Adversarial Cross-Modal Retrieval. - Bokun Wang; Yang Yang 002; Xing Xu 001; Alan Hanjalic; Heng Tao Shen (ACM Multimedia, 2017)

Towards Fair Deep Clustering With Multi-State Protected Variables. - Bokun Wang; Ian Davidson (CoRR, 2019)

Bidirectional Discrete Matrix Factorization Hashing for Image Search. - Shiyuan He; Bokun Wang; Zheng Wang 044; Yang Yang 002; Fumin Shen; Zi Huang; Heng Tao Shen (IEEE Trans. Cybern., 2020)

IntSGD: Floatless Compression of Stochastic Gradients. - Konstantin Mishchenko; Bokun Wang; Dmitry Kovalev; Peter Richtárik (CoRR, 2021)

Smoothness-Aware Quantization Techniques. - Bokun Wang; Mher Safaryan; Peter Richtárik (CoRR, 2021)

Memory-based Optimization Methods for Model-Agnostic Meta-Learning. - Bokun Wang; Zhuoning Yuan; Yiming Ying; Tianbao Yang (CoRR, 2021)

IntSGD: Adaptive Floatless Compression of Stochastic Gradients. - Konstantin Mishchenko; Bokun Wang; Dmitry Kovalev; Peter Richtárik (ICLR, 2022)

Optimal Algorithms for Stochastic Multi-Level Compositional Optimization. - Wei Jiang 029; Bokun Wang; Yibo Wang 005; Lijun Zhang 005; Tianbao Yang (ICML, 2022)

Finite-Sum Coupled Compositional Stochastic Optimization: Theory and Applications. - Bokun Wang; Tianbao Yang (ICML, 2022)

GraphFM: Improving Large-Scale GNN Training via Feature Momentum. - Haiyang Yu 005; Limei Wang; Bokun Wang; Meng Liu 015; Tianbao Yang; Shuiwang Ji (ICML, 2022)

When AUC meets DRO: Optimizing Partial AUC for Deep Learning with Non-Convex Convergence Guarantee. - Dixian Zhu; Gang Li; Bokun Wang; Xiaodong Wu; Tianbao Yang (ICML, 2022)

Theoretically Better and Numerically Faster Distributed Optimization with Smoothness-Aware Quantization Techniques. - Bokun Wang; Mher Safaryan; Peter Richtárik (NeurIPS, 2022)

Finite-Sum Compositional Stochastic Optimization: Theory and Applications. - Bokun Wang; Tianbao Yang (CoRR, 2022)

Riemannian Stochastic Proximal Gradient Methods for Nonsmooth Optimization over the Stiefel Manifold. - Bokun Wang; Shiqian Ma; Lingzhou Xue (J. Mach. Learn. Res., 2022)

Video Anomaly Detection Based on Convolutional Recurrent AutoEncoder. - Bokun Wang; Caiqian Yang (Sensors, 2022)

Provable Multi-instance Deep AUC Maximization with Stochastic Pooling. - Dixian Zhu; Bokun Wang; Zhi Chen 025; Yaxing Wang; Milan Sonka; Xiaodong Wu 001; Tianbao Yang (ICML, 2023)

ALEXR: Optimal Single-Loop Algorithms for Convex Finite-Sum Coupled Compositional Stochastic Optimization. - Bokun Wang; Tianbao Yang (CoRR, 2023)

Memory-Based Optimization Methods for Model-Agnostic Meta-Learning and Personalized Federated Learning. - Bokun Wang; Zhuoning Yuan; Yiming Ying; Tianbao Yang (J. Mach. Learn. Res., 2023)

Everything Perturbed All at Once: Enabling Differentiable Graph Attacks. - Haoran Liu; Bokun Wang; Jianling Wang; Xiangjue Dong; Tianbao Yang; James Caverlee (WWW (Companion Volume), 2024)

Towards Federated Learning with On-device Training and Communication in 8-bit Floating Point. - Bokun Wang; Axel Berg; Durmus Alp Emre Acar; Chuteng Zhou (CoRR, 2024)

Toward enhancing concrete crack segmentation accuracy under complex scenarios: a novel modified U-Net network. - Feng Qu; Bokun Wang; Qing Zhu; Fu Xu; Yaojing Chen; Caiqian Yang (Multim. Tools Appl., 2024)

On Discriminative Probabilistic Modeling for Self-Supervised Representation Learning. - Bokun Wang; Yunwen Lei; Yiming Ying; Tianbao Yang (ICLR, 2025)

Discovering Global False Negatives On the Fly for Self-supervised Contrastive Learning. - Vicente Balmaseda; Bokun Wang; Ching-Long Lin; Tianbao Yang (CoRR, 2025)

Stochastic Primal-Dual Double Block-Coordinate for Two-way Partial AUC Maximization. - Linli Zhou; Bokun Wang; My T. Thai; Tianbao Yang (CoRR, 2025)

Stochastic Momentum Methods for Non-smooth Non-Convex Finite-Sum Coupled Compositional Optimization. - Xingyu Chen; Bokun Wang; Min Yang 007; Quanqi Hu; Qihang Lin; Tianbao Yang (CoRR, 2025)