From Cost Sharing Mechanisms to Online Selection Problems

We consider a general class of online optimization problems, called online selection problems, where customers arrive sequentially, and one has to decide upon arrival whether to accept or reject each customer. If a customer is rejected, then a rejection cost is incurred. The accepted customers are served with minimum possible cost, either online or after all customers have arrived. The goal is to minimize the total production costs for the accepted customers plus the rejection costs for the rejected customers. These selection problems are related to online variants of offline prize collecting combinatorial optimization problems that have been widely studied in the computer science literature. In this paper, we provide a general framework to develop online algorithms for this class of selection problems. In essence, the algorithmic framework leverages any cost sharing mechanism with certain properties into a poly-logarithmic competitive online algorithm for the respective problem; the competitive ratios are shown to be near-optimal. We believe that the general and transparent connection we establish between cost sharing mechanisms and online algorithms could lead to additional online algorithms for problems beyond the ones studied in this paper.National Science Foundation (U.S.) (CAREER Award CMMI-0846554)United States. Air Force Office of Scientific Research (FA9550-11-1-0150)United States. Air Force Office of Scientific Research (FA9550-08-1-0369)Solomon Buchsbaum AT&T Research Fun

Designing cost-sharing methods for Bayesian games

We study the design of cost-sharing protocols for two fundamental resource allocation problems, the Set Cover and the Steiner Tree Problem, under environments of incomplete information (Bayesian model). Our objective is to design protocols where the worst-case Bayesian Nash equilibria, have low cost, i.e. the Bayesian Price of Anarchy (PoA) is minimized. Although budget balance is a very natural requirement, it puts considerable restrictions on the design space, resulting in high PoA. We propose an alternative, relaxed requirement called budget balance in the equilibrium (BBiE).We show an interesting connection between algorithms for Oblivious Stochastic optimization problems and cost-sharing design with low PoA. We exploit this connection for both problems and we enforce approximate solutions of the stochastic problem, as Bayesian Nash equilibria, with the same guarantees on the PoA. More interestingly, we show how to obtain the same bounds on the PoA, by using anonymous posted prices which are desirable because they are easy to implement and, as we show, induce dominant strategies for the players

Community-based risk management arrangements : an overview and implications for social fund programs

Risk and its consequences pose a formidable threat to poverty reduction efforts. This study reviews a plethora of community-based risk management arrangements across the developing world. These types of arrangements are garnering greater interest in light of the growing recognition of the relative prominence of household or individual-specific idiosyncratic risk as well as the increasing shift towards community-based development funding. The study discusses potential advantages (such as targeting, cost, and informational) and disadvantages (such as exclusion and inability to manage correlated risk) of these arrangements, and their implications for the design of innovative social fund programs.Rural Poverty Reduction,Labor Policies,Insurance&Risk Mitigation,Currencies and Exchange Rates,Debt Markets

Privacy and Accountability in Black-Box Medicine

Black-box medicine—the use of big data and sophisticated machine learning techniques for health-care applications—could be the future of personalized medicine. Black-box medicine promises to make it easier to diagnose rare diseases and conditions, identify the most promising treatments, and allocate scarce resources among different patients. But to succeed, it must overcome two separate, but related, problems: patient privacy and algorithmic accountability. Privacy is a problem because researchers need access to huge amounts of patient health information to generate useful medical predictions. And accountability is a problem because black-box algorithms must be verified by outsiders to ensure they are accurate and unbiased, but this means giving outsiders access to this health information. This article examines the tension between the twin goals of privacy and accountability and develops a framework for balancing that tension. It proposes three pillars for an effective system of privacy-preserving accountability: substantive limitations on the collection, use, and disclosure of patient information; independent gatekeepers regulating information sharing between those developing and verifying black-box algorithms; and information-security requirements to prevent unintentional disclosures of patient information. The article examines and draws on a similar debate in the field of clinical trials, where disclosing information from past trials can lead to new treatments but also threatens patient privacy

Designing postgraduate pedagogies: connecting internal and external leaders

Learning is the new resource driving the knowledge economy. Now everyone is expected to make themselves available to learn : un-learn : re-learn. Much has been written about new modes of learning, as well the new technologies that promise to deliver information 24/7. Paradoxically, however, in the field of educational sociology there has been little systematic theorisation of the pedagogies designed to facilitate learning in the knowledge economy. Nor have there been systematic efforts to connect macro economic, technological and social changes to state official policies and institutional pedagogic practices. The Bernsteinian theoretical corpus models the power and control relations generating pedagogic discourses, practices and identities from the macro level of policy formation to the micro level of pedagogic interactions. It is therefore useful in examining the new pedagogies designed to generate the learning resources of the knowledge economy. In this paper, we draw on and extend Bernstein's theory of pedagogic discourse and identities to analyse the design and implementation of a postgraduate unit in educational research. This unit aimed to be: rigorous in disciplinary knowledge, technologically innovative, cost efficient; and responsive to diverse student needs and market contingencies