Learning sparse models of diffusive graph signals. - Shuyu Dong; Dorina Thanou; Pierre-Antoine Absil; Pascal Frossard (ESANN, 2017)

Preconditioned conjugate gradient algorithms for graph regularized matrix completion. - Shuyu Dong; Pierre-Antoine Absil; Kyle A. Gallivan (ESANN, 2019)

Alternating minimization algorithms for graph regularized tensor completion. - Yu Guan; Shuyu Dong; Pierre-Antoine Absil; François Glineur (CoRR, 2020)

Low-rank matrix and tensor completion using graph-based regularization. - Shuyu Dong (2021)

From Graphs to DAGs: A Low-Complexity Model and a Scalable Algorithm. - Shuyu Dong; Michèle Sebag (ECML/PKDD (5), 2022)

On the analysis of optimization with fixed-rank matrices: a quotient geometric view. - Shuyu Dong; Bin Gao 007; Wen Huang 001; Kyle A. Gallivan (CoRR, 2022)

High-Dimensional Causal Discovery: Learning from Inverse Covariance via Independence-based Decomposition. - Shuyu Dong; Kento Uemura; Akito Fujii; Shuang Chang; Yusuke Koyanagi; Koji Maruhashi; Michèle Sebag (CoRR, 2022)

New Riemannian Preconditioned Algorithms for Tensor Completion via Polyadic Decomposition. - Shuyu Dong; Bin Gao 007; Yu Guan; François Glineur (SIAM J. Matrix Anal. Appl., 2022)

DCDILP: a distributed learning method for large-scale causal structure learning. - Shuyu Dong; Michèle Sebag; Kento Uemura; Akito Fujii; Shuang Chang; Yusuke Koyanagi; Koji Maruhashi (CoRR, 2024)

DCILP: A Distributed Approach for Large-Scale Causal Structure Learning. - Shuyu Dong; Michèle Sebag; Kento Uemura; Akito Fujii; Shuang Chang; Yusuke Koyanagi; Koji Maruhashi (AAAI, 2025)

Learning Measurement Models via Subspace Identification and Clustering. - Shuyu Dong; Arthur Tenenhaus; Laurent Le Brusquet; Mohammed Nabil El Korso (SSP, 2025)

Beyond Freezing: Sparse Tuning Enhances Plasticity in Continual Learning with Pre-Trained Models. - Huan Zhang; Fan Lyu; Shuyu Dong; Shenghua Fan; Yujin Zheng; Dingwen Wang (CoRR, 2025)