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20202025
most citedDataset Distillation via Factorization

59 citations · 115 across the 13 of their papers we have counts for

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Showing cs.LGShow all

6 papers · 1 filter

cs.LG2025

GraphBridge: Towards Arbitrary Transfer Learning in GNNs

Li Ju, Xingyi Yang, Qi Li +1

Graph neural networks (GNNs) are conventionally trained on a per-domain, per-task basis. It creates a significant barrier in transferring the acquired knowledge to different, heter…

cs.LG202417 cited

Kolmogorov-Arnold Transformer

Xingyi Yang, Xinchao Wang

Transformers stand as the cornerstone of mordern deep learning. Traditionally, these models rely on multi-layer perceptron (MLP) layers to mix the information between channels. In…

cs.LG20232 cited

Distribution Shift Inversion for Out-of-Distribution Prediction

Runpeng Yu, Songhua Liu, Xingyi Yang +1

Machine learning society has witnessed the emergence of a myriad of Out-of-Distribution (OoD) algorithms, which address the distribution shift between the training and the testing…

cs.LG20209 cited

DSRNA: Differentiable Search of Robust Neural Architectures

Ramtin Hosseini, Xingyi Yang, Pengtao Xie

In deep learning applications, the architectures of deep neural networks are crucial in achieving high accuracy. Many methods have been proposed to search for high-performance neur…

cs.LG2020

Stochastic Gradient Variance Reduction by Solving a Filtering Problem

Xingyi Yang

Deep neural networks (DNN) are typically optimized using stochastic gradient descent (SGD). However, the estimation of the gradient using stochastic samples tends to be noisy and u…

cs.LG2020

COVID-CT-Dataset: A CT Scan Dataset about COVID-19

Xingyi Yang, Xuehai He, Jinyu Zhao +3

During the outbreak time of COVID-19, computed tomography (CT) is a useful manner for diagnosing COVID-19 patients. Due to privacy issues, publicly available COVID-19 CT datasets a…