With the fast growth of smart devices and social networks, a lot of computing systems collect data that record different types of activities. An important computational challenge is to analyze these data, extract patt...
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ISBN:
(纸本)9781450329569
With the fast growth of smart devices and social networks, a lot of computing systems collect data that record different types of activities. An important computational challenge is to analyze these data, extract patterns, and understand activity trends. We consider the problem of mining activity networks to identify interesting events, such as a big concert or a demonstration in a city, or a trending keyword in a user community in a social network. We define an event to be a subset of nodes in the network that are close to each other and have high activity levels. We formalize the problem of event detection using two graph-theoretic formulations. The first one captures the compactness of an event using the sum of distances among all pairs of the event nodes. We show that this formulation can be mapped to the MAxCuT problem, and thus, it can be solved by applying standard semidefinite programming techniques. The second formulation captures compactness using a minimum-distance tree. This formulation leads to the prize-collecting Steiner-tree problem, which we solve by adapting existing approximation algorithms. For the two problems we introduce, we also propose efficient and effective greedy approaches and we prove performance guarantees for one of them. We experiment with the proposed algorithms on real datasets from a public bicycling system and a geolocation-enabled social network dataset collected from twitter. The results show that our methods are able to detect meaningful events.
We study the polyhedral structure of a mixed 0-1 set arising in the submodularmaximization problem, given by P = {(w, x) is an element of R x {0,1}(n) : w <= f (x), x is an element of chi}, where submodular functi...
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ISBN:
(纸本)9783030457716;9783030457709
We study the polyhedral structure of a mixed 0-1 set arising in the submodularmaximization problem, given by P = {(w, x) is an element of R x {0,1}(n) : w <= f (x), x is an element of chi}, where submodularfunction f(x) is represented by a concave function composed with a linear function, and chi is the feasible region of binary variables x. For chi = {0, 1}(n), two families of facet-defining inequalities are proposed for the convex hull of P through restriction and lifting using submodular inequalities. When chi is a partition matroid, we propose a new class of facet-defining inequalities for the convex hull of P through multidimensional sequence independent lifting. Our results enable us to unify and generalize the existing results on valid inequalities for the mixed 0-1 knapsack. Finally, we perform some preliminary computational experiments to illustrate the superiority of our facet-defining inequalities.
In heterogeneous networks(HetNets), offloading mobile users to less congested small cells results in a degraded SINR for offloaded users and leads to a high probability of outage for these users. In this paper, we pro...
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ISBN:
(纸本)9781479989935
In heterogeneous networks(HetNets), offloading mobile users to less congested small cells results in a degraded SINR for offloaded users and leads to a high probability of outage for these users. In this paper, we proposes a general framework to solve the cell association problem for load balancing while improving system outage performance in a downlink multi-tier HetNet. A bi-criterion optimization problem is formulated to strike a tradeoff between load balancing and outage performance. Our method inherits the utility maximization with proportional fairness objectives, and explicitly takes into account the outage probabilities for users. In addition, we show this combinatorial bi-criterion optimization problem can be reformulated as a submodular function maximization problem and propose a greedy lazy algorithm that offers a near optimal solution to the reformulated problem, which enforces single BS association for each user. Simulation results show that our proposed method achieves load balancing and improves system outage performance significantly
Camera calibration is a crucial pre-processing for 3D related computer vision applications. When non-expert calibration operators capture calibration images, they strongly require guidance what kind of images must be ...
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ISBN:
(纸本)9789811548185;9789811548178
Camera calibration is a crucial pre-processing for 3D related computer vision applications. When non-expert calibration operators capture calibration images, they strongly require guidance what kind of images must be taken. In the literature, several types of supports have been proposed. Focusing on the plane-based calibration method proposed by Zhang, this paper proposed to such non-expert calibration operators. The proposed method asks such operators to take calibration images with variety of position and orientation and the method takes a subset of good quality images. Thanks to Gaussian Process modeling, the proposed method can select a near optimum subset with some accuracy guarantee in the sense of submodularity. To enable this, we propose to use 4-point parameterized homography as a global image feature. We conduct a small experiment with both synthesized and a public dataset and validate the proposed method works.
Application of point clouds is in critical demand, which, however, are composed of large amounts of data and difficult to stream in bandwidth-constrained networks. To address this, we propose a QoE-driven and tile-bas...
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ISBN:
(纸本)9781728176055
Application of point clouds is in critical demand, which, however, are composed of large amounts of data and difficult to stream in bandwidth-constrained networks. To address this, we propose a QoE-driven and tile-based adaptive streaming approach for point clouds, to reduce transmission redundancy and maximize user's QoE. Specifically, by utilizing the perspective projection, we model the QoE of a 3D tile as a function of the bitrate of its representation, user's view frustum and spatial position, occlusion between tiles, and the resolution of rendering device. We then formulate the QoE-optimized rate adaptation problem as a multiple-choice knapsack problem that allocates bitrates for different tiles under a given transmission capacity. We equivalently convert it as a submodular function maximization problem subject to knapsack constraints, and develop a practical greedy algorithm with a theoretical performance guarantee. Experimental results further demonstrate superiority of the proposed rate adaptation algorithm over existing schemes, in terms of both user's visual quality and transmission efficiency.
The traditional literature on camera network design focuses on constructing automated algorithms. These require problem-specific input from experts in order to produce their output. The nature of the required input is...
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The traditional literature on camera network design focuses on constructing automated algorithms. These require problem-specific input from experts in order to produce their output. The nature of the required input is highly unintuitive, leading to an impractical workflow for human operators. In this work we focus on developing a virtual reality user interface allowing human operators to manually design camera networks in an intuitive manner. From real world practical examples we conclude that the camera networks designed using this interface are highly competitive with, or sometimes even superior to, those generated by automated algorithms, but the associated workflow is more intuitive and simple. The competitiveness of the human-generated camera networks is remarkable because the structure of the optimization problem is a well known combinatorial NP-hard problem. These results indicate that human operators can be used in challenging geometrical combinatorial optimization problems, given an intuitive visualization of the problem.
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