Paper

  • On the Tradeoff Between Robustness and Fairness

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    On the Tradeoff Between Robustness and Fairness

    Xinsong Ma, Zekai Wang, Weiwei Liu p26230-26241 from Advances in Neural Information Processing Systems 35
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  • On the Use of Anchoring for Training Vision Models

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    On the Use of Anchoring for Training Vision Models

    Vivek Narayanaswamy, Kowshik Thopalli, Rushil Anirudh, Yamen Mubarka, Wesam Sakla, Jayaraman Thiagarajan p95438-95455 from Advances in Neural Information Processing Systems 37
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  • ON THE USE OF ARUCO MARKERS IN LONG TERM MONITORING OF TIMBER STRUCTURES

    World Conference on Timber Engineering 2023 (WCTE 2023)

    ON THE USE OF ARUCO MARKERS IN LONG TERM MONITORING OF TIMBER STRUCTURES

    Jirí Kunecký p558-563 from World Conference on Timber Engineering (WCTE 2023)
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  • ON THE UTILISATION OF THE WORKSPACE OF AN INDUSTRIAL ROBOT FOR MILLING STRUCTURAL TIMBER COMPONENTS - EXPERIMENTAL TRIALS WITH DIFFERENT ARM POSITIONS AND EVALUATION OF MACHINING QUALITY

    World Conference on Timber Engineering 2023 (WCTE 2023)

    ON THE UTILISATION OF THE WORKSPACE OF AN INDUSTRIAL ROBOT FOR MILLING STRUCTURAL TIMBER COMPONENTS - EXPERIMENTAL TRIALS WITH DIFFERENT ARM POSITIONS AND EVALUATION OF MACHINING QUALITY

    Marc Pantscharowitsch, Finn Linzer, Hans-Berndt Neuner, Benjamin Kromoser p599-608 from World Conference on Timber Engineering (WCTE 2023)
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  • On the Variance, Admissibility, and Stability of Empirical Risk Minimization

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    On the Variance, Admissibility, and Stability of Empirical Risk Minimization

    Gil Kur, Eli Putterman, Alexander Rakhlin p37527-37539 from Advances in Neural Information Processing Systems 36
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  • On the Worst Prompt Performance of Large Language Models

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    On the Worst Prompt Performance of Large Language Models

    Bowen Cao, Deng Cai, Zhisong Zhang, Yuexian Zou, Wai Lam p69022-69042 from Advances in Neural Information Processing Systems 37
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  • On Tractable $\Phi$-Equilibria in Non-Concave Games

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    On Tractable $\Phi$-Equilibria in Non-Concave Games

    Yang Cai, Constantinos Daskalakis, Haipeng Luo, Chen-Yu Wei, Weiqiang Zheng p140366-140404 from Advances in Neural Information Processing Systems 37
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  • On Transfer of Adversarial Robustness from Pretraining to Downstream Tasks

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    On Transfer of Adversarial Robustness from Pretraining to Downstream Tasks

    Laura F. Nern, Harsh Raj, Maurice André Georgi, Yash Sharma p59206-59226 from Advances in Neural Information Processing Systems 36
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  • On Translation and Reconstruction Guarantees of the Cycle-Consistent Generative Adversarial Networks

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    On Translation and Reconstruction Guarantees of the Cycle-Consistent Generative Adversarial Networks

    Anish Chakrabarty, Swagatam Das p23607-23620 from Advances in Neural Information Processing Systems 35
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  • On Uncertainty, Tempering, and Data Augmentation in Bayesian Classification

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    On Uncertainty, Tempering, and Data Augmentation in Bayesian Classification

    Sanyam Kapoor, Wesley Maddox, Pavel Izmailov, Andrew Wilson p18211-18225 from Advances in Neural Information Processing Systems 35
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  • On Weak Regret Analysis for Dueling Bandits

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    On Weak Regret Analysis for Dueling Bandits

    El Mehdi Saad, Alexandra Carpentier, Tomáš Kocák, Nicolas Verzelen p40752-40791 from Advances in Neural Information Processing Systems 37
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  • On-Demand Sampling: Learning Optimally from Multiple Distributions

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    On-Demand Sampling: Learning Optimally from Multiple Distributions

    Nika Haghtalab, Michael Jordan, Eric Zhao p406-419 from Advances in Neural Information Processing Systems 35
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