Emotion quantification techniques for cognitive reappraisal: a systematic review and scientometric analysis
Cognitive reappraisal intends to study the significance of an event concerning any emotional
reaction. Understanding the efficacy of cognitive reappraisal in emotion regulation requires …
reaction. Understanding the efficacy of cognitive reappraisal in emotion regulation requires …
Trustworthy AI-based Performance Diagnosis Systems for Cloud Applications: A Review
Performance diagnosis systems are defined as detecting abnormal performance
phenomena and play a crucial role in cloud applications. An effective performance …
phenomena and play a crucial role in cloud applications. An effective performance …
Empowering generative AI with knowledge base 4.0: towards linking analytical, cognitive, and generative intelligence
A Beheshti - 2023 IEEE International Conference on Web …, 2023 - ieeexplore.ieee.org
Intelligence refers to the ability to acquire and apply knowledge and skills, which comprises
three fundamental components, namely knowledge, experience, and creativity …
three fundamental components, namely knowledge, experience, and creativity …
Federated iot interaction vulnerability analysis
IoT devices provide users with great convenience in smart homes. However, the
interdependent behaviors across devices may yield unexpected interactions. To analyze the …
interdependent behaviors across devices may yield unexpected interactions. To analyze the …
Enhancing federated learning with in-cloud unlabeled data
Federated learning (FL) has been widely applied to collaboratively train deep learning (DL)
models on massive end devices (ie, clients). Due to the limited storage capacity and high …
models on massive end devices (ie, clients). Due to the limited storage capacity and high …
Knowledge base 4.0: Using crowdsourcing services for mimicking the knowledge of domain experts
A Beheshti - 2022 IEEE International Conference on Web …, 2022 - ieeexplore.ieee.org
Intelligence is the ability to learn from experience. Knowledge workers in knowledge-
intensive processes develop invaluable domain-specific expertise and knowledge over time …
intensive processes develop invaluable domain-specific expertise and knowledge over time …
Ferrari: A personalized federated learning framework for heterogeneous edge clients
Federated semi-supervised learning (FSSL) has been proposed to address the insufficient
labeled data problem by training models with pseudo-labeling. In previous FSSL systems, a …
labeled data problem by training models with pseudo-labeling. In previous FSSL systems, a …
Semi-Supervised Decentralized Machine Learning with Device-to-Device Cooperation
The massive data from mobile and embedded devices have huge potential for training
machine learning models. Decentralized machine learning (DML) can avoid the inherent …
machine learning models. Decentralized machine learning (DML) can avoid the inherent …
On dynamically pricing crowdsourcing tasks
Crowdsourcing techniques have been extensively explored in the past decade, including
task allocation, quality assessment, and so on. Most of professional crowdsourcing platforms …
task allocation, quality assessment, and so on. Most of professional crowdsourcing platforms …
Enhancing federated learning with server-side unlabeled data by adaptive client and data selection
Federated learning (FL) has been widely applied to collaboratively train deep learning (DL)
models on massive end devices (ie, clients). Due to the limited storage capacity and high …
models on massive end devices (ie, clients). Due to the limited storage capacity and high …