Approximating TSP on Metrics with Bounded Global Growth

published_or_final_versio

Fast convergence for consensus in dynamic networks

LNCS v. 3756 entitled: Automata, languages and programming : 38th international colloquium, ICALP 2011 ... proceedingsWe study the convergence time required to achieve consensus in dynamic networks. In each time step, a node's value is updated to some weighted average of its neighbors' and its old values. We study the case when the underlying network is dynamic, and investigate different averaging models. Both our analysis and experiments show that dynamic networks exhibit fast convergence behavior, even under very mild connectivity assumptions. © 2011 Springer-Verlag.postprin

Sparse Fault-Tolerant Spanners for Doubling Metrics with Bounded Hop-Diameter or Degree

postprin

Revealing optimal thresholds for generalized secretary problem via continuous LP: impacts on online K-item auction and bipartite K-matching with random arrival order

We consider the general (J, K)-secretary problem, where n totally ordered items arrive in a random order. An algorithm observes the relative merits of arriving items and is allowed to make J selections. The objective is to maximize the expected number of items selected among the K best items. Buchbinder, Jain and Singh proposed a finite linear program (LP) that completely characterizes the problem, but it is difficult to analyze the asymptotic behavior of its optimal solution as n tends to infinity. Instead, we prove a formal connection between the finite model and an infinite model, where there are a countably infinite number of items, each of which has arrival time drawn independently and uniformly from [0, 1]. The finite LP extends to a continuous LP, whose complementary slackness conditions reveal an optimal algorithm which involves JK thresholds that play a similar role as the 1/e-threshold in the optimal classical secretary algorithm. In particular, for the case K=1, the J optimal thresholds have a nice 'rational description'. Our continuous LP analysis gives a very clear perspective on the problem, and the new insights inspire us; to solve two related problems. 1. We settle the open problem whether algorithms based only on relative merits can achieve optimal ratio for matroid secretary problems. We show that, for online 2-item auction with random arriving bids (the if-uniform matroid problem with K=2), an algorithm making decisions based only on relative merits cannot achieve the optimal ratio. This is in contrast with the folklore that, for online 1-item auction, no algorithm can have performance ratio strictly larger than 1/e, which is achievable by an algorithm that considers only relative merits. 2. We give a general transformation technique that takes any monotone algorithm (such as thresholdalgorithms) for the (K, K)-secretary problem, and constructs an algorithm for online bipartite K-matching with random arrival order that has at least the same performance guarantee.postprin

Oblivious RAM with O((log N)3) worst-case cost

LNCS v. 7073 entitled: Advances in Cryptology – ASIACRYPT 2011Oblivious RAM is a useful primitive that allows a client to hide its data access patterns from an untrusted server in storage outsourcing applications. Until recently, most prior works on Oblivious RAM aim to optimize its amortized cost, while suffering from linear or even higher worst-case cost. Such poor worst-case behavior renders these schemes impractical in realistic settings, since a data access request can occasionally be blocked waiting for an unreasonably large number of operations to complete. This paper proposes novel Oblivious RAM constructions that achieves poly-logarithmic worst-case cost, while consuming constant client-side storage. To achieve the desired worst-case asymptotic performance, we propose a novel technique in which we organize the O-RAM storage into a binary tree over data buckets, while moving data blocks obliviously along tree edges.postprin

New Doubling Spanners: Better and Simpler

published_or_final_versio

Privacy-Preserving Aggregation of Time-Series Data

The conference paper can be viewed at: http://www.isoc.org/isoc/conferences/ndss/11/proceedings.shtmlSession 9: PrivacyWe consider how an untrusted data aggregator can learn desired statistics over multiple participants’ data, without compromising each individual’s privacy. We propose a construction that allows a group of participants to periodically upload encrypted values to a data aggregator, such that the aggregator is able to compute the sum of all participants’ values in every time period, but is unable to learn anything else. We achieve strong privacy guarantees using two main techniques. First, we show how to utilize applied cryptographic techniques to allow the aggregator to decrypt the sum from multiple ciphertexts encrypted under different user keys. Second, we describe a distributed data randomization procedure that guarantees the differential privacy of the outcome statistic, even when a subset of participants might be compromised.published_or_final_versio

Remuneração executiva e desempenho : evidências empíricas no mercado de capitais brasileiro

O objetivo desta dissertação é analisar a relação existente entre remuneração executiva e desempenho em companhias brasileiras de capital aberto listadas na BM&FBOVESPA. A linha teórica parte do pressuposto que o contrato de incentivos corrobora com o alinhamento de interesses entre acionistas e executivos e atua como um mecanismo de governança corporativa a fim de direcionar os esforços dos executivos para maximização de valor da companhia. A amostra foi composta pelas 100 companhias mais líquidas listadas em quantidade de negociações de ações na BM&FBOVESPA durante o período 2010-2012, totalizando 296 observações. Os dados foram extraídos dos Formulários de Referência disponibilizados pela CVM e a partir dos softwares Economática® e Thomson Reuters ®. Foram estabelecidas oito hipóteses de pesquisa e estimados modelos de regressão linear múltipla com a técnica de dados em painel desbalanceado, empregando como variável dependente a remuneração total e a remuneração média individual e como regressores variáveis concernentes ao desempenho operacional, valor de mercado, tamanho, estrutura de propriedade, governança corporativa, além de variáveis de controle. Para verificar os fatores que explicam a utilização de stock options, programa de bônus e maior percentual de remuneração variável foram estimados modelos de regressão logit. Os resultados demonstram que, na amostra selecionada, existe relação positiva entre remuneração executiva e valor de mercado. Verificou-se também que os setores de mineração, química, petróleo e gás exercem influência positiva na remuneração executiva. Não obstante, exerce relação inversa com a remuneração total à concentração acionária, o controle acionário público e o fato da companhia pertencer ao nível 2 ou novo mercado conforme classificação da BMF&BOVESPA. O maior valor de mercado influencia na utilização de stock options, assim como no emprego de bônus, sendo que este também é impactado pelo maior desempenho contábil. Foram empregados também testes de robustez com estimações por efeitos aleatórios, regressões com erros-padrão robustos clusterizados, modelos dinâmicos e os resultados foram similares. Conclui-se que a remuneração executiva está relacionada com o valor corporativo gerando riqueza aos acionistas, mas que a ausência de relação com o desempenho operacional sugere falhas no sistema remuneratório que ainda depende de maior transparência e outros mecanismos de governança para alinhar os interesses entre executivos e acionistas.The objective of this dissertation is to analyze the relation between management compensation and firm performance of Brazilian public listed companies at BM&FBOVESPA. The theoretical supposes that the incentive contract corroborates with the interests alignment between shareholders and managers and acts as a mechanism of corporate governance in order to drive the managers efforts for maximization of firm value. The sample is 100 more liquid listed firms in share trading at BM&FBOVESPA during the period of 2010 to 2012, for 296 sample observations. Data was obtained from the Reference Forms of Brazilian SEC (Comissão de Valores Mobiliários — CVM) and from Economática® as well from Thomson Reuters®. Eight hypotheses were tested as well as OLS regression models with unbalanced panel data, using the total compensation as the dependent variable and, for independent variables, variables concerning performance, firm value, size, ownership structure, corporate governance and control variables as well. To verify the factors that explain the usage of stock options and bonus programs, logit models were used. The results show that, in the selected sample, the greater the company size, board and firm value, the greater will be the manager compensation. Some industries like mining, chemistry, oil and gas, also plays a positive influence on manager compensation. Further, there is inverse relationship between total manager compensation and ownership concentration, the public rights of control and the governance classification set by BM&FBOVESPA. A greater firm value influences the utilization of stock options, as well as the use of bonus, being this impacted by grater firm performance. There were also robust check tests estimated by random effects, clustered standard-errors, dynamic models but the results remained the same. Therefore that the executive compensation is related with the corporate value, creating wealth to the shareholders; but the lack of relation with operational performance suggests failures on the compensation system which still depends on greater transparency and other governance mechanisms to align the interests of CEOs and shareholders

Beating ratio 0.5 for weighted oblivious matching problems

ESA 2016 is organized in collaboration with the European Association for Theoretical Computer Science (EATCS) and is a part of ALGO 2016We prove the first non-trivial performance ratios strictly above 0.5 for weighted versions of the oblivious matching problem. Even for the unweighted version, since Aronson, Dyer, Frieze, and Suen first proved a non-trivial ratio above 0.5 in the mid-1990s, during the next twenty years several attempts have been made to improve this ratio, until Chan, Chen, Wu and Zhao successfully achieved a significant ratio of 0.523 very recently (SODA 2014). To the best of our knowledge, our work is the first in the literature that considers the node-weighted and edge-weighted versions of the problem in arbitrary graphs (as opposed to bipartite graphs). (1) For arbitrary node weights, we prove that a weighted version of the Ranking algorithm has ratio strictly above 0.5. We have discovered a new structural property of the ranking algorithm: if a node has two unmatched neighbors at the end of algorithm, then it will still be matched even when its rank is demoted to the bottom. This property allows us to form LP constraints for both the node-weighted and the unweighted oblivious matching problems. As a result, we prove that the ratio for the node-weighted case is at least 0.501512. Interestingly via the structural property, we can also improve slightly the ratio for the unweighted case to 0.526823 (from the previous best 0.523166 in SODA 2014). (2) For a bounded number of distinct edge weights, we show that ratio strictly above 0.5 can be achieved by partitioning edges carefully according to the weights, and running the (unweighted) Ranking algorithm on each part. Our analysis is based on a new primal-dual framework known as matching coverage, in which dual feasibility is bypassed. Instead, only dual constraints corresponding to edges in an optimal matching are satisfied. Using this framework we also design and analyze an algorithm for the edge-weighted online bipartite matching problem with free disposal. We prove that for the case of bounded online degrees, the ratio is strictly above 0.5.published_or_final_versio

Online algorithms for covering and packing problems with convex objectives

We present online algorithms for covering and packing problems with (non-linear) convex objectives. The convex covering problem is defined as ...postprin