We study a variant of the maximum coverage problem which we label the maximum coverage problem with group budget constraints (MCG). We are given a collection of sets S = {S1, S2, . . . , Sm} where each set Si is a subset of a given ground set X. In the maximum coverage problem the goal is to pick k sets from S to maximize the cardinality of their union. In the MCG problem S is partitioned into ...

We study a model that incorporates a budget constraint in a decision making problem. Our goal is to maximize the expected wealth, where in each time period we can either stop the business getting our current wealth or to continue one additional time period and getting a random revenue. We show that when the wealth is scalar, the problem is NP-hard and we provide an FPTAS. However, when the weal...

Distributed Algorithmic Mechanism Design Rahul Sami 2003 Distributed algorithmic mechanism design (DAMD) is an approach to designing distributed systems that takes into account both the distributed-computational environment and the incentives of autonomous agents. In this dissertation, we study two problems, multicast cost sharing and interdomain routing. We also touch upon several issues impor...

Increasing accessibility and affordability of healthcare services has been considered as an important policy objective since the beginning of 1980s in Iran. However, current 60- 70% health care out-of-pocket payments create a barrier to an equal access to quality health services, especially in terms of new medicines which affects equity issues and "health" in Iran. Currently, health insurance o...

Given a connected node-weighted (di)graph, with a root node r, and a (possibly empty) set of nodes R, the Rooted Maximum NodeWeight Connected Subgraph Problem (RMWCS) is the problem of finding a connected subgraph rooted at r that connects all nodes in R with maximum total weight. In this paper we consider the RMWCS as well as its budget-constrained version, in which also non-negative costs of ...

We present a new perspective on the classical shortest path routing (SPR) problem in graphs. We show that the SPR problem can be recast to that of probabilistic inference in a mixture of simple Bayesian networks. Maximizing the likelihood in this mixture becomes equivalent to solving the SPR problem. We develop the well known Expectation-Maximization (EM) algorithm for the SPR problem that maxi...

To control ever-increasing costs, global budget payment has gained attention but has unclear impacts on health care systems. We propose the CAP framework that helps navigate 3 domains of difficult design choices in global budget payment: Constraints in resources (capitation vs facility-based budgeting; hard vs soft budget constraints), Agent-principal in resource allocation (individual vs group...

Solving multiobjective engineering problems is a very difficult task due to, in general, in these class of problems, the objectives conflict across a high-dimensional problem space. In these problems, there is no single optimal solution, the interaction of multiple objectives gives rise to a set of efficient solutions, known as the Pareto-optimal solutions. During the past decade, Genetic Algor...

In this paper we address the problem of budget allocation for redundantly crowdsourcing a set of classification tasks where a key challenge is to find a trade–off between the total cost and the accuracy of estimation. We propose CrowdBudget, an agent–based budget allocation algorithm, that efficiently divides a given budget among different tasks in order to achieve low estimation error. In part...

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