AdaBoost is an excellent machine-learning algorithm, which produces a strong classifier by selecting the discriminating features and combining them linearly. But the computational complexity of AdaBoost algorithms is ...
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Driven by the market demand for high-definition 3D graphics, commodity graphics processing units (GPUs) have evolved into highly parallel, multi-threaded, many-core processors, which are ideal for data parallel comput...
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Massive information networks, such as the knowledge graph by Google, contain billions of labeled entities. Star queries, which aim to identify an entity, given a set of related entities, are common on such networks. A...
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ISBN:
(纸本)9781479976157
Massive information networks, such as the knowledge graph by Google, contain billions of labeled entities. Star queries, which aim to identify an entity, given a set of related entities, are common on such networks. Answering star queries can be modeled as a graph pattern matching problem. Traditional approaches apply graph indices to accelerate the query processing. Unfortunately, it is so costly that it is nearly infeasible to build indices on billion node graphs since the time or storage complexity of most indexing techniques is super-linear to the graph size. In this paper, we propose an algorithm to identify the top-k best answers for a star query. Instead of using expensive indices, our algorithm utilizes novel bounding techniques to derive the top-k best answers efficiently. Further, the algorithm can be implemented in a distributed manner scaling to billions of entities and hundreds of machines. We demonstrate the effectiveness and the efficiency of our approach through a series of experiments on real-world information networks.
The presented work is part of our long-term research goal to develop parallel SAT solving methods for large scale Peer-to-Peer Desktop Grids, which aggregate globally distributed resources. In such a parallel environm...
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The proceedings contain 125 papers. The topics discussed include: schedule swapping: a technique for temperature management of distributed embedded systems;user-level network protocol stacks for automotive infotainmen...
ISBN:
(纸本)9780769543222
The proceedings contain 125 papers. The topics discussed include: schedule swapping: a technique for temperature management of distributed embedded systems;user-level network protocol stacks for automotive infotainment systems;replay debugging for multi-threaded embedded software;optimizing runtime reconfiguration decisions;architectural support for reducing parallel processing overhead in an embedded multiprocessor;trading conditional execution for more registers on ARM processors;co-simulation of self-adaptive automotive embedded systems;empirical evaluation of content-based pub/sub systems over cloud infrastructure;a reflective service gateway for integrating evolvable sensor-actuator networks with pervasive infrastructure;handling mobility on a QoS-aware service-based framework for mobile systems;trust measurement methods in organic computing systems by direct observation;and rule-based approach for context inconsistency management scheme in ubiquitous computing.
SciCloud is a project studying the scope of establishing private clouds at universities. With these clouds, researchers can efficiently use the already existing resources in solving computationally intensive scientifi...
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Scientific applications are striving to accurately simulate multiple interacting physical processes that comprise complex phenomena being modeled. Efficient and scalable parallel implementations of these coupled simul...
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The lack of license management schemes in distributed environments is becoming a major obstacle for the commercial adoption of Grid or Cloud infrastructures. In this paper, we present a complete license management arc...
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We propose a two layer protocol for tracking fast targets in sensor networks. At the lower layer, the distributed Spanning Tree Algorithm (DSTA) [12] partitions the network into clusters with controllable diameter and...
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There is growing interest in large-scale systems where globally distributed and commoditized resources can be shared and traded, such as peer-to-peer networks, grids, and cloud computing. Users of these systems are ra...
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