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07/31/2023
LaplaceConfidence: a Graph-based Approach for Learning with Noisy Labels
In real-world applications, perfect labels are rarely available, making ...
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04/28/2023
Knowledge-refined Denoising Network for Robust Recommendation
Knowledge graph (KG), which contains rich side information, becomes an e...
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04/27/2023
Towards Explainable Collaborative Filtering with Taste Clusters Learning
Collaborative Filtering (CF) is a widely used and effective technique fo...
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02/13/2023
LDPTrace: Locally Differentially Private Trajectory Synthesis
Trajectory data has the potential to greatly benefit a wide-range of rea...
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10/06/2022
Spatial-Temporal Graph Convolutional Gated Recurrent Network for Traffic Forecasting
As an important part of intelligent transportation systems, traffic fore...
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04/14/2022
Self-Guided Learning to Denoise for Robust Recommendation
The ubiquity of implicit feedback makes them the default choice to build...
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04/11/2022
HAKG: Hierarchy-Aware Knowledge Gated Network for Recommendation
Knowledge graph (KG) plays an increasingly important role to improve the...
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02/08/2022
MetaKG: Meta-learning on Knowledge Graph for Cold-start Recommendation
A knowledge graph (KG) consists of a set of interconnected typed entitie...
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12/17/2021
Deep Spatially and Temporally Aware Similarity Computation for Road Network Constrained Trajectories
Trajectory similarity computation has drawn massive attention, as it is ...
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12/06/2021
Two Wrongs Don't Make a Right: Combating Confirmation Bias in Learning with Label Noise
Noisy labels damage the performance of deep networks. For robust learnin...
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10/13/2021
An Efficient Source Model Selection Framework in Model Databases
With the explosive increase of big data, training a Machine Learning (ML...
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09/09/2021
Generation, augmentation, and alignment: A pseudo-source domain based method for source-free domain adaptation
Conventional unsupervised domain adaptation (UDA) methods need to access...
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08/10/2021
AdaRNN: Adaptive Learning and Forecasting of Time Series
Time series has wide applications in the real world and is known to be d...
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07/10/2021
Semi-Supervised Learning with Multi-Head Co-Training
Co-training, extended from self-training, is one of the frameworks for s...
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06/29/2021
Cross-domain error minimization for unsupervised domain adaptation
Unsupervised domain adaptation aims to transfer knowledge from a labeled...
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03/26/2020
Unsupervised domain adaptation with exploring more statistics and discriminative information
Unsupervised domain adaptation aims at transferring knowledge from the l...
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01/01/2020
Dual Adversarial Domain Adaptation
Unsupervised domain adaptation aims at transferring knowledge from the l...
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12/31/2019
