Paper

  • The Fine-Grained Complexity of Gradient Computation for Training Large Language Models

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    The Fine-Grained Complexity of Gradient Computation for Training Large Language Models

    Josh Alman, Zhao Song p61419-61454 from Advances in Neural Information Processing Systems 37
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  • The FineWeb Datasets: Decanting the Web for the Finest Text Data at Scale

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    The FineWeb Datasets: Decanting the Web for the Finest Text Data at Scale

    Loubna allal, Hynek Kydlíček, Anton Lozhkov, Margaret Mitchell, Guilherme Penedo, Colin Raffel, Leandro Von Werra, Thomas Wolf p30811-30849 from Advances in Neural Information Processing Systems 37
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  • THE FIRST MASS TIMBER BUILDING IN BRAZIL

    World Conference on Timber Engineering 2023 (WCTE 2023)

    THE FIRST MASS TIMBER BUILDING IN BRAZIL

    Carlito Calil Neto, Alexander Takata, Vitor Afonso Neves Silva p4215-4221 from World Conference on Timber Engineering (WCTE 2023)
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  • The First Optimal Acceleration of High-Order Methods in Smooth Convex Optimization

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    The First Optimal Acceleration of High-Order Methods in Smooth Convex Optimization

    Alexander Gasnikov, Dmitry Kovalev p35339-35351 from Advances in Neural Information Processing Systems 35
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  • The First Optimal Algorithm for Smooth and Strongly-Convex-Strongly-Concave Minimax Optimization

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    The First Optimal Algorithm for Smooth and Strongly-Convex-Strongly-Concave Minimax Optimization

    Alexander Gasnikov, Dmitry Kovalev p14691-14703 from Advances in Neural Information Processing Systems 35
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  • The Fragility of Fairness: Causal Sensitivity Analysis for Fair Machine Learning

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    The Fragility of Fairness: Causal Sensitivity Analysis for Fair Machine Learning

    Mel Andrews, Jake Fawkes, Nic Fishman, Zachary Lipton p137105-137134 from Advances in Neural Information Processing Systems 37
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  • The Franz-Parisi Criterion and Computational Trade-Offs in High Dimensional Statistics

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    The Franz-Parisi Criterion and Computational Trade-Offs in High Dimensional Statistics

    Afonso S Bandeira, Ahmed El Alaoui, Samuel Hopkins, Tselil Schramm, Alexander S Wein, Ilias Zadik p33831-33844 from Advances in Neural Information Processing Systems 35
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  • The Fundamental Limitations of Clay for Assessing Human Response for Behind Armour Blunt Trauma

    Royal Military Academy (Belgium)

    The Fundamental Limitations of Clay for Assessing Human Response for Behind Armour Blunt Trauma

    J. Op’t Eynde, D. Y. Pang, C. F. Morino, M. Z. Abrams, J. R. Kait, R. S. Salzar, T. B. Bentley, B. S. Shender, C. R. Bass p45-54 from 16th Personal Armour Systems Symposium (PASS 2023)
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  • The Future of Thermoeconomics After the School of Zaragoza

    ECOS 2023

    The Future of Thermoeconomics After the School of Zaragoza

    César Torres, Antonio Valero Capilla, Alicia Valero Delgado, César Torres Cuadra p7-21 from 36th International Conference on Efficiency, Cost, Optimization, Simulation and Environmental Impact of Energy Systems (ECOS 2023)
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  • The Future of Thermoeconomics: From Industrial Cost Minimization Toward Cumulative Resources Accounting and Sustainability Assessment

    ECOS 2023

    The Future of Thermoeconomics: From Industrial Cost Minimization Toward Cumulative Resources Accounting and Sustainability Assessment

    Mauro Reini, Melchiorre Casisi p48-57 from 36th International Conference on Efficiency, Cost, Optimization, Simulation and Environmental Impact of Energy Systems (ECOS 2023)
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  • The Gain from Ordering in Online Learning

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    The Gain from Ordering in Online Learning

    Vasilis Kontonis, Mingchen Ma, Christos Tzamos p63894-63906 from Advances in Neural Information Processing Systems 36
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  • The GAN is dead; long live the GAN! A Modern GAN Baseline

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    The GAN is dead; long live the GAN! A Modern GAN Baseline

    Aaron Gokaslan, Yiwen Huang, Volodymyr Kuleshov, James Tompkin p44177-44215 from Advances in Neural Information Processing Systems 37
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