A Survey of Trustworthy Federated Learning: Issues, Solutions, and Challenges
Trustworthy artificial intelligence (TAI) has proven invaluable in curbing potential negative repercussions tied to AI applications. Within the TAI spectrum, federated learning (FL) emerges as a promising solution to safeguard personal information in ...
Federated Learning Survey: A Multi-Level Taxonomy of Aggregation Techniques, Experimental Insights, and Future Frontiers
The emerging integration of Internet of Things (IoT) and AI has unlocked numerous opportunities for innovation across diverse industries. However, growing privacy concerns and data isolation issues have inhibited this promising advancement. Unfortunately, ...
Surveying More Than Two Decades of Music Information Retrieval Research on Playlists
In this article, we present an extensive survey of music information retrieval (MIR) research into music playlists. Our survey spans more than 20 years, and includes around 300 papers about playlists, with over 70 supporting sources. It is the first ...
Efficiently Gluing Pre-Trained Language and Vision Models for Image Captioning
Vision-and-language pre-training models have achieved impressive performance for image captioning. But most of them are trained with millions of paired image-text data and require huge memory and computing overhead. To alleviate this, we try to stand on ...
Intermediary-Generated Bridge Network for RGB-D Cross-Modal Re-Identification
RGB-D cross-modal person re-identification (re-id) targets at retrieving the person of interest across RGB and depth image modalities. To cope with the modal discrepancy, some existing methods generate an auxiliary mode with either inherent properties of ...
Toward Ubiquitous Interaction-Attentive and Extreme-Aware Crowd Activity Level Prediction
Accurate prediction of citywide crowd activity levels (CALs), i.e., the numbers of participants of citywide crowd activities under different venue categories at certain time and locations, is essential for the city management, the personal service ...
A Unified Framework for Analyzing Textual Context and Intent in Social Media
In the realm of natural language processing, tasks like emotion recognition, irony detection, hate speech detection, offensive language identification, and stance detection are pivotal for understanding user-generated content. While several task-specific ...
Relation Constrained Capsule Graph Neural Networks for Non-Rigid Shape Correspondence
Non-rigid 3D shape correspondence aims to establish dense correspondences between two non-rigidly deformed 3D shapes. However, the variability and symmetry of non-rigid shapes usually lead to mismatches due to shape deformation, topological changes, or ...
Efficient Federated Learning Using Dynamic Update and Adaptive Pruning with Momentum on Shared Server Data
Despite achieving remarkable performance, Federated Learning (FL) encounters two important problems, i.e., low training efficiency and limited computational resources. In this article, we propose a new FL framework, i.e., FedDUMAP, with three original ...
KGDA: A Knowledge Graph Driven Decomposition Approach for Cellular Traffic Prediction
- Jiahui Gong,
- Tong Li,
- Huandong Wang,
- Yu Liu,
- Xing Wang,
- Zhendong Wang,
- Chao Deng,
- Junlan Feng,
- Depeng Jin,
- Yong Li
Understanding and accurately predicting cellular traffic data is vital for communication operators and device users, as it facilitates efficient resource allocation and ensures superior service quality. However, large-scale cellular traffic data ...
RCCNet: A Spatial-Temporal Neural Network Model for Logistics Delivery Timely Rate Prediction
In logistics service, the delivery timely rate is a key experience indicator, which is highly essential to the competitive advantage of express companies. Prediction on it enables intervention on couriers with low predicted results in advance, thus ...
Adapting to My User, Engaging with My Robot: An Adaptive Affective Architecture for a Social Assistive Robot
- Marcos Maroto-Gómez,
- Matthew Lewis,
- Álvaro Castro-González,
- María Malfaz,
- Miguel Ángel Salichs,
- Lola Cañamero
Affective feedback from social robots is a useful technique for communicating to people whether they are interacting “well” with the robot or not. However, some users, such as people with physical or cognitive difficulties, may not be able to interact in ...
Quantum Informative Analysis in Smart Power Distribution
Advancements in the Internet of Things (IoT) paradigm have greatly improved the quality of services in the electricity industry through the integration of smart energy distribution and dependable electric devices. Conspicuously, the current research ...