly. In parallel, time series analysis and forecasting have become increasingly important in various fields of research such as data mining, economics, business, engineering, medicine, politics, and many others. Despite the large ...

Modeling and optimization of metabolic networks has been one of the hottest topics in computational systems biology within recent years. However, the complexity and uncertainty of these networks in addition to the lack of necessary data has resulted in more efforts to design and usage of more capable models which fit to realistic conditions. In this paper, instead of optimizing networks in equi...

Typical recommender systems adopt a static view of the recommendation process and treat it as a prediction problem. We argue that it is more appropriate to view the problem of generating recommendations as a sequential optimization problem and, consequently, that Markov decision processes (MDPs) provide a more appropriate model for recommender systems. MDPs introduce two benefits: they take int...