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Found 14 papers, 1 papers with code
AskMe: Joint Individual-level and Community-level Behavior Interaction for Question Recommendation
On the one hand, we model the rich correlations between the users' diverse behaviors (e. g., answer, follow, vote) to obtain the individual-level behavior interaction.
Multiway sparse distance weighted discrimination
We conducted extensive simulation studies, showing that our model is robust to the degree of sparsity and improves classification accuracy when the data have multiway structure.
DeepExpress: Heterogeneous and Coupled Sequence Modeling for Express Delivery Prediction
To address these issues, we propose DeepExpress - a deep-learning based express delivery sequence prediction model, which extends the classic seq2seq framework to learning complex coupling between sequence and features.
TL-SDD: A Transfer Learning-Based Method for Surface Defect Detection with Few Samples
To solve the imbalanced distribution problem, in this paper we propose TL-SDD: a novel Transfer Learning-based method for Surface Defect Detection.
AdaSpring: Context-adaptive and Runtime-evolutionary Deep Model Compression for Mobile Applications
There are many deep learning (e. g., DNN) powered mobile and wearable applications today continuously and unobtrusively sensing the ambient surroundings to enhance all aspects of human lives.
Towards information-rich, logical text generation with knowledge-enhanced neural models
Text generation system has made massive promising progress contributed by deep learning techniques and has been widely applied in our life.
Deep Learning for Sensor-based Human Activity Recognition: Overview, Challenges and Opportunities
In this study, we present a survey of the state-of-the-art deep learning methods for sensor-based human activity recognition.
The Future of Misinformation Detection: New Perspectives and Trends
We first give a brief review of the literature history of MID, based on which we present several new research challenges and techniques of it, including early detection, detection by multimodal data fusion, and explanatory detection.
Conditional Text Generation for Harmonious Human-Machine Interaction
In recent years, with the development of deep learning, text generation technology has undergone great changes and provided many kinds of services for human beings, such as restaurant reservation and daily communication.
From Crowdsourcing to Crowdmining: Using Implicit Human Intelligence for Better Understanding of Crowdsourced Data
A generic model for CrowdMining is further proposed based on a set of existing studies.
Learning Cross-Domain Representation with Multi-Graph Neural Network
In fact, user's behaviors from different domains regarding the same items are usually relevant.
Multi-agent Attentional Activity Recognition
And the multiple agents in the proposed model represent activities with collective motions across body parts by independently selecting modalities associated with single motions.
AI-Powered Text Generation for Harmonious Human-Machine Interaction: Current State and Future Directions
In the last two decades, the landscape of text generation has undergone tremendous changes and is being reshaped by the success of deep learning.
Smart City Development with Urban Transfer Learning
To address this problem, transfer learning can be leveraged to accelerate the smart city development, which we term the urban transfer learning paradigm.