Shaogao Lv - RankMe

24 papers A* 3Journal 20Unranked 1

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	An accelerated noise-tolerant power method for fair streaming PCA with PAFO learnability. Inf. Sci. Xingcai Zhou, Xiaochen Fan, Shaogao Lv
2024	J	`jnl`	Efficient Byzantine-robust distributed inference with regularization: A trade-off between compression and adversary. Inf. Sci. Xingcai Zhou, Guang Yang, Le Chang, Shaogao Lv
2024	A*	`conf`	Meta-Learning via PAC-Bayesian with Data-Dependent Prior: Generalization Bounds from Local Entropy. IJCAI Shiyu Liu, Wei Shi, Zenglin Xu, Shaogao Lv, Yehong Zhang, Hui Wang
2023	J	`jnl`	Communication-efficient and Byzantine-robust distributed learning with statistical guarantee. Pattern Recognit. Xingcai Zhou, Le Chang, Pengfei Xu, Shaogao Lv
2023	J	`jnl`	Kernel-based estimation for partially functional linear model: Minimax rates and randomized sketches. J. Mach. Learn. Res. Shaogao Lv, Xin He, Junhui Wang
2023	J	`jnl`	Personalized Federated Learning via Amortized Bayesian Meta-Learning. CoRR Shiyu Liu, Shaogao Lv, Dun Zeng, Zenglin Xu, Hui Wang, Yue Yu
2023	—	`conf`	Quantized SGD in Federated Learning: Communication, Optimization and Generalization. ICONIP (9) Shiyu Liu, Linsen Wei, Shaogao Lv, Zenglin Xu
2023	J	`jnl`	Robust Graph Structure Learning with the Alignment of Features and Adjacency Matrix. CoRR Shaogao Lv, Gang Wen, Shiyu Liu, Linsen Wei, Ming Li
2023	A*	`conf`	Stability and Generalization of lp-Regularized Stochastic Learning for GCN. IJCAI Shiyu Liu, Linsen Wei, Shaogao Lv, Ming Li
2023	J	`jnl`	Stability and Generalization of 𝓁 CoRR Shiyu Liu, Linsen Wei, Shaogao Lv, Ming Li
2022	J	`jnl`	Debiased Distributed Learning for Sparse Partial Linear Models in High Dimensions. J. Mach. Learn. Res. Shaogao Lv, Heng Lian
2022	J	`jnl`	Improved Inference for Imputation-Based Semisupervised Learning Under Misspecified Setting. IEEE Trans. Neural Networks Learn. Syst. Shaogao Lv, Linsen Wei, Qian Zhang, Bin Liu, Zenglin Xu
2021	J	`jnl`	Communication-efficient Byzantine-robust distributed learning with statistical guarantee. CoRR Xingcai Zhou, Le Chang, Pengfei Xu, Shaogao Lv
2021	J	`jnl`	Generalization bounds for graph convolutional neural networks via Rademacher complexity. CoRR Shaogao Lv
2021	A*	`conf`	Improved Learning Rates of a Functional Lasso-type SVM with Sparse Multi-Kernel Representation. NeurIPS Shaogao Lv, Junhui Wang, Jiankun Liu, Yong Liu
2021	J	`jnl`	SStaGCN: Simplified stacking based graph convolutional networks. CoRR Jia Cai, Zhilong Xiong, Shaogao Lv
2020	J	`jnl`	A reproducing kernel Hilbert space approach to high dimensional partially varying coefficient model. Comput. Stat. Data Anal. Shaogao Lv, Zengyan Fan, Heng Lian, Taiji Suzuki, Kenji Fukumizu
2019	J	`jnl`	Financial Market Directional Forecasting With Stacked Denoising Autoencoder. CoRR Shaogao Lv, Yongchao Hou, Hongwei Zhou
2018	J	`jnl`	On the sign consistency of the Lasso for the high-dimensional Cox model. J. Multivar. Anal. Shaogao Lv, Mengying You, Huazhen Lin, Heng Lian, Jian Huang
2018	J	`jnl`	Scalable kernel-based variable selection with sparsistency. CoRR Xin He, Junhui Wang, Shaogao Lv
2017	J	`jnl`	Ensemble Multiple-Kernel Based Manifold Regularization. Neural Process. Lett. Guo Niu, Zhengming Ma, Shaogao Lv
2016	J	`jnl`	Model-free Variable Selection in Reproducing Kernel Hilbert Space. J. Mach. Learn. Res. Lei Yang, Shaogao Lv, Junhui Wang
2015	J	`jnl`	Optimal learning rates of l Inf. Sci. Shaogao Lv, Fanyin Zhou
2010	J	`jnl`	Learning theory viewpoint of approximation by positive linear operators. Comput. Math. Appl. Shaogao Lv, Lei Shi