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Imperative Process Algebra and Models of Parallel Computation
Studies of issues related to computability and computational complexity involve the use of a model of computation. Central in such a model are...
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Verification and computation in restricted Tile Automata
Many models of self-assembly have been shown to be capable of performing computation. Tile Automata was recently introduced combining features of...
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Federated computation: a survey of concepts and challenges
Federated Computation is an emerging area that seeks to provide stronger privacy for user data, by performing large scale, distributed computations...
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Fast Symbolic Computation of Bottom SCCs
The computation of bottom strongly connected components (BSCCs) is a fundamental task in model checking, as well as in characterizing the attractors...
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Restricted Boltzmann Machines
The restricted Boltzmann machine (RBM) is a fundamentally different model from the feed-forward network. Conventional neural networks are...
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Restricted Flow Games
Classical graph problems are defined with respect to plain graphs, namely vertices connected by possibly weighted edges. On the other hand, model...
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DIDO: Data Provenance from Restricted TLS 1.3 Websites
Public data can be authenticated by obtaining from a trustworthy website with TLS. Private data, such as user profile, are usually restricted from...
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Equivalent convolution strategy for the evolution computation in parametric active contour model
Parametric active contour model is an efficient approach for image segmentation. However, the high cost of evolution computation has restricted their...
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Relational Expressions for Data Transformation and Computation
Separate programming models for data transformation (declarative) and computation (procedural) impact programmer ergonomics, code reusability and...
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Recommendation-based trust computation and rating prediction model for security enhancement in cloud computing systems
The cloud service providers need to deliver cloud services based on the service level agreement to their users. The services must be secure and...
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Boundary-restricted metric learning
Metric learning aims to learn a distance metric to properly measure the similarities between pairwise examples. Most existing learning algorithms are...
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On the Power of an Honest Majority in Three-Party Computation Without Broadcast
Fully secure multiparty computation (MPC) allows a set of parties to compute some function of their inputs, while guaranteeing correctness, privacy,...
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Nonadiabatic holonomic quantum computation and its optimal control
The geometric phase has the intrinsic property of being resistant to some types of local noises as it only depends on global properties of the...
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The application of evolutionary computation in generative adversarial networks (GANs): a systematic literature survey
As a subfield of deep learning (DL), generative adversarial networks (GANs) have produced impressive generative results by applying deep generative...
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An expectile computation cookbook
A substantial body of work in the last 15 years has shown that expectiles constitute an excellent candidate for becoming a standard tool in...
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R3PO: Reach-Restricted Reactive Program Obfuscation and Its Applications
In recent breakthrough results, novel use of grabled circuits yielded constructions for several primitives like Identity-Based Encryption (IBE) and...
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Efficiently approaching vertical federated learning by combining data reduction and conditional computation techniques
In this paper, a framework based on a sparse Mixture of Experts (MoE) architecture is proposed for the federated learning and application of a...
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A Survey on Analog Models of Computation
We present a survey on analog models of computation. Analog can be understood both as computing by analogy, or as working on the continuum. We...
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On designing the adaptive computation framework of distributed deep learning models for Internet-of-Things applications
Deep learning methods have been gradually adopted in the Internet-of-Things (IoT) applications. Nevertheless, the large demands for the computation...
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Approaches for coarsest granularity based near-optimal reduct computation
Traditionally, the shortest length has been used as the optimality criterion in rough set based optimal / near-optimal reduct computation. A more...
