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Algorithms and theory47205 (210)
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Shipra Agrawal and Nikhil R. Devanur
In this paper, we consider a very general model for exploration-exploitation tradeoff which allows arbitrary concave rewards and convex constraints on the decisions across time, in addition to the customary limitation on the time horizon. This model subsumes the classic multi-armed bandit (MAB) model, and the Bandits with Knapsacks (BwK) model of Badanidiyuru et al.[2013]. We also consider an extension of this model to allow linear contexts, similar to the linear contextual extension of the MAB model. We...
Publication details
Date: 1 June 2014
Type: Inproceeding
Publisher: ACM conference on Economics and Computation
Leon Bottou, Jonas Peters, Joaquin Quiñonero-Candela, Denis X. Charles, D. Max Chickering, Elon Portugaly, Dipankar Ray, Patrice Simard, and Ed Snelson
This work shows how to leverage causal inference to understand the behavior of complex learning systems interacting with their environment and predict the consequences of changes to the system. Such predictions allow both humans and algorithms to select the changes that would have improved the system performance. This work is illustrated by experiments on the ad placement system associated with the Bing search engine.
Publication details
Date: 1 November 2013
Type: Article
Publisher: Journal of Machine Learning Research
Number: Nov
Brendan Lucier, Ishai Menache, Joseph Naor, and Jonathan Yaniv
We consider mechanisms for online deadline-aware scheduling in large computing clusters. Batch jobs that run on such clusters often require guarantees on their completion time (i.e., deadlines). However, most existing scheduling systems implement fair-share resource allocation between users, an approach that ignores heterogeneity in job requirements and may cause deadlines to be missed. In our framework, jobs arrive dynamically and are characterized by their value and total resource demand (or estimation...
Publication details
Date: 1 July 2013
Type: Inproceeding
Yuezhou Lv and Thomas Moscibroda
We study Incentive Trees for motivating the participation of people in crowdsourcing or human tasking systems. In an Incentive Tree, each participant is rewarded for contributing to the system, as well as for soliciting new participants into the system, who then themselves contribute to it and/or themselves solicit new participants. An Incentive Tree mechanism is an algorithm that determines how much reward each individual participant receives based on all the participants’ contributions, as well as the...
Publication details
Date: 1 July 2013
Type: Inproceeding
Publisher: ACM
Mahyar Salek, Yoram Bachrach, and Peter Key
Object localization is an image annotation task which consists of finding the location of a target object in an image. It is common to crowdsource annotation tasks and aggregate responses to estimate the true annotation. While for other kinds of annotations consensus is simple and powerful, it cannot be applied to object localization as effectively due to the task’s rich answer space and inherent noise in responses. We propose a probabilistic graphical model to localize objects in images based on responses...
Publication details
Date: 1 July 2013
Type: Inproceeding
Publisher: AAAI
Ben Roberts, Ian Kash, and Peter Key
In a sponsored search auction, decisions about how to rank ads impose tradeoffs between objectives such as revenue and welfare. In this paper, we examine how these tradeoffs should be made. We begin by arguing that the most natural solution concept to evaluate these tradeoffs is the lowest symmetric Nash equilibrium (SNE). As part of this argument, we generalize the well known connection between the lowest SNE and the VCG outcome. We then propose a new ranking algorithm, loosely based on the...
Publication details
Date: 1 June 2013
Type: Inproceeding
Publisher: ACM
Anand Bhalgat, Sreenivas Gollapudi, and Kamesh Munagala
We show that the multiplicative weight update method provides a simple recipe for designing and analyzing optimal Bayesian Incentive Compatible (BIC) auctions, and reduces the time complexity of the problem to polynomial in parameters that depend on single agent instead of on the joint type space. We use this framework to design the first computationally efficient optimal auctions that satisfy ex-post Individual Rationality in the presence of constraints such as (hard, private) budgets and envy-freeness....
Publication details
Date: 1 June 2013
Type: Inproceeding
Publisher: ACM Conference on Electronic Commerce
Kshipra Bhawalkar, Sreenivas Gollapudi, and Kamesh Munagala
We present game-theoretic models of opinion formation in social networks where opinions themselves co-evolve with friendships. In these models, nodes form their opinions by maximizing agreements with friends weighted by the strength of the relationships, which in turn depend on difference in opinion with the respective friends. We define a social cost of this process by generalizing recent work of Bindel et al., FOCS 2011. We tightly bound the price of anarchy of the resulting dynamics via local smoothness...
Publication details
Date: 1 June 2013
Type: Inproceeding
Publisher: ACM
Publication details
Date: 1 January 2013
Type: Article
Number: 99
Yiling Chen, Stephen Chong, Ian A. Kash, Tal Moran, and Salil Vadhan
Publication details
Date: 1 January 2013
Type: Inproceeding
Publication details
Date: 1 January 2013
Type: Inproceeding
Dipanjan Chakraborty, Indrani Medhi, Edward Cutrell, and William Thies
Many organizations in the developing world need to conduct phone surveys to collect data from low-income respondents. Such organizations generally have two options: employ a live operator, or utilize interactive voice response (IVR). Despite the relevance of this question, we are unaware of any work that rigorously compares the accuracy, speed, and cost of an IVR survey relative to a live operator. In this paper, we address these questions by giving two identical interviews { one using IVR, and one using...
Publication details
Date: 1 January 2013
Type: Proceedings
Publisher: ACM Symposium on Computing for Development (ACM DEV)
Itai Ashlagi, Felix Fischer, Ian A. Kash, and Ariel Procaccia
Publication details
Date: 1 January 2013
Type: Article
Saikat Guha and Srikanth Kandula
Data breaches, e.g. malware, network intrusions, or physical theft, that lead to the compromise of users’ personal data, happen often. The impacted companies lose reputation and have to spend millions of dollars providing affected users with identity and credit monitoring services. Users can suffer from fraudulent transactions and identity theft. At present, there are no mechanisms that both cover the risk from accidental data breaches and incentivise best practices that would prevent such breaches. This...
Publication details
Date: 1 October 2012
Type: Inproceeding
Kareem Amin, Michael Kearns, Peter Key, and Anton Schwaighofer
We consider the budget optimization problem faced by an advertiser participating in repeated sponsored search auctions, seeking to maximize the number of clicks attained under that budget. We cast the budget optimization problem as a Markov Decision Process (MDP) with censored observations, and propose a learning algorithm based on the well-known Kaplan-Meier or product-limit estimator. We validate the performance of this algorithm by comparing it to several others on a large set of search auction data...
Publication details
Date: 1 August 2012
Type: Inproceeding
Publisher: Uncertainty in Artificial Intelligence (UAI)
David F. Bacon, David C. Parkes, Yiling Chen, Malvika Rao, Ian Kash, and Manu Sridharan
Publication details
Date: 1 May 2012
Type: Inproceeding
Vineet Abhiskeh, Ian A Kash, and Peter Key
This paper considers two simple pricing schemes for selling cloud instances and studies the trade-off between them. We characterize the equilibrium for the hybrid system where arriving jobs can choose between fixed or the market based pricing. We provide theoretical and simulation based evidence suggesting that fixed price generates a higher expected revenue than the hybrid system.
Publication details
Date: 1 March 2012
Type: Inproceeding
Publisher: NetEcon
Pushmeet Kohli, Yoram Bachrach, David Stillwell, Michael Kearns, Ralf Herbrich, and Thore Graepel
We study how social relations between people affect the way they play the famous resource allocation game called Colonel Blotto. We report the deployment of a Facebook application called “Project Waterloo” which allows users to invite both friends and strangers to play Colonel Blotto against them. Most previous empirical studies of Blotto have been performed in a laboratory environment and have typically employed monetary incentives to attract human subjects to play games. In contrast, our framework relies...
Publication details
Date: 1 January 2012
Type: Inproceeding
Publisher: ACM Conference on Web Sciences
Publication details
Date: 1 January 2012
Type: Article
Publisher: Springer-Verlag
Number: 5
Reshef Meir, Moshe Tennenholtz, Yoram Bachrach, and Peter Key
We propose a natural model for agent failures in congestion games. In our model, each of the agents may fail to participate in the game, introducing uncertainty regarding the set of active agents. We examine how such uncertainty may change the Nash equilibria (NE) of the game. We prove that although the perturbed game induced by the failure model is not always a congestion game, it still admits at least one pure Nash equilibrium. Then, we turn to examine the effect of failures on the maximal social cost in...
Publication details
Date: 1 January 2012
Type: Inproceeding
Publisher: Association for the Advancement of Artificial Intelligence
Xi Alice Gao, Yoram Bachrach, Peter Key, and Thore Graepel
We examine designs for crowdsourcing contests, where participants compete for rewards given to superior solutions of a task. We theoretically analyze tradeoffs between the expectation and variance of the principal’s utility (i.e. the best solution’s quality), and empirically test our theoretical predictions using a controlled experiment on Amazon Mechanical Turk. Our evaluation method is also crowdsourcing based and relies on the peer prediction mechanism. Our theoretical analysis shows an...
Publication details
Date: 1 January 2012
Type: Inproceeding
Publisher: Association for the Advancement of Artificial Intelligence
Michal Kosinski, Yoram Bachrach, Gjergji Kasneci, Jurgen Van-Gael, and Thore Graepel
We measure crowdsourcing performance based on a standard IQ questionnaire, and examine Amazon's Mechanical Turk (AMT) performance under different conditions. These include variations of the payment amount offered, the way incorrect responses affect workers' reputations, threshold reputation scores of participating AMT workers, and the number of workers per task. We show that crowds composed of workers of high reputation achieve higher performance than low reputation crowds, and the effect of the amount of...
Publication details
Date: 1 January 2012
Type: Inproceeding
Publisher: ACM Conference on Web Sciences
Yoram Bachrach, Ian Kash, and Nisarg Shah
We examine the impact of independent agents failures on the solutions of cooperative games, focusing on totally balanced games and the more specific subclass of convex games. We follow the reliability extension model, and show that a (approximately) totally balanced (or convex) game remains (approximately) totally balanced (or convex) when independent agent failures are introduced or when the failure probabilities increase. One implication of these results is that any reliability extension of a totally...
Publication details
Date: 1 January 2012
Type: Inproceeding
Publication details
Date: 1 January 2012
Type: Inproceeding
R Gummadi, P B Key, and A Proutiere
We consider the problem of a bidder with limited budget competing in a series of second-price auctions. A motivating example is that of sponsored search auctions, where advertisers bid in a sequence of repeated generalized second price auctions. To characterize the optimal bidding strategy, we formulate the problem as a discounted Markov Decision Process, and provide explicit solutions when the bidder is involved in a large number of auctions.
Publication details
Date: 30 September 2011
Type: Inproceeding
Publisher: IEEE
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