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Found 5 papers, 2 papers with code
DEPHN: Different Expression Parallel Heterogeneous Network using virtual gradient optimization for Multi-task Learning
In view of the model's differentiating ability for different task information flows, DEPHN uses feature explicit mapping and virtual gradient coefficient for expert gating during the training process, and adaptively adjusts the learning intensity of the gated unit by considering the difference of gating values and task correlation.
FaFCNN: A General Disease Classification Framework Based on Feature Fusion Neural Networks
There are two fundamental problems in applying deep learning/machine learning methods to disease classification tasks, one is the insufficient number and poor quality of training samples; another one is how to effectively fuse multiple source features and thus train robust classification models.
DADIN: Domain Adversarial Deep Interest Network for Cross Domain Recommender Systems
Click-Through Rate (CTR) prediction is one of the main tasks of the recommendation system, which is conducted by a user for different items to give the recommendation results.
MIntRec: A New Dataset for Multimodal Intent Recognition
This paper introduces a novel dataset for multimodal intent recognition (MIntRec) to address this issue.
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Multimodal Intent Recognition
on MIntRec
Learning Discriminative Representations and Decision Boundaries for Open Intent Detection
To address these issues, this paper presents an original framework called DA-ADB, which successively learns distance-aware intent representations and adaptive decision boundaries for open intent detection.
