1,720,959 research outputs found
Simple and Optimal Greedy Online Contention Resolution Schemes
Get PDFReal-world problems such as ad allocation and matching have been extensively
studied under the lens of combinatorial optimization. In several applications,
uncertainty in the input appears naturally and this has led to the study of
online stochastic optimization models for such problems. For the offline case,
these constrained combinatorial optimization problems have been extensively
studied, and Contention Resolution Schemes (CRSs), introduced by Chekuri,
Vondr\'{a}k, and Zenklusen, have emerged in recent years as a general framework
to obtaining a solution. The idea behind a CRS is to first obtain a fractional
solution to a (continuous) relaxation of the objective and then round the
fractional solution to an integral one. When the order of rounding is
controlled by an adversary, Online Contention Resolution Schemes (OCRSs) can be
used instead, and have been successfully applied in settings such as prophet
inequalities and stochastic probing.
In this work, we focus on greedy OCRSs, which provide guarantees against the
strongest possible adversary, an almighty adversary. Intuitively, a greedy OCRS
has to make all its decisions before the online process starts. We present
simple - selectable greedy OCRSs for the single-item setting, partition
matroids and transversal matroids, which improve upon the previous
state-of-the-art greedy OCRSs for these constraints. We also show that our
greedy OCRSs are optimal, even for the simple single-item case.Comment: 16 pages, to appear in NeurIPS 202
Going Beyond Counting First Authors in Author Co-citation Analysis
Get PDFThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Get PDF“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Get PDFWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Nuevas direcciones en parada óptima: metodologías para problemas de transacciones con desigualdades de profeta
Get PDFEste trabajo se centra en la implementaci´on de algoritmos online para resolver problemas
de trading en diversos contextos. Los problemas de Optimal Stopping y las Prophet Inequali-
ties han captado la atenci´on en diversos campos debido a su capacidad para modelar la toma
de decisiones en situaciones inciertas, como las estrategias de compra y venta en mercados
financieros [10, 23]. Un enfoque reciente de Correa et al. [9] aborda la single item prophet
inequality, comparando la eficacia de un algoritmo de compra y venta repetido, con el marco
de referencia de un profeta, bajo la premisa de variables aleatorias independientes.
En este trabajo, se presenta un avance te´orico al demostrar que la ganancia esperada
del algoritmo para precios independientes con igual mediana es al menos 1
2 de la ganancia del
profeta, mejorando as´ı los resultados previos que ped´ıan como condici´on, sobre los precios,
independencia id´enticamente distribuida.
Adem´as, se utilizaron m´etodos de Montecarlo para estimar las ganancias probables de
estos algoritmos. En concreto, para diferentes valores 0 < λ < 1 se estim´o la proporci´on
de casos en los cuales la ganancia del algoritmo es mayor o igual a λ veces la ganancia
del profeta. Este enfoque permiti´o evaluar el desempe˜no m´as probable del algoritmo
donde se encontr´o que en la gran mayor´ıa de los casos el algoritmo obtiene una ganancia
esperada superior a 0,7 veces la ganancia esperada del profeta.
En la parte final de nuestro trabajo, se desarrollaron metodolog´ıas para implementar el
algoritmo en escenarios reales, espec´ıficamente cumpliendo las condiciones requeridas en
las garant´ıas te´oricas. Se confirmaron los resultados obtenidos en las simulaciones cuando era
posible asumir, de forma aproximada, condiciones de independencia; por otro lado, se con-
trastaron en los casos donde estas condiciones no se cumpl´ıan. En estos ´ultimos, se constat´o
que, ante un comportamiento fundamentalmente estoc´astico de los precios y una informaci´on
limitada, los algoritmos online no son suficientes para generar ganancias.
Al conectar el marco te´orico actual con aplicaciones industriales relevantes, este trabajo
contribuye al desarrollo de modelos y algoritmos m´as adaptativos y robustos frente a la
incertidumbre del mundo real.Versión original del auto
Prophet Inequalities for Cost Minimization
Get PDFProphet inequalities for rewards maximization are fundamental to optimal
stopping theory with extensive applications to mechanism design and online
optimization. We study the \emph{cost minimization} counterpart of the
classical prophet inequality: a decision maker is facing a sequence of costs
drawn from known distributions in an online manner and
\emph{must} ``stop'' at some point and take the last cost seen. The goal is to
compete with a ``prophet'' who can see the realizations of all 's upfront
and always select the minimum, obtaining a cost of .
If the 's are not identically distributed, no strategy can achieve a
bounded approximation, even for random arrival order and . This leads us
to consider the case where the 's are independent and identically
distributed (I.I.D.). For the I.I.D. case, we show that if the distribution
satisfies a mild condition, the optimal stopping strategy achieves a
(distribution-dependent) constant-factor approximation to the prophet's cost.
Moreover, for MHR distributions, this constant is at most . All our results
are tight. We also demonstrate an example distribution that does not satisfy
the condition and for which the competitive ratio of any algorithm is infinite.
Turning our attention to single-threshold strategies, we design a threshold
that achieves a -factor approximation, where the
exponent in the logarithmic factor is a distribution-dependent constant, and we
show a matching lower bound. Finally, we note that our results can be used to
design approximately optimal posted price-style mechanisms for procurement
auctions which may be of independent interest.
Our techniques utilize the \emph{hazard rate} of the distribution in a novel
way, allowing for a fine-grained analysis which could find further applications
in prophet inequalities.Comment: 40 page
Dispelling the Myths Behind First-author Citation Counts
Get PDFWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
Minimization I.I.D. Prophet Inequality via Extreme Value Theory: A Unified Approach
No full textThe I.I.D. Prophet Inequality is a fundamental problem where, given independent random variables drawn from a known distribution , one has to decide at every step whether to stop and accept or discard it forever and continue. The goal is to maximize or minimize the selected value and compete against the all-knowing prophet. For maximization, a tight constant-competitive guarantee of is well-known (Correa et al, 2019), whereas minimization is qualitatively different: the optimal constant is distribution-dependent and can be arbitrarily large (Livanos and Mehta, 2024).
In this paper, we provide a novel framework via the lens of Extreme Value Theory to analyze optimal threshold algorithms. We show that the competitive ratio for the minimization setting has a closed form described by a function , which depends only on the extreme value index ; in particular, it corresponds to for . Despite the contrast of maximization and minimization, our framework turns out to be universal and we recover the results of (Kennedy and Kertz, 1991) for maximization as well. Surprisingly, the optimal competitive ratio for maximization is given by the same function , but for . Along the way, we obtain several results on the algorithm and the prophet\u27s objectives from the perspective of extreme value theory, which might be of independent interest.
We next study single-threshold algorithms for minimization. Using extreme value theory, we generalize the results of (Livanos and Mehta, 2024) which hold only for special classes of distributions, and obtain poly-logarithmic in guarantees. Finally, we consider the -multi-unit prophet inequality for minimization and show that there exist constant-competitive single-threshold algorithms when .44 pages, 1 figur
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