Vahidian, Saeed

11 publications

ICLR 2025 Group Distributionally Robust Dataset Distillation with Risk Minimization Saeed Vahidian, Mingyu Wang, Jianyang Gu, Vyacheslav Kungurtsev, Wei Jiang, Yiran Chen

CVPR 2024 Efficient Dataset Distillation via Minimax Diffusion Jianyang Gu, Saeed Vahidian, Vyacheslav Kungurtsev, Haonan Wang, Wei Jiang, Yang You, Yiran Chen

CVPRW 2024 Exploring the Impact of Dataset Bias on Dataset Distillation Yao Lu, Jianyang Gu, Xuguang Chen, Saeed Vahidian, Qi Xuan

ECCV 2024 Unlocking the Potential of Federated Learning: The Symphony of Dataset Distillation via Deep Generative Latents Yuqi Jia, Saeed Vahidian, Jingwei Sun, Jianyi Zhang, Vyacheslav Kungurtsev, Neil Zhenqiang Gong, Yiran Chen

AAAI 2023 Efficient Distribution Similarity Identification in Clustered Federated Learning via Principal Angles Between Client Data Subspaces Saeed Vahidian, Mahdi Morafah, Weijia Wang, Vyacheslav Kungurtsev, Chen Chen, Mubarak Shah, Bill Lin

NeurIPSW 2023 Towards Building the FederatedGPT: Federated Instruction Tuning Jianyi Zhang, Saeed Vahidian, Martin Kuo, Chunyuan Li, Ruiyi Zhang, Tong Yu, Guoyin Wang, Yiran Chen

ICCV 2023 When Do Curricula Work in Federated Learning? Saeed Vahidian, Sreevatsank Kadaveru, Woonjoon Baek, Weijia Wang, Vyacheslav Kungurtsev, Chen Chen, Mubarak Shah, Bill Lin

NeurIPSW 2022 FLIS: Clustered Federated Learning via Inference Similarity for Non-IID Data Distribution Saeed Vahidian, Mahdi Morafah, Weijia Wang, Bill Lin

NeurIPSW 2022 Rethinking Data Heterogeneity in Federated Learning: Introducing a New Notion and Standard Benchmarks Saeed Vahidian, Mahdi Morafah, Chen Chen, Mubarak Shah, Bill Lin

ICLR 2021 Unsupervised Meta-Learning Through Latent-Space Interpolation in Generative Models Siavash Khodadadeh, Sharare Zehtabian, Saeed Vahidian, Weijia Wang, Bill Lin, Ladislau Boloni

UAI 2020 Coresets for Estimating Means and Mean Square Error with Limited Greedy Samples Saeed Vahidian, Baharan Mirzasoleiman, Alexander Cloninger