Weak attributes for large-scale image retrieval von Yu, F. X., Rongrong Ji, Ming-Hen Tsai, Guangnan Ye, Shih-Fu Chang

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Active query sensing: Suggesting the best query view for mobile visual search von Ji, Rongrong, Yu, Felix X., Zhang, Tongtao, Chang, Shih-Fu

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Automatic Engineering of Long Prompts von Hsieh, Cho-Jui, Si, Si, Yu, Felix X, Dhillon, Inderjit S

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FedLite: A Scalable Approach for Federated Learning on Resource-constrained Clients von Wang, Jianyu, Qi, Hang, Rawat, Ankit Singh, Reddi, Sashank, Waghmare, Sagar, Yu, Felix X, Joshi, Gauri

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Disentangling Sampling and Labeling Bias for Learning in Large-Output Spaces von Rawat, Ankit Singh, Menon, Aditya Krishna, Jitkrittum, Wittawat, Jayasumana, Sadeep, Yu, Felix X, Reddi, Sashank, Kumar, Sanjiv

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Federated Learning with Only Positive Labels von Yu, Felix X, Rawat, Ankit Singh, Menon, Aditya Krishna, Kumar, Sanjiv

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Pre-training Tasks for Embedding-based Large-scale Retrieval von Chang, Wei-Cheng, Yu, Felix X, Chang, Yin-Wen, Yang, Yiming, Kumar, Sanjiv

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Automatic Engineering of Long Prompts von Cho-Jui Hsieh, Si, Si, Yu, Felix X, Dhillon, Inderjit S

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AdaCliP: Adaptive Clipping for Private SGD von Pichapati, Venkatadheeraj, Suresh, Ananda Theertha, Yu, Felix X, Reddi, Sashank J, Kumar, Sanjiv

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Learning Spread-out Local Feature Descriptors von Zhang, Xu, Yu, Felix X, Kumar, Sanjiv, Chang, Shih-Fu

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FedLite: A Scalable Approach for Federated Learning on Resource-constrained Clients von Wang, Jianyu, Qi, Hang, Ankit Singh Rawat, Reddi, Sashank, Waghmare, Sagar, Yu, Felix X, Joshi, Gauri

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Learning a Compressed Sensing Measurement Matrix via Gradient Unrolling von Wu, Shanshan, Dimakis, Alexandros G, Sanghavi, Sujay, Yu, Felix X, Holtmann-Rice, Daniel, Storcheus, Dmitry, Rostamizadeh, Afshin, Kumar, Sanjiv

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Compact Nonlinear Maps and Circulant Extensions von Yu, Felix X, Kumar, Sanjiv, Rowley, Henry, Chang, Shih-Fu

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A Field Guide to Federated Optimization von Wang, Jianyu, Charles, Zachary, Xu, Zheng, Joshi, Gauri, McMahan, H. Brendan, Arcas, Blaise Aguera y, Al-Shedivat, Maruan, Andrew, Galen, Avestimehr, Salman, Daly, Katharine, Data, Deepesh, Diggavi, Suhas, Eichner, Hubert, Gadhikar, Advait, Garrett, Zachary, Girgis, Antonious M, Hanzely, Filip, Hard, Andrew, He, Chaoyang, Horvath, Samuel, Huo, Zhouyuan, Ingerman, Alex, Jaggi, Martin, Javidi, Tara, Kairouz, Peter, Kale, Satyen, Karimireddy, Sai Praneeth, Konecny, Jakub, Koyejo, Sanmi, Li, Tian, Liu, Luyang, Mohri, Mehryar, Qi, Hang, Reddi, Sashank J, Richtarik, Peter, Singhal, Karan, Smith, Virginia, Soltanolkotabi, Mahdi, Song, Weikang, Suresh, Ananda Theertha, Stich, Sebastian U, Talwalkar, Ameet, Wang, Hongyi, Woodworth, Blake, Wu, Shanshan, Yu, Felix X, Yuan, Honglin, Zaheer, Manzil, Zhang, Mi, Zhang, Tong, Zheng, Chunxiang, Zhu, Chen, Zhu, Wennan

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Distributed Mean Estimation with Limited Communication von Suresh, Ananda Theertha, Yu, Felix X, Kumar, Sanjiv, McMahan, H. Brendan

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Orthogonal Random Features von Yu, Felix X, Suresh, Ananda Theertha, Choromanski, Krzysztof, Holtmann-Rice, Daniel, Kumar, Sanjiv

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Federated Learning: Strategies for Improving Communication Efficiency von Konečný, Jakub, McMahan, H. Brendan, Yu, Felix X, Richtárik, Peter, Suresh, Ananda Theertha, Bacon, Dave

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Disentangling Sampling and Labeling Bias for Learning in Large-Output Spaces von Ankit Singh Rawat, Menon, Aditya Krishna, Jitkrittum, Wittawat, Jayasumana, Sadeep, Yu, Felix X, Reddi, Sashank, Kumar, Sanjiv

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Federated Learning with Only Positive Labels von Yu, Felix X, Ankit Singh Rawat, Menon, Aditya Krishna, Kumar, Sanjiv

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Circulant Binary Embedding von Yu, Felix X, Kumar, Sanjiv, Gong, Yunchao, Chang, Shih-Fu

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