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Found 9 papers, 2 papers with code
A Survey on Deep Neural Network Partition over Cloud, Edge and End Devices
This paper provides a comprehensive survey on the recent advances and challenges in DNN partition approaches over the cloud, edge, and end devices based on a detailed literature collection.
Scene Style Text Editing
Specifically, QuadNet consists of four parts, namely background inpainting, style encoder, content encoder, and fusion generator.
Who Should I Engage with At What Time? A Missing Event Aware Temporal Graph Neural Network
In real-world applications, events are not always observable, and estimating event time is as important as predicting future events.
A Personalized Utterance Style (PUS) based Dialogue Strategy for Efficient Service Requirement Elicitation
Considering that traditional dialogue system with static slots cannot be directly applied to the SRE task, it is a challenge to design an efficient dialogue strategy to guide users to express their complete and accurate requirements in such a huge potential requirement space.
DySR: A Dynamic Representation Learning and Aligning based Model for Service Bundle Recommendation
The fundamental problem with these studies is that they ignore the evolution of services over time and the representation gap between services and requirements.
Learning Representation over Dynamic Graph using Aggregation-Diffusion Mechanism
However, relying only on aggregation to propagate information in dynamic graphs can result in delays in information propagation and thus affect the performance of the method.
User Intention Recognition and Requirement Elicitation Method for Conversational AI Services
In recent years, chat-bot has become a new type of intelligent terminal to guide users to consume services.
A4 : Evading Learning-based Adblockers
Efforts by online ad publishers to circumvent traditional ad blockers towards regaining fiduciary benefits, have been demonstrably successful.
LTP: A New Active Learning Strategy for CRF-Based Named Entity Recognition
In this paper, we first examine traditional active learning strategies in a specific case of BiLstm-CRF that has widely used in named entity recognition on several typical datasets.
