Shaogao Lv

Publication Activity (10 Years)

Years Active: 2010-2024
Publications (10 Years): 20

Top Topics

Distributed Learning

Generalization Bounds

High Dimensional

Top Venues

J. Mach. Learn. Res.

Pattern Recognit.

Publications

Xingcai Zhou, Guang Yang, Le Chang, Shaogao Lv
Efficient Byzantine-robust distributed inference with regularization: A trade-off between compression and adversary. Inf. Sci. 678 (2024)
Shaogao Lv, Gang Wen, Shiyu Liu, Linsen Wei, Ming Li
Robust Graph Structure Learning with the Alignment of Features and Adjacency Matrix. CoRR (2023)
Shiyu Liu, Linsen Wei, Shaogao Lv, Zenglin Xu
Quantized SGD in Federated Learning: Communication, Optimization and Generalization. ICONIP (9) (2023)
Shiyu Liu, Shaogao Lv, Dun Zeng, Zenglin Xu, Hui Wang, Yue Yu
Personalized Federated Learning via Amortized Bayesian Meta-Learning. CoRR (2023)
Shiyu Liu, Linsen Wei, Shaogao Lv, Ming Li
Stability and Generalization of lp-Regularized Stochastic Learning for GCN. IJCAI (2023)
Xingcai Zhou, Le Chang, Pengfei Xu, Shaogao Lv
Communication-efficient and Byzantine-robust distributed learning with statistical guarantee. Pattern Recognit. 137 (2023)
Shaogao Lv, Xin He, Junhui Wang
Kernel-based estimation for partially functional linear model: Minimax rates and randomized sketches. J. Mach. Learn. Res. 24 (2023)
Shiyu Liu, Linsen Wei, Shaogao Lv, Ming Li
-Regularized Stochastic Learning for GCN. CoRR (2023)
Shaogao Lv, Linsen Wei, Qian Zhang, Bin Liu, Zenglin Xu
Improved Inference for Imputation-Based Semisupervised Learning Under Misspecified Setting. IEEE Trans. Neural Networks Learn. Syst. 33 (11) (2022)
Shaogao Lv, Heng Lian
Debiased Distributed Learning for Sparse Partial Linear Models in High Dimensions. J. Mach. Learn. Res. 23 (2022)
Shaogao Lv, Junhui Wang, Jiankun Liu, Yong Liu
Improved Learning Rates of a Functional Lasso-type SVM with Sparse Multi-Kernel Representation. NeurIPS (2021)
Xingcai Zhou, Le Chang, Pengfei Xu, Shaogao Lv
Communication-efficient Byzantine-robust distributed learning with statistical guarantee. CoRR (2021)
Jia Cai, Zhilong Xiong, Shaogao Lv
SStaGCN: Simplified stacking based graph convolutional networks. CoRR (2021)
Shaogao Lv
Generalization bounds for graph convolutional neural networks via Rademacher complexity. CoRR (2021)
Shaogao Lv, Zengyan Fan, Heng Lian, Taiji Suzuki, Kenji Fukumizu
A reproducing kernel Hilbert space approach to high dimensional partially varying coefficient model. Comput. Stat. Data Anal. 152 (2020)
Shaogao Lv, Yongchao Hou, Hongwei Zhou
Financial Market Directional Forecasting With Stacked Denoising Autoencoder. CoRR (2019)
Shaogao Lv, Mengying You, Huazhen Lin, Heng Lian, Jian Huang
On the sign consistency of the Lasso for the high-dimensional Cox model. J. Multivar. Anal. 167 (2018)
Xin He, Junhui Wang, Shaogao Lv
Scalable kernel-based variable selection with sparsistency. CoRR (2018)
Guo Niu, Zhengming Ma, Shaogao Lv
Ensemble Multiple-Kernel Based Manifold Regularization. Neural Process. Lett. 45 (2) (2017)
Lei Yang, Shaogao Lv, Junhui Wang
Model-free Variable Selection in Reproducing Kernel Hilbert Space. J. Mach. Learn. Res. 17 (2016)
Shaogao Lv, Fanyin Zhou
-type multiple kernel learning under general conditions. Inf. Sci. 294 (2015)
Shaogao Lv, Lei Shi
Learning theory viewpoint of approximation by positive linear operators. Comput. Math. Appl. 60 (12) (2010)