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9,156
Approximately Strategy-Proof Voting
- PROCEEDINGS OF THE TWENTY-SECOND INTERNATIONAL JOINT CONFERENCE ON ARTIFICIAL INTELLIGENCE
, 2011
"... The classic Gibbard-Satterthwaite Theorem establishes that only dictatorial voting rules are strategyproof; under any other voting rule, players have an incentive to lie about their true preferences. We consider a new approach for circumventing this result: we consider randomized voting rules that o ..."
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Cited by 11 (1 self)
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that only approximate a deterministic voting rule and only are approximately strategy-proof. We show that any deterministic voting rule can be approximated by an approximately strategy-proof randomized voting rule, and we provide asymptotically tight lower bounds on the parameters required by such voting
Shannon, TESPAR And Approximation Strategies
"... This paper outlines the development and application of an alternative embodiment of Claude Shannon’s celebrated sampling theorem qualified by Shannon in 1949 and tested more recently by the authors, via the classification of a wide variety of real-world band-limited waveforms. The work of Voelcker, ..."
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, Requicha et. al. is called upon and developed, to indicate key features of the basic coding concept, designated “Time-Encoded Signal Processing And Recognition ” (TESPAR). TESPAR coding is based upon approximations to the locations of the 2TW Real and Complex Zeros, derived from an analysis
Maximizing the Spread of Influence Through a Social Network
- In KDD
, 2003
"... Models for the processes by which ideas and influence propagate through a social network have been studied in a number of domains, including the diffusion of medical and technological innovations, the sudden and widespread adoption of various strategies in game-theoretic settings, and the effects of ..."
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Cited by 990 (7 self)
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the first provable approximation guarantees for efficient algorithms. Using an analysis framework based on submodular functions, we show that a natural greedy strategy obtains a solution that is provably within 63 % of optimal for several classes of models; our framework suggests a general approach
SPEA2: Improving the Strength Pareto Evolutionary Algorithm
, 2001
"... The Strength Pareto Evolutionary Algorithm (SPEA) (Zitzler and Thiele 1999) is a relatively recent technique for finding or approximating the Pareto-optimal set for multiobjective optimization problems. In different studies (Zitzler and Thiele 1999; Zitzler, Deb, and Thiele 2000) SPEA has shown very ..."
Abstract
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Cited by 708 (19 self)
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The Strength Pareto Evolutionary Algorithm (SPEA) (Zitzler and Thiele 1999) is a relatively recent technique for finding or approximating the Pareto-optimal set for multiobjective optimization problems. In different studies (Zitzler and Thiele 1999; Zitzler, Deb, and Thiele 2000) SPEA has shown
SMOTE: Synthetic Minority Over-sampling Technique
- Journal of Artificial Intelligence Research
, 2002
"... An approach to the construction of classifiers from imbalanced datasets is described. A dataset is imbalanced if the classification categories are not approximately equally represented. Often real-world data sets are predominately composed of ``normal'' examples with only a small percentag ..."
Abstract
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Cited by 634 (27 self)
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An approach to the construction of classifiers from imbalanced datasets is described. A dataset is imbalanced if the classification categories are not approximately equally represented. Often real-world data sets are predominately composed of ``normal'' examples with only a small
Power provisioning for a warehousesized computer,”
- ACM SIGARCH Computer Architecture News,
, 2007
"... ABSTRACT Large-scale Internet services require a computing infrastructure that can be appropriately described as a warehouse-sized computing system. The cost of building datacenter facilities capable of delivering a given power capacity to such a computer can rival the recurring energy consumption ..."
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Cited by 450 (2 self)
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consumption tends to vary significantly with the actual computing activity. Effective power provisioning strategies are needed to determine how much computing equipment can be safely and efficiently hosted within a given power budget. In this paper we present the aggregate power usage characteristics of large
Locality-constrained linear coding for image classification
- IN: IEEE CONFERENCE ON COMPUTER VISION AND PATTERN CLASSIFICATOIN
, 2010
"... The traditional SPM approach based on bag-of-features (BoF) requires nonlinear classifiers to achieve good image classification performance. This paper presents a simple but effective coding scheme called Locality-constrained Linear Coding (LLC) in place of the VQ coding in traditional SPM. LLC util ..."
Abstract
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Cited by 443 (20 self)
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, achieving state-of-the-art performance on several benchmarks. Compared with the sparse coding strategy [22], the objective function used by LLC has an analytical solution. In addition, the paper proposes a fast approximated LLC method by first performing a K-nearest-neighbor search and then solving a
Complexity results and approximation strategies for map explanations
- Journal of Artificial Intelligence Research
, 2004
"... MAP is the problem of finding a most probable instantiation of a set of variables given evidence. MAP has always been perceived to be significantly harder than the related problems of computing the probability of a variable instantiation (Pr), or the problem of computing the most probable explanatio ..."
Abstract
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Cited by 44 (4 self)
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. For example, we show that MAP is NP-complete when the networks are restricted to polytrees, and even then can not be effectively approximated. Given the difficulty of computing MAP exactly, and the difficulty of approximating MAP while providing useful guarantees on the resulting approximation, we investigate
Exact and approximate strategies for symmetry reduction in model checking.
- In FM’06, LNCS 4085,
, 2006
"... Abstract. Symmetry reduction techniques can help to combat the state space explosion problem for model checking, but are restricted by the hard problem of determining equivalence of states during search. Consequently, existing symmetry reduction packages can only exploit full symmetry between syste ..."
Abstract
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Cited by 10 (4 self)
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system components, as checking the equivalence of states is straightforward in this special case. We present a framework for symmetry reduction with an arbitrary group of structural symmetries. By generalising existing techniques for efficiently exploiting symmetry, and introducing an approximate
Approximation Strategies for Multi-Structure Sentence Compression
"... Sentence compression has been shown to benefit from joint inference involving both n-gram and dependency-factored objec-tives but this typically requires expensive integer programming. We explore instead the use of Lagrangian relaxation to decou-ple the two subproblems and solve them separately. Whi ..."
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bigram-based inference approach using Lagrange multipliers. Experiments show that these approximation strategies produce results comparable to a state-of-the-art integer linear programming formulation for the same joint inference task along with a sig-nificant improvement in runtime. 1
Results 1 - 10
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9,156
