Paper

  • Optimal Preconditioning and Fisher Adaptive Langevin Sampling

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Optimal Preconditioning and Fisher Adaptive Langevin Sampling

    Michalis Titsias p29449-29460 from Advances in Neural Information Processing Systems 36
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  • Optimal privacy guarantees for a relaxed threat model: Addressing sub-optimal adversaries in differentially private machine learning

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Optimal privacy guarantees for a relaxed threat model: Addressing sub-optimal adversaries in differentially private machine learning

    Georgios Kaissis, Stefan Kolek, Anneliese Riess, Daniel Rueckert, Alexander Ziller p55802-55825 from Advances in Neural Information Processing Systems 36
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  • Optimal Private and Communication Constraint Distributed Goodness-of-Fit Testing for Discrete Distributions in the Large Sample Regime

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Optimal Private and Communication Constraint Distributed Goodness-of-Fit Testing for Discrete Distributions in the Large Sample Regime

    Lasse Vuursteen p3354-3390 from Advances in Neural Information Processing Systems 37
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  • Optimal Query Complexities for Dynamic Trace Estimation

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Optimal Query Complexities for Dynamic Trace Estimation

    David Woodruff, Fred Zhang, Richard Zhang p35049-35060 from Advances in Neural Information Processing Systems 35
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  • Optimal Rates for Bandit Nonstochastic Control

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Optimal Rates for Bandit Nonstochastic Control

    Elad Hazan, Stephen Newman, Y. Jennifer Sun p21908-21919 from Advances in Neural Information Processing Systems 36
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  • Optimal Rates for Vector-Valued Spectral Regularization Learning Algorithms

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Optimal Rates for Vector-Valued Spectral Regularization Learning Algorithms

    Arthur Gretton, Zhu Li, Dimitri Meunier, Mattes Mollenhauer, Zikai Shen p82514-82559 from Advances in Neural Information Processing Systems 37
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  • Optimal Regret Is Achievable with Bounded Approximate Inference Error: An Enhanced Bayesian Upper Confidence Bound Framework

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Optimal Regret Is Achievable with Bounded Approximate Inference Error: An Enhanced Bayesian Upper Confidence Bound Framework

    Ziyi Huang, Henry Lam, Amirhossein Meisami, Haofeng Zhang p16055-16082 from Advances in Neural Information Processing Systems 36
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  • Optimal Scalarizations for Sublinear Hypervolume Regret

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Optimal Scalarizations for Sublinear Hypervolume Regret

    Qiuyi (Richard) Zhang p39963-39999 from Advances in Neural Information Processing Systems 37
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  • Optimal Scaling for Locally Balanced Proposals in Discrete Spaces

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Optimal Scaling for Locally Balanced Proposals in Discrete Spaces

    Hanjun Dai, Dale Schuurmans, Haoran Sun p23867-23880 from Advances in Neural Information Processing Systems 35
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  • OPTIMAL SIZING OF AN AMMONIA PRODUCTION AND TRANSPORTATION SUPPLY CHAIN BASED ON RENEWABLE ELECTRICITY: COMPARISON BETWEEN PARAMETRIC STUDY AND A COSTS-EMISSIONS BI-OBJECTIVE OPTIMIZATION

    ECOS 2024

    OPTIMAL SIZING OF AN AMMONIA PRODUCTION AND TRANSPORTATION SUPPLY CHAIN BASED ON RENEWABLE ELECTRICITY: COMPARISON BETWEEN PARAMETRIC STUDY AND A COSTS-EMISSIONS BI-OBJECTIVE OPTIMIZATION

    Cécile Diamantis, Pimprenelle Parmentier, Elise Le Goff, Alain Ruby p1095-1106 from 37th International Conference on Efficiency, Cost, Optimization, Simulation and Environmental Impact of Energy Systems (ECOS 2024)
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  • Optimal testing using combined test statistics across independent studies

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Optimal testing using combined test statistics across independent studies

    Botond Szabo, Aad Van Der Vaart, Harry Van Zanten, Lasse Vuursteen p80661-80673 from Advances in Neural Information Processing Systems 36
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  • Optimal Time Complexities of Parallel Stochastic Optimization Methods Under a Fixed Computation Model

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Optimal Time Complexities of Parallel Stochastic Optimization Methods Under a Fixed Computation Model

    Peter Richtarik, Alexander Tyurin p16515-16577 from Advances in Neural Information Processing Systems 36
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