Browsing by Subject "Ambiguity"

Now showing 1 - 10 of 10

Open Access
The dark night : representing urban anxieties in contemporary superhero films
(2011) Okay, Damla
The comic book superhero is one of the most important cultural products of the United States. From the second quarter of the 20th century on, the iconic and allusional images of the larger-than-life superheroes in colorful costumes took over not only the pages of comic books, but also occasionally, and recently quite frequently, the big screen. Due to the changing tone of the superhero narratives over time and with the help of special effects that enable directors to imagine broader cityscapes, the concept of city, which has always been a fundamental element in superhero comics, gained even more importance on film. This study aims to overview the aesthetics of urban spaces in recent superhero films, as well as the relationship they build with the elements of the city. Additionally this study will investigate and bring together thoughts on the after-effects of the September 11, 2001 attacks on New York City as one of the possible reasons of the ‘superhero boom’ of the last decade, and ultimately reach the conclusion that the position of the superhero films towards both urban crime and international terror can be classified as ambiguity.
Open Access
Delegated portfolio management under ambiguity aversion
(2014) Fabretti, A.; Herzel, S.; Pınar, M. Ç.
We examine the problem of setting optimal incentives for a portfolio manager hired by an investor who wants to induce ambiguity-robust portfolio choices with respect to estimation errors in expected returns. Adopting a worst-case max-min approach we obtain the optimal compensation in various cases where the investor and the manager, adopt or relinquish an ambiguity averse attitude. We also provide examples of applications to real market data.
Open Access
Diversity and novelty in information retrieval
(ACM, 2013-07-08) Santos, R. L. T.; Castells, P.; Altıngövde, I. S.; Can, Fazlı
This tutorial aims to provide a unifying account of current research on diversity and novelty in different IR domains, namely, in the context of search engines, recommender sys- tems, and data streams.
Open Access
Diversity and novelty in web search, recommender systems and data streams
(Association for Computing Machinery, 2014-02) Santos, R. L. T.; Castells, P.; Altingovde, I. S.; Can, Fazlı
This tutorial aims to provide a unifying account of current research on diversity and novelty in the domains of web search, recommender systems, and data stream processing.
Open Access
Essays on bilateral trade with discrete types
(2019-10) Mohammadinezhad, Kamyar Kargar
Bilateral trade is probably the most common market interaction problem and can be considered as the simplest form of two sided markets where a seller and a buyer bargain over an indivisible object subject to incomplete information on the reservation values of participants. We treat this problem as a combinatorial optimization problem and re-establish some results of economic theory that are well-known under continuous valuations assumptions for the case of discrete valuations using linear programming techniques. First, we propose mathematical formulation for the problem under dominant strategy incentive compatibility (DIC) and ex-post individual rationality (EIR) properties. Then we derive necessary and sufficient conditions under which ex-post efficiency can be obtained together with DIC and EIR. We also define a new property called Allocation Maximality and prove that the Posted Price mechanism is the only mechanism that satisfies DIC, EIR and allocation maximality. In the final part we consider ambiguity in the problem framework originating from different sets of priors for agents types and derive robust counterparts. Next, we study the bilateral trade problem with an intermediary who wants to maximize her expected gains. Using network programming we transform the initial linear program into one from which the structure of mechanism is transparent. We then relax the risk-neutrality assumption of the intermediary and consider the problem from the perspective of risk-averse intermediary. The effects of risk-averse approach are presented using computational experiments. Finally, we broaden the scope of the problem and discuss the case in which the seller is also a producer at the same time and consider benefit and cost functions for the respective parties. Starting by a non-convex optimization problem, we obtain an equivalent convex optimization problem from which the problem is solved easily. We also reconsider the same problem under dominant strategy incentive compatibility and ex-post individual rationality constraints to preserve the practicality of all obtained solutions.
Open Access
Optimal allocation with costly inspection and discrete types under ambiguity
(Taylor & Francis, 2017) Bayrak, H. I.; Güler, K.; Pınar, M. Ç.
We consider the following problem: a principal has a good to allocate among a collection of agents who attach a private value to receiving the good. The principal, instead of using monetary transfers (i.e. charging the agents) to allocate the good, can check the truthfulness of the agents' value declaration at a cost. Under the assumption that the agents' valuations are drawn from a discrete set of values at random, we characterize the class of optimal Bayesian mechanisms which are symmetric, direct and maximizing the expected value of assigning the good to the principal minus the cost of verification using such standard finite-dimensional optimization tools as linear programming and submodular functions, thus extending the work of [R.V. Vohra, Optimization and mechanism design, Math. Program. 134 (2012), pp. 283–303]. Our results are discrete-type analogs of those of [E. Ben-Porath, E. Dekel, and B.L. LipmanBen-Porath, Optimal allocation with costly verification, Amer. Econ. Rev. 104 (2014), pp. 3779–3813]. When the distribution of valuations is not known but can be one of a set of distributions (the case referred to as ambiguity), we compute a robust allocation mechanism by maximizing the worst-case expected value of the principal in two cases amenable to solution with two suitable assumptions on the set of distributions.
Open Access
Robust auction design under multiple priors by linear and integer programming
(Springer New York LLC, 2018) Koçyiğit, Ç.; Bayrak, Halil İbrahim; Pınar, Mustafa Çelebi
It is commonly assumed in the optimal auction design literature that valuations of buyers are independently drawn from a unique distribution. In this paper we study auctions under ambiguity, that is, in an environment where valuation distribution is uncertain itself, and present a linear programming approach to robust auction design problem with a discrete type space. We develop an algorithm that gives the optimal solution to the problem under certain assumptions when the seller is ambiguity averse with a finite prior set P and the buyers are ambiguity neutral with a prior f∈ P. We also consider the case where all parties, the buyers and the seller, are ambiguity averse, and formulate this problem as a mixed integer programming problem. Then, we propose a hybrid algorithm that enables to compute an optimal solution for the problem in reduced time.
Open Access
Robust bilateral trade with discrete types
(Springer, 2018) Kargar, Kamyar; Bayrak, Halil İbrahim; Pınar, Mustafa Çelebi
Bilateral trade problem is the most common market interaction in which a seller and a buyer bargain over an indivisible object, and the valuation of each agent about the object is private information. We investigate the cases where mechanisms satisfying Dominant Strategy Incentive Compatibility (DIC) and Ex-post Individual Rationality (EIR) properties can exhibit robust performance in the face of imprecision in prior structure. We start with the general mathematical formulation for the bilateral trade problem with DIC, EIR properties. We derive necessary and sufficient conditions for DIC, EIR mechanisms to be Ex-post efficient at the same time. Then, we define a new property—Allocation Maximality—and prove that the Posted Price mechanisms are the only mechanisms that satisfy DIC, EIR and Allocation Maximal properties. We also show that Posted Price mechanism is not the only mechanism that satisfies DIC and EIR properties. The last part of the paper introduces different sets of priors for agents’ types and consequently allows ambiguity in the problem framework. We derive robust counterparts and solve them numerically for the proposed objective function under box and ϕ-divergence ambiguity specifications. Results suggest that restricting the feasible set to Posted Price mechanisms can decrease the objective value to different extents depending on the uncertainty set.
Open Access
Robust screening under ambiguity
(Springer, 2017) Pınar, M. Ç.; Kızılkale, C.
We consider the problem of screening where a seller puts up for sale an indivisible good, and a buyer with a valuation unknown to the seller wishes to acquire the good. We assume that the buyer valuations are represented as discrete types drawn from some distribution, which is also unknown to the seller. The seller is averse to possible mis-specification of types distribution, and considers the unknown type density as member of an ambiguity set and seeks an optimal pricing mechanism in a worst case sense. We specify four choices for the ambiguity set and derive the optimal mechanism in each case.
Open Access
Worst-case large deviations upper bounds for i.i.d. sequences under ambiguity
(TÜBİTAK, 2018) Pınar, Mustafa Çelebi
An introductory study of large deviations upper bounds from a worst-case perspective under parameter uncertainty (referred to as ambiguity) of the underlying distributions is given. Borrowing ideas from robust optimization, suitable sets of ambiguity are defined for imprecise parameters of underlying distributions. Both univariate and multivariate i.i.d. sequences of random variables are considered. The resulting optimization problems are challenging min–max (or max–min) problems that admit some simplifications and some explicit results, mostly in the case of the normal probability law.