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08/31/2023
Continual Learning From a Stream of APIs
Continual learning (CL) aims to learn new tasks without forgetting previ...
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07/16/2023
A Comprehensive Survey of Forgetting in Deep Learning Beyond Continual Learning
Forgetting refers to the loss or deterioration of previously acquired in...
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05/28/2023
Learning to Learn from APIs: Black-Box Data-Free Meta-Learning
Data-free meta-learning (DFML) aims to enable efficient learning of new ...
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04/24/2023
Customized Load Profiles Synthesis for Electricity Customers Based on Conditional Diffusion Models
Customers' load profiles are critical resources to support data analytic...
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03/20/2023
Architecture, Dataset and Model-Scale Agnostic Data-free Meta-Learning
The goal of data-free meta-learning is to learn useful prior knowledge f...
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09/03/2022
Meta-Learning with Less Forgetting on Large-Scale Non-Stationary Task Distributions
The paradigm of machine intelligence moves from purely supervised learni...
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07/15/2022
Improving Task-free Continual Learning by Distributionally Robust Memory Evolution
Task-free continual learning (CL) aims to learn a non-stationary data st...
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02/18/2022
Space4HGNN: A Novel, Modularized and Reproducible Platform to Evaluate Heterogeneous Graph Neural Network
Heterogeneous Graph Neural Network (HGNN) has been successfully employed...
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12/28/2021
Uncertainty Detection in EEG Neural Decoding Models
EEG decoding systems based on deep neural networks have been widely used...
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09/29/2021
Meta Learning on a Sequence of Imbalanced Domains with Difficulty Awareness
Recognizing new objects by learning from a few labeled examples in an ev...
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02/07/2021
Meta-Learning with Neural Tangent Kernels
Model Agnostic Meta-Learning (MAML) has emerged as a standard framework ...
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09/20/2020
Repulsive Attention: Rethinking Multi-head Attention as Bayesian Inference
The neural attention mechanism plays an important role in many natural l...
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08/26/2020
A Multitask Deep Learning Approach for User Depression Detection on Sina Weibo
In recent years, due to the mental burden of depression, the number of p...
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05/03/2020
Towards Faithful Neural Table-to-Text Generation with Content-Matching Constraints
Text generation from a knowledge base aims to translate knowledge triple...
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12/21/2019
Learning Diverse Stochastic Human-Action Generators by Learning Smooth Latent Transitions
Human-motion generation is a long-standing challenging task due to the r...
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07/18/2018