Publications

Statistical Inference on High Dimensional Gaussian Graphical Regression Models.

Published in Biometrics, 2025

Recommended citation: Xuran Meng, Jingfei Zhang and Yi Li, "Statistical Inference on High Dimensional Gaussian Graphical Regression Models." Biometrics, 2025.
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Xuran Meng and Yi Li’s contribution to the Discussion of “On optimal linear prediction” by I. Helland.

Published in Scandinavian Journal of Statistics, 2025

Recommended citation: Xuran Meng and Yi Li, "Xuran Meng and Yi Li’s contribution to the Discussion of “On optimal linear prediction” by I. Helland." Scandinavian Journal of Statistics, 2025.
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Estimation of Out-of-Sample Sharpe Ratio for High Dimensional Portfolio Optimization.

Published in Journal of the American Statistical Association, 2025

Recommended citation: Xuran Meng, Yuan Cao and Weichen Wang, "Estimation of Out-of-Sample Sharpe Ratio for High Dimensional Portfolio Optimization." JASA, 2025.
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Per-Example Gradient Regularization Improves Learning Signals from Noisy Data.

Published in Machine Learning, 2025

Machine Learning

Recommended citation: Xuran Meng, Yuan Cao and Difan Zou, "Per-Example Gradient Regularization Improves Learning Signals from Noisy Data." Machine Learning, 2025.
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Multiple Descent in the Multiple Random Feature Model.

Published in Journal of Machine Learning Research, 2024

Recommended citation: Xuran Meng, Jianfeng Yao and Yuan Cao, "Multiple Descent in the Multiple Random Feature Model." JMLR 25, 2024.
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Impact of classification difficulty on the weight matrices spectra in Deep Learning and application to early-stopping.

Published in Journal of Machine Learning Research, 2023

Recommended citation: Xuran Meng and Jianfeng Yao, "Impact of classification difficulty on the weight matrices spectra in Deep Learning and application to early-stopping." JMLR 24, 2023.
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l1–2 minimisation for compressed sensing with partially known signal support.

Published in Electronics Letters, 2020

Recommended citation: Jing Zhang, Shuguang Zhang and Xuran Meng, "l1–2 minimisation for compressed sensing with partially known signal support." Electronics Letters 56, 2020.
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High frequency algorithm and its back-testing results based on GAN.

Published in JUSTC, 2020

Recommended citation: Xuran Meng, Xiuchun Bi and Shuguang Zhang, "High frequency algorithm and its back-testing results based on GAN." JUSTC 50, 2020.
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A Local Existence Theorem for a Parabolic Blow-Up Inverse Problem.

Published in Pure Mathematics, 2017

Recommended citation: Yu Pan, Xuran Meng and Wuqing Ning, "A Local Existence Theorem for a Parabolic Blow-Up Inverse Problem." Pure Mathematics, 2017.
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Transformer learns optimal variable selection in group-sparse classification.

Published in International Conference on Learning Representations, 2025

Recommended citation: Chenyang Zhang, Xuran Meng and Yuan Cao, "Transformer learns optimal variable selection in group-sparse classification." ICLR, 2025.
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Benign Overfitting in Two-Layer ReLU Convolutional Neural Networks for XOR Data.

Published in International Conference on Machine Learning, 2024

Recommended citation: Xuran Meng, Difan Zou and Yuan Cao, "Benign Overfitting in Two-Layer ReLU Convolutional Neural Networks for XOR Data." ICML, 2024.
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Towards Understanding Feature Learning in Parameter Transfer.

Published in Arxiv, 2025

Submitted to ICLR

Recommended citation: Hua Yuan, Xuran Meng et. al., "Towards Understanding Feature Learning in Parameter Transfer." arxiv: 2509.22056, 2025.
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Temporal Self-Rewarding Language Models: Decoupling Chosen-Rejected via Past-Future.

Published in Arxiv, 2025

Submitted to AAAI

Recommended citation: Yidong Wang et. al., "Temporal Self-Rewarding Language Models: Decoupling Chosen-Rejected via Past-Future." arxiv: 2508.06026, 2025.
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Inferring Outcome Means of Exponential Family Distributions Estimated by Deep Neural Networks.

Published in Arxiv, 2025

Submitted to JASA

Recommended citation: Xuran Meng and Yi Li, "Inferring Outcome Means of Exponential Family Distributions Estimated by Deep Neural Networks." arxiv: 2504.09347, 2025.
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Initialization Matters: On the Benign Overfitting of Two-Layer ReLU CNN with Fully Trainable Layers.

Published in Arxiv, 2024

Submitted to JMLR

Recommended citation: Shuning Shang, Xuran Meng, Yuan Cao and Difan Zou, "Initialization Matters: On the Benign Overfitting of Two-Layer ReLU CNN with Fully Trainable Layers." arxiv: 2410.19139, 2024.
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