Crowdsourced, or human computation based clustering algorithms usually rely on relative distance comparisons, as these are easier to elicit from human workers than absolute distance information. We build upon existing...
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ISBN:
(纸本)9781538638354
Crowdsourced, or human computation based clustering algorithms usually rely on relative distance comparisons, as these are easier to elicit from human workers than absolute distance information. We build upon existing work on correlation clustering, a well-known non-parametric approach to clustering, and present a novel clustering algorithm for human computation. We first define a novel variant of correlation clustering that is based on relative distance comparisons, and briefly outline an approximation algorithm for this problem. As a second contribution, we propose a more practical algorithm, which we empirically compare against existing methods from literature. Experiments with synthetic data suggest that our approach can outperform more complex methods. Also, our method efficiently finds good and intuitive clusterings from real relative distance comparison data.
This paper studies problems on locally stopping distributed consensus algorithms over networks where each node updates its state by interacting with its neighbors and decides by itself whether certain level of agreeme...
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ISBN:
(纸本)9781509028733
This paper studies problems on locally stopping distributed consensus algorithms over networks where each node updates its state by interacting with its neighbors and decides by itself whether certain level of agreement has been achieved among nodes. Since an individual node is unable to access the states of those beyond its neighbors, this problem becomes challenging. In this work, we first define the stopping problem for generic distributed algorithms. Then, a distributed algorithm is explicitly provided for each node to stop consensus updating by exploring the relationship between the so-called local and global consensus. Finally, we show both in theory and simulation that its effectiveness depends both on the network size and the structure.
In the age of big data, many graph algorithms are now required to operate in external memory and deliver performance that does not significantly degrade with the scale of the problem. One particular area that frequent...
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ISBN:
(纸本)9781538638354
In the age of big data, many graph algorithms are now required to operate in external memory and deliver performance that does not significantly degrade with the scale of the problem. One particular area that frequently deals with graphs larger than RAM is triangle listing, where the algorithms must carefully piece together edges from multiple partitions to detect cycles. In recent literature, two competing proposals (i.e., Pagh and PCF) have emerged;however, neither one is universally better than the other. Since little is known about the I/O cost of PCF or how these methods compare to each other, we undertake an investigation into the properties of these algorithms, model their I/O cost, understand their shortcomings, and shed light on the conditions under which each method defeats the other. This insight leads us to develop a novel framework we call Trigon that surpasses the I/O performance of both previous techniques in all graphs and under all RAM conditions.
Random Key (RK) is an alternative representation for permutation problems that enables application of techniques generally used for continuous optimisation. Although the benefit of RKs to permutation optimisation has ...
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ISBN:
(纸本)9781509046010
Random Key (RK) is an alternative representation for permutation problems that enables application of techniques generally used for continuous optimisation. Although the benefit of RKs to permutation optimisation has been shown, its use within Estimation of Distribution algorithms (EDAs) has been a challenge. Recent research proposing a RK-based EDA (RK-EDA) has shown that RKs can produce competitive results with state of the art algorithms. Following promising results on the Permutation Flowshop Scheduling Problem, this paper presents an analysis of RK-EDA for optimising the total flow time. Experiments show that RK-EDA outperforms other permutation-based EDAs on instances of large dimensions. The difference in performance between RK-EDA and the state of the art algorithms also decreases when the problem difficulty increases.
The Sentinel fleet will provide a so-far unique coverage with Earth observation (EO) data and therewith new opportunities for the implementation of methodologies to generate innovative geo-information products and ser...
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ISBN:
(纸本)9781509058082
The Sentinel fleet will provide a so-far unique coverage with Earth observation (EO) data and therewith new opportunities for the implementation of methodologies to generate innovative geo-information products and services. It is here where the TEP Urban project is supposed to initiate a step change by providing an open and participatory platform based on modern Information and Communication Technologies (ICTs) that enable any interested user to easily exploit EO data pools, in particular those of the Sentinel missions, and derive thematic information on the status and development of the built environment from these data. Key component of TEP Urban project is the implementation of a web-based platform employing distributed high-level computing infrastructures and providing key functionalities for i) high-performance access to satellite imagery and derived thematic data, ii) modular and generic state-of-the-art pre-processing, analysis, and visualization techniques, iii) customized development and dissemination of algorithms, products and services, and iv) networking and communication. This contribution introduces the main facts about the TEP Urban project, including a description of the general objectives, the platform systems design and functionalities, and the preliminary portfolio products and services available at the TEP Urban platform.
This paper presents a fast sample adaptive offset (SAO) parameter estimation algorithm for high efficiency video coding (HEVC) encoder. The proposed algorithm decides the best SAO parameters earlier by exploiting a sp...
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ISBN:
(纸本)9781509055449
This paper presents a fast sample adaptive offset (SAO) parameter estimation algorithm for high efficiency video coding (HEVC) encoder. The proposed algorithm decides the best SAO parameters earlier by exploiting a spatial correlation between current and neighbor SAO types. From the experimental results, the proposed algorithm achieves 56.02% time-saving with only 0.26% bitrate increase on average, compared to HE VC reference software HM 16.9 under common test condition.
Multipath TCP ( MPTCP) enables transmission via multiple routes for an end-to-end connection to improve resource usage of regular TCP. Due to the increasing concern in green computing, there has been significant inter...
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ISBN:
(纸本)9781538617915
Multipath TCP ( MPTCP) enables transmission via multiple routes for an end-to-end connection to improve resource usage of regular TCP. Due to the increasing concern in green computing, there has been significant interest in designing energyefficient multipath transport. For existing MPTCP congestion control algorithms, the research community still lacks a comprehensive understanding of which components in such an algorithm play the fundamental role in energy efficiency, how various algorithms compare against each other from energy-consuming perspective, or whether there exist potentially better solutions for energy saving. In this paper, we take a first step to answer these questions. Based on the MPTCP Linux kernel experiments, we first summarize that the energy consumption is related to three aspects: average throughput, path delay and different network scenarios. In order to bridge congestion control to the three aspects, we analyze the existing algorithms and capture the essential parameters of multipath congestion control model related to MPTCP's energy-efficiency. Then we design a window increase factor to shift traffic to low-delay energy-efficient paths. We further extend this design by using an energy-aware compensative parameter to fit the general hierarchical Internet topology. We evaluate the performance of existing multipath congestion control algorithms and our proposed algorithm in different network scenarios. The results successfully validate the improved energy efficiency of our design.
We consider how asynchronous networks of agents who imitate their highest-earning neighbors can be efficiently driven towards a desired strategy by offering payoff incentives, either uniformly or targeted to individua...
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ISBN:
(纸本)9781509028733
We consider how asynchronous networks of agents who imitate their highest-earning neighbors can be efficiently driven towards a desired strategy by offering payoff incentives, either uniformly or targeted to individuals. In particular, if for each available strategy, agents playing that strategy receive maximum payoff when their neighbors play that same strategy, we show that providing incentives to agents in a network that is at equilibrium will result in convergence to a unique equilibrium. When a uniform incentive can be offered to all agents, one can compute the optimal incentive using a binary search algorithm. When incentives can be targeted to individuals, we propose an algorithm to select which agents should be chosen based on iteratively maximizing a ratio of the number of agents who adopt the desired strategy to the payoff incentive required to get those agents to do so. Simulations demonstrate that this algorithm computes near-optimal targeted payoff incentives for a range of networks and payoff distributions in coordination games.
The non-exact projective NPNP (NP3) Boolean matching problem is practically significant in the applications of technology mapping, logic verification, and hardware security. However, its difficulty compels an unsatisf...
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ISBN:
(纸本)9781467368537
The non-exact projective NPNP (NP3) Boolean matching problem is practically significant in the applications of technology mapping, logic verification, and hardware security. However, its difficulty compels an unsatisfactory running time, and conventional algorithms for the basic NPNP Boolean matching problem perform terribly on the non-exact and projective type. In this paper, we propose a novel algorithm to solve this newly rising NP3 Boolean matching problem, and multiple types of optimization were applied to further improve the performance. Experimental results indicate that our algorithm has outstanding outcomes.
Path planning for automated parking remains challenged by the demand to balance general parking scenarios and computational efficiency. This paper proposes a two-stage rapid-exploring random tree (RRT) algorithm to im...
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ISBN:
(纸本)9781509067817
Path planning for automated parking remains challenged by the demand to balance general parking scenarios and computational efficiency. This paper proposes a two-stage rapid-exploring random tree (RRT) algorithm to improve the computational efficiency. At first the proposed algorithm performs space exploration and establishes prior knowledge, represented as waypoints, using cheap computation. Secondly a waypoint-guided RRT algorithm, with a sampling scheme biased by the waypoints, constructs a kinematic tree connecting the initial and goal configurations. Numerical study demonstrates that the two-stage algorithm achieves at least 2X faster than the baseline one-stage algorithm.
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