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Inherit or discard: learning better domain-specific child networks from the general domain for multi-domain NMT
Multi-domain NMT aims to develop a parameter-sharing model for translating general and specific domains, such as biology, legal, etc., which often...
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MHTFPE2D: two-dimensional multi-scale hierarchical time–frequency permutation entropy for complexity measurement
As a nonlinear dynamic index, hierarchical permutation entropy (HPE) can effectively represent the complexity change of time series. However, HPE...
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A generalized dual-domain generative framework with hierarchical consistency for medical image reconstruction and synthesis
Medical image reconstruction and synthesis are critical for imaging quality, disease diagnosis and treatment. Most of the existing generative models...
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Global-chronological graph interactive networks for multi-domain dialogue state tracking
Dialogue state tracking (DST) provides necessary information for the policy learning module to decide the next action according to the historical...
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A multi-feature fusion approach based on domain adaptive pretraining for aspect-based sentiment analysis
Aspect-based sentiment analysis aims to recognize the sentiment polarities for opinion words with the aid of some machine learning or deep...
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Gate-Enhanced Multi-domain Dialog State Tracking for Task-Oriented Dialogue Systems
Dialogue state tracking (DST) task is a core component of task-oriented dialogue systems. Recently, several open-vocabulary-based models were...
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A multi-domain BEM based on the dual interpolation boundary face method for 3D potential problems
In this paper, a multi-domain method, based on the dual interpolation boundary face method with Hermite-type moving-least-squares approximation...
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Exploring and exploiting hierarchical structures for large-scale classification
Classification and recognition tasks confronted by intelligent systems are becoming complicated as the sizes of samples, dimensionality and labels...
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Encrypted Image Search Based on SGX and Hierarchical Index
Cloud computing meets the storage and computing needs brought about by the explosive growth of images, but it also raises privacy threats. Encryption...
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Multi-theme hierarchical monitoring method for wireless sensor networks
In large-scale industrial and agricultural production environments, many nodes of the Internet of Things (IoT) were deployed. These nodes are of...
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Hierarchical generative modelling for autonomous robots
Humans generate intricate whole-body motions by planning, executing and combining individual limb movements. We investigated this fundamental aspect...
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An Energy-Aware Model for Wireless Sensor Networks: Hierarchical Compressive Data Gathering for Hierarchical Grid-Based Routing (HCDG-HGR)
In wireless sensor networks compressive sensing (CS) is an effective alternative technique for traditional data gathering methods which affect the...
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Group-aggregation of Hierarchical Containment Control for Homogeneous Multi-agent Systems in Precision Agriculture
The mixed planting, as one of the diversification strategies, provides the substitute for many costly inputs, such as fertilizers, pesticides,...
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Learning Multiple-Gait Quadrupedal Locomotion via Hierarchical Reinforcement Learning
Over long periods of evolution, legged animals have developed the capability to use a variety of gaits to move efficiently and flexibly at different...
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H-Louvain: Hierarchical Louvain-based community detection in social media data streams
The rise of online social networks has fundamentally transformed the traditional way of social interaction and information dissemination, leading to...
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Hierarchical model updating for high-speed maglev vehicle/guideway coupled system based on multi-objective optimization
The high-speed maglev vehicle/guideway coupled model is an essential simulation tool for investigating vehicle dynamics and mitigating coupled...
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A hierarchical multi-agent allocation-action learning framework for multi-subtask games
Great progress has been made in the domain of multi-agent reinforcement learning in recent years. Most work concentrates on solving a single task by...
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Application of hierarchical symbolic fuzzy entropy and sparse Bayesian ELM to bearing fault diagnosis
Bearing fault diagnosis is essential for reducing equipment operating and maintenance costs. We propose a bearing fault diagnosis method that...
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Biomedical event causal relation extraction based on a knowledge-guided hierarchical graph network
Biomedical Event Causal Relation Extraction (BECRE) is a challenging task in biological information extraction and plays a crucial role to serve for...
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Hierarchical few-shot learning based on top-down correction mechanism with stop strategy
Few-shot learning has become an important branch of machine learning, which aims to give correct prediction information to unknown samples. Many...
