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09/11/2023
Fully-Connected Spatial-Temporal Graph for Multivariate Time Series Data
Multivariate Time-Series (MTS) data is crucial in various application fi...
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09/11/2023
Graph Contextual Contrasting for Multivariate Time Series Classification
Contrastive learning, as a self-supervised learning paradigm, becomes po...
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08/18/2023
Unlimited Knowledge Distillation for Action Recognition in the Dark
Dark videos often lose essential information, which causes the knowledge...
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07/30/2023
Shuffled Differentially Private Federated Learning for Time Series Data Analytics
Trustworthy federated learning aims to achieve optimal performance while...
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07/14/2023
Source-Free Domain Adaptation with Temporal Imputation for Time Series Data
Source-free domain adaptation (SFDA) aims to adapt a pretrained model fr...
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07/07/2023
Distilling Universal and Joint Knowledge for Cross-Domain Model Compression on Time Series Data
For many real-world time series tasks, the computational complexity of p...
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04/10/2023
ECG-CL: A Comprehensive Electrocardiogram Interpretation Method Based on Continual Learning
Electrocardiogram (ECG) monitoring is one of the most powerful technique...
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03/18/2023
Confidence Attention and Generalization Enhanced Distillation for Continuous Video Domain Adaptation
Continuous Video Domain Adaptation (CVDA) is a scenario where a source m...
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03/18/2023
Augmenting and Aligning Snippets for Few-Shot Video Domain Adaptation
For video models to be transferred and applied seamlessly across video t...
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02/27/2023
Learning Large Neighborhood Search for Vehicle Routing in Airport Ground Handling
Dispatching vehicle fleets to serve flights is a key task in airport gro...
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02/13/2023
Label-efficient Time Series Representation Learning: A Review
The scarcity of labeled data is one of the main challenges of applying d...
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12/03/2022
CoTMix: Contrastive Domain Adaptation for Time-Series via Temporal Mixup
Unsupervised Domain Adaptation (UDA) has emerged as a powerful solution ...
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11/17/2022
Video Unsupervised Domain Adaptation with Deep Learning: A Comprehensive Survey
Video analysis tasks such as action recognition have received increasing...
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08/13/2022
Self-supervised Contrastive Representation Learning for Semi-supervised Time-Series Classification
Learning time-series representations when only unlabeled data or few lab...
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08/10/2022
EXTERN: Leveraging Endo-Temporal Regularization for Black-box Video Domain Adaptation
To enable video models to be applied seamlessly across video tasks in di...
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05/08/2022
A Survey on AI Sustainability: Emerging Trends on Learning Algorithms and Research Challenges
Artificial Intelligence (AI) is a fast-growing research and development ...
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03/15/2022
ADATIME: A Benchmarking Suite for Domain Adaptation on Time Series Data
Unsupervised domain adaptation methods aim to generalize well on unlabel...
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03/09/2022
Learning Temporal Consistency for Source-Free Video Domain Adaptation
Video-based Unsupervised Domain Adaptation (VUDA) methods improve the ro...
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02/19/2022
Going Deeper into Recognizing Actions in Dark Environments: A Comprehensive Benchmark Study
While action recognition (AR) has gained large improvements with the int...
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11/29/2021
Self-supervised Autoregressive Domain Adaptation for Time Series Data
Unsupervised domain adaptation (UDA) has successfully addressed the doma...
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10/06/2021
Learning to Iteratively Solve Routing Problems with Dual-Aspect Collaborative Transformer
Recently, Transformer has become a prevailing deep architecture for solv...
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09/21/2021
Multi-Source Video Domain Adaptation with Temporal Attentive Moment Alignment
Multi-Source Domain Adaptation (MSDA) is a more practical domain adaptat...
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07/20/2021
Attention-Guided NIR Image Colorization via Adaptive Fusion of Semantic and Texture Clues
Near infrared (NIR) imaging has been widely applied in low-light imaging...
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07/11/2021
Partial Video Domain Adaptation with Partial Adversarial Temporal Attentive Network
Partial Domain Adaptation (PDA) is a practical and general domain adapta...
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07/09/2021
Adversarial Domain Adaptation with Self-Training for EEG-based Sleep Stage Classification
Sleep staging is of great importance in the diagnosis and treatment of s...
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06/26/2021
Time-Series Representation Learning via Temporal and Contextual Contrasting
Learning decent representations from unlabeled time-series data with tem...
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01/18/2021
Deep Inertial Odometry with Accurate IMU Preintegration
Inertial Measurement Units (IMUs) are interceptive modalities that provi...
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07/20/2020
Attention Sequence to Sequence Model for Machine Remaining Useful Life Prediction
Accurate estimation of remaining useful life (RUL) of industrial equipme...
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01/21/2019