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  • PRINTED SENSORS FOR MONITORING WOOD MOISTURE CONTENT INSIDE TIMBER BUILDING ELEMENTS

    World Conference on Timber Engineering 2023 (WCTE 2023)

    PRINTED SENSORS FOR MONITORING WOOD MOISTURE CONTENT INSIDE TIMBER BUILDING ELEMENTS

    Boris Forsthuber, Michael Truskaller, Irene Spitaler, Pavel Kulha, Maximilian Scherf, Gabriel Partl, Albert Rössler, Gerhard Engelbrecht, Gerhard Grüll p3874-3879 from World Conference on Timber Engineering (WCTE 2023)
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  • Prior-itizing Privacy: A Bayesian Approach to Setting the Privacy Budget in Differential Privacy

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Prior-itizing Privacy: A Bayesian Approach to Setting the Privacy Budget in Differential Privacy

    Zeki Kazan, Jerome Reiter p90384-90430 from Advances in Neural Information Processing Systems 37
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  • PRIOR: Personalized Prior for Reactivating the Information Overlooked in Federated Learning.

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    PRIOR: Personalized Prior for Reactivating the Information Overlooked in Federated Learning.

    Mingjia Shi, Yuhao Zhou, Kai Wang, Huaizheng Zhang, Shudong Huang, Qing Ye, Jiancheng Lv p28378-28392 from Advances in Neural Information Processing Systems 36
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  • PriorBand: Practical Hyperparameter Optimization in the Age of Deep Learning

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    PriorBand: Practical Hyperparameter Optimization in the Age of Deep Learning

    Neeratyoy Mallik, Edward Bergman, Carl Hvarfner, Danny Stoll, Maciej Janowski, Marius Lindauer, Luigi Nardi, Frank Hutter p7377-7391 from Advances in Neural Information Processing Systems 36
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  • Prioritizing Samples in Reinforcement Learning with Reducible Loss

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Prioritizing Samples in Reinforcement Learning with Reducible Loss

    Shivakanth Sujit, Somjit Nath, Pedro Braga, Samira Ebrahimi Kahou p23237-23258 from Advances in Neural Information Processing Systems 36
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  • Prism: A Framework for Decoupling and Assessing the Capabilities of VLMs

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Prism: A Framework for Decoupling and Assessing the Capabilities of VLMs

    Yuxuan Qiao, Haodong Duan, Xinyu Fang, Junming Yang, Lin Chen, Songyang Zhang, Jiaqi Wang, Dahua Lin, Kai Chen p111863-111898 from Advances in Neural Information Processing Systems 37
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  • Privacy Amplification via Compression: Achieving the Optimal Privacy-Accuracy-Communication Trade-off in Distributed Mean Estimation

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Privacy Amplification via Compression: Achieving the Optimal Privacy-Accuracy-Communication Trade-off in Distributed Mean Estimation

    Wei-Ning Chen, Dan Song, Ayfer Ozgur, Peter Kairouz p69202-69227 from Advances in Neural Information Processing Systems 36
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  • Privacy Assessment on Reconstructed Images: Are Existing Evaluation Metrics Faithful to Human Perception?

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Privacy Assessment on Reconstructed Images: Are Existing Evaluation Metrics Faithful to Human Perception?

    Xiaoxiao Sun, Nidham Gazagnadou, Vivek Sharma, Lingjuan Lyu, Hongdong Li, Liang Zheng p10223-10237 from Advances in Neural Information Processing Systems 36
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  • Privacy Auditing with One (1) Training Run

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Privacy Auditing with One (1) Training Run

    Thomas Steinke, Milad Nasr, Matthew Jagielski p49268-49280 from Advances in Neural Information Processing Systems 36
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  • Privacy Backdoors: Enhancing Membership Inference through Poisoning Pre-trained Models

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Privacy Backdoors: Enhancing Membership Inference through Poisoning Pre-trained Models

    Yuxin Wen, Leo Marchyok, Sanghyun Hong, Jonas Geiping, Tom Goldstein, Nicholas Carlini p83374-83396 from Advances in Neural Information Processing Systems 37
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  • Privacy Induces Robustness: Information-Computation Gaps and Sparse Mean Estimation

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Privacy Induces Robustness: Information-Computation Gaps and Sparse Mean Estimation

    Kristian Georgiev, Samuel Hopkins p6829-6842 from Advances in Neural Information Processing Systems 35
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  • Privacy of Noisy Stochastic Gradient Descent: More Iterations Without More Privacy Loss

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Privacy of Noisy Stochastic Gradient Descent: More Iterations Without More Privacy Loss

    Jason Altschuler, Kunal Talwar p3788-3800 from Advances in Neural Information Processing Systems 35
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