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06/18/2023
In-Process Global Interpretation for Graph Learning via Distribution Matching
Graphs neural networks (GNNs) have emerged as a powerful graph learning ...
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02/22/2023
Source-Function Weighted-Transfer Learning for Nonparametric Regression with Seemingly Similar Sources
The homogeneity, or more generally, the similarity between source domain...
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10/02/2022
Spectral Augmentation for Self-Supervised Learning on Graphs
Graph contrastive learning (GCL), as an emerging self-supervised learnin...
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09/30/2022
Metro: Memory-Enhanced Transformer for Retrosynthetic Planning via Reaction Tree
Retrosynthetic planning plays a critical role in drug discovery and orga...
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09/29/2022
How Powerful is Implicit Denoising in Graph Neural Networks
Graph Neural Networks (GNNs), which aggregate features from neighbors, a...
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09/26/2022
Renewable Composite Quantile Method and Algorithm for Nonparametric Models with Streaming Data
We are interested in renewable estimations and algorithms for nonparamet...
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06/10/2022
A Correlation-Ratio Transfer Learning and Variational Stein's Paradox
A basic condition for efficient transfer learning is the similarity betw...
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06/04/2022
Feature screening for multi-response linear models by empirical likelihood
This paper proposes a new feature screening method for the multi-respons...
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05/05/2022
Communication-Efficient Adaptive Federated Learning
Federated learning is a machine learning training paradigm that enables ...
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01/29/2022
Global Bias-Corrected Divide-and-Conquer by Quantile-Matched Composite for General Nonparametric Regressions
The issues of bias-correction and robustness are crucial in the strategy...
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11/01/2021
Communication-Compressed Adaptive Gradient Method for Distributed Nonconvex Optimization
Due to the explosion in the size of the training datasets, distributed l...
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11/01/2021
Graph Structural Attack by Spectral Distance
Graph Convolutional Networks (GCNs) have fueled a surge of interest due ...
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10/31/2021
Graph Embedding with Hierarchical Attentive Membership
The exploitation of graph structures is the key to effectively learning ...
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10/26/2021
Unbiased Graph Embedding with Biased Graph Observations
Graph embedding techniques have been increasingly employed in real-world...
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01/21/2021
A General Framework of Online Updating Variable Selection for Generalized Linear Models with Streaming Datasets
In the research field of big data, one of important issues is how to rec...
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10/30/2020
A pressure-correction and bound-preserving discretization of the phase-field method for variable density two-phase flows
In this paper, we present an efficient numerical algorithm for solving t...
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08/20/2020
Unified Rules of Renewable Weighted Sums for Various Online Updating Estimations
This paper establishes unified frameworks of renewable weighted sums (RW...
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03/03/2020
Optimally estimating the sample mean and standard deviation from the five-number summary
When reporting the results of clinical studies, some researchers may cho...
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12/01/2019
JNET: Learning User Representations via Joint Network Embedding and Topic Embedding
User representation learning is vital to capture diverse user preference...
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11/27/2019
A race-DC in Big Data
The strategy of divide-and-combine (DC) has been widely used in the area...
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04/16/2019
A Global Bias-Correction DC Method for Biased Estimation under Memory Constraint
This paper introduces a global bias-correction divide-and-conquer (GBC-D...
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01/04/2018
How to estimate the sample mean and standard deviation from the five number summary?
In some clinical studies, researchers may report the five number summary...
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11/30/2017