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09/08/2023
UER: A Heuristic Bias Addressing Approach for Online Continual Learning
Online continual learning aims to continuously train neural networks fro...
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04/10/2023
PCR: Proxy-based Contrastive Replay for Online Class-Incremental Continual Learning
Online class-incremental continual learning is a specific task of contin...
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03/03/2022
MetaDT: Meta Decision Tree for Interpretable Few-Shot Learning
Few-Shot Learning (FSL) is a challenging task, which aims to recognize n...
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10/09/2021
SGMNet: Scene Graph Matching Network for Few-Shot Remote Sensing Scene Classification
Few-Shot Remote Sensing Scene Classification (FSRSSC) is an important ta...
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10/03/2021
RAP-Net: Region Attention Predictive Network for Precipitation Nowcasting
Natural disasters caused by heavy rainfall often cost huge loss of life ...
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08/11/2021
Prototype Completion for Few-Shot Learning
Few-shot learning aims to recognize novel classes with few examples. Pre...
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03/26/2021
MetaNODE: Prototype Optimization as a Neural ODE for Few-Shot Learning
Few-Shot Learning (FSL) is a challenging task, i.e., how to recognize no...
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09/10/2020
Prototype Completion with Primitive Knowledge for Few-Shot Learning
Few-shot learning is a challenging task, which aims to learn a classifie...
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08/06/2020
Multi-source Heterogeneous Domain Adaptation with Conditional Weighting Adversarial Network
Heterogeneous domain adaptation (HDA) tackles the learning of cross-doma...
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07/05/2020
MetaConcept: Learn to Abstract via Concept Graph for Weakly-Supervised Few-Shot Learning
Meta-learning has been proved to be an effective framework to address fe...
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04/25/2020
Inter-sequence Enhanced Framework for Personalized Sequential Recommendation
Modeling the sequential correlation of users' historical interactions is...
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08/28/2019
Heterogeneous Domain Adaptation via Soft Transfer Network
Heterogeneous domain adaptation (HDA) aims to facilitate the learning ta...
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10/29/2018
Deep Reinforcement Learning based Recommendation with Explicit User-Item Interactions Modeling
Recommendation is crucial in both academia and industry, and various tec...
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07/16/2018
An Adjustable Heat Conduction based KNN Approach for Session-based Recommendation
The KNN approach, which is widely used in recommender systems because of...
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04/12/2018
DeepFM: An End-to-End Wide & Deep Learning Framework for CTR Prediction
Learning sophisticated feature interactions behind user behaviors is cri...
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02/23/2018
Novel Approaches to Accelerating the Convergence Rate of Markov Decision Process for Search Result Diversification
Recently, some studies have utilized the Markov Decision Process for div...
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03/13/2017