Bokun Wang

Publication Activity (10 Years)

Years Active: 2017-2024
Publications (10 Years): 26

Top Topics

Optimization Methods

Top Venues

J. Mach. Learn. Res.

IEEE Trans. Cybern.

Publications

Bokun Wang, Axel Berg, Durmus Alp Emre Acar, Chuteng Zhou
Towards Federated Learning with On-device Training and Communication in 8-bit Floating Point. CoRR (2024)
Haoran Liu, Bokun Wang, Jianling Wang, Xiangjue Dong, Tianbao Yang, James Caverlee
Everything Perturbed All at Once: Enabling Differentiable Graph Attacks. WWW (Companion Volume) (2024)
Dixian Zhu, Bokun Wang, Zhi Chen, Yaxing Wang, Milan Sonka, Xiaodong Wu, Tianbao Yang
Provable Multi-instance Deep AUC Maximization with Stochastic Pooling. CoRR (2023)
Haoran Liu, Bokun Wang, Jianling Wang, Xiangjue Dong, Tianbao Yang, James Caverlee
Everything Perturbed All at Once: Enabling Differentiable Graph Attacks. CoRR (2023)
Bokun Wang, Zhuoning Yuan, Yiming Ying, Tianbao Yang
Memory-Based Optimization Methods for Model-Agnostic Meta-Learning and Personalized Federated Learning. J. Mach. Learn. Res. 24 (2023)
Dixian Zhu, Bokun Wang, Zhi Chen, Yaxing Wang, Milan Sonka, Xiaodong Wu, Tianbao Yang
Provable Multi-instance Deep AUC Maximization with Stochastic Pooling. ICML (2023)
Bokun Wang, Tianbao Yang
ALEXR: Optimal Single-Loop Algorithms for Convex Finite-Sum Coupled Compositional Stochastic Optimization. CoRR (2023)
Bokun Wang, Caiqian Yang
Video Anomaly Detection Based on Convolutional Recurrent AutoEncoder. Sensors 22 (12) (2022)
Haiyang Yu, Limei Wang, Bokun Wang, Meng Liu, Tianbao Yang, Shuiwang Ji
GraphFM: Improving Large-Scale GNN Training via Feature Momentum. ICML (2022)
Wei Jiang, Bokun Wang, Yibo Wang, Lijun Zhang, Tianbao Yang
Optimal Algorithms for Stochastic Multi-Level Compositional Optimization. CoRR (2022)
Bokun Wang, Tianbao Yang
Finite-Sum Compositional Stochastic Optimization: Theory and Applications. CoRR (2022)
Haiyang Yu, Limei Wang, Bokun Wang, Meng Liu, Tianbao Yang, Shuiwang Ji
GraphFM: Improving Large-Scale GNN Training via Feature Momentum. CoRR (2022)
Bokun Wang, Mher Safaryan, Peter Richtárik
Theoretically Better and Numerically Faster Distributed Optimization with Smoothness-Aware Quantization Techniques. NeurIPS (2022)
Dixian Zhu, Gang Li, Bokun Wang, Xiaodong Wu, Tianbao Yang
When AUC meets DRO: Optimizing Partial AUC for Deep Learning with Non-Convex Convergence Guarantee. CoRR (2022)
Konstantin Mishchenko, Bokun Wang, Dmitry Kovalev, Peter Richtárik
IntSGD: Adaptive Floatless Compression of Stochastic Gradients. ICLR (2022)
Bokun Wang, Tianbao Yang
Finite-Sum Coupled Compositional Stochastic Optimization: Theory and Applications. ICML (2022)
Bokun Wang, Shiqian Ma, Lingzhou Xue
Riemannian Stochastic Proximal Gradient Methods for Nonsmooth Optimization over the Stiefel Manifold. J. Mach. Learn. Res. 23 (2022)
Dixian Zhu, Gang Li, Bokun Wang, Xiaodong Wu, Tianbao Yang
When AUC meets DRO: Optimizing Partial AUC for Deep Learning with Non-Convex Convergence Guarantee. ICML (2022)
Wei Jiang, Bokun Wang, Yibo Wang, Lijun Zhang, Tianbao Yang
Optimal Algorithms for Stochastic Multi-Level Compositional Optimization. ICML (2022)
Konstantin Mishchenko, Bokun Wang, Dmitry Kovalev, Peter Richtárik
IntSGD: Floatless Compression of Stochastic Gradients. CoRR (2021)
Bokun Wang, Mher Safaryan, Peter Richtárik
Smoothness-Aware Quantization Techniques. CoRR (2021)
Bokun Wang, Zhuoning Yuan, Yiming Ying, Tianbao Yang
Memory-based Optimization Methods for Model-Agnostic Meta-Learning. CoRR (2021)
Shiyuan He, Bokun Wang, Zheng Wang, Yang Yang, Fumin Shen, Zi Huang, Heng Tao Shen
Bidirectional Discrete Matrix Factorization Hashing for Image Search. IEEE Trans. Cybern. 50 (9) (2020)
Bokun Wang, Shiqian Ma, Lingzhou Xue
Riemannian Stochastic Proximal Gradient Methods for Nonsmooth Optimization over the Stiefel Manifold. CoRR (2020)
Bokun Wang, Ian Davidson
Towards Fair Deep Clustering With Multi-State Protected Variables. CoRR (2019)
Bokun Wang, Yang Yang, Xing Xu, Alan Hanjalic, Heng Tao Shen
Adversarial Cross-Modal Retrieval. ACM Multimedia (2017)