Paper

  • A MULTI-OBJECTIVE APPROACH FOR OPTIMIZING TECHNICAL, ENVIRONMENTAL, AND ECONOMIC OF ENERGY COMMUNITIES: A CASE STUDY OF A RESIDENTIAL COMMUNITY IN TARRAGONA.

    ECOS 2024

    A MULTI-OBJECTIVE APPROACH FOR OPTIMIZING TECHNICAL, ENVIRONMENTAL, AND ECONOMIC OF ENERGY COMMUNITIES: A CASE STUDY OF A RESIDENTIAL COMMUNITY IN TARRAGONA.

    Youssef Elomari, Carles Mateu, Marc Marín-Genescà, Dieter Boer p1411-1421 from 37th International Conference on Efficiency, Cost, Optimization, Simulation and Environmental Impact of Energy Systems (ECOS 2024)
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  • A MULTI-OBJECTIVE OPTIMIZATION STRATEGY FOR DISTRICT HEATING PRODUCTION PORTFOLIO PLANNING

    ECOS 2024

    A MULTI-OBJECTIVE OPTIMIZATION STRATEGY FOR DISTRICT HEATING PRODUCTION PORTFOLIO PLANNING

    Janina Zittel, Jan-Patrick Clarner, Christine Tawfik, Maxwell Dykes, Fabian Rivetta, Stephanie Riedmüller p764-775 from 37th International Conference on Efficiency, Cost, Optimization, Simulation and Environmental Impact of Energy Systems (ECOS 2024)
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  • A MULTI-PHASE HYGRO-THERMAL MODEL FOR WOODEN BRIDGE COMPONENTS EXPOSED TO SOLAR RADIATION

    World Conference on Timber Engineering 2023 (WCTE 2023)

    A MULTI-PHASE HYGRO-THERMAL MODEL FOR WOODEN BRIDGE COMPONENTS EXPOSED TO SOLAR RADIATION

    Stefania Fortino, Petr Hradil, Timo Avikainen, Keijo Koski, Ludovic Fülöp p449-454 from World Conference on Timber Engineering (WCTE 2023)
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  • A Multi-Resolution Framework for U-Nets with Applications to Hierarchical VAEs

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    A Multi-Resolution Framework for U-Nets with Applications to Hierarchical VAEs

    Dominic Danks, George Deligiannidis, Arnaud Doucet, Fabian Falck, Chris C Holmes, Matthew Willetts, Christopher Williams, Christopher Yau p15529-15544 from Advances in Neural Information Processing Systems 35
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  • A Multi-Task Benchmark for Korean Legal Language Understanding and Judgement Prediction

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    A Multi-Task Benchmark for Korean Legal Language Understanding and Judgement Prediction

    Kyoungyeon Cho, Wonseok Hwang, Dongjun Lee, Hanuhl Lee, Minjoon Seo p32537-32551 from Advances in Neural Information Processing Systems 35
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  • A Multilabel Classification Framework for Approximate Nearest Neighbor Search

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    A Multilabel Classification Framework for Approximate Nearest Neighbor Search

    Ville Hyvönen, Elias Jääsaari, Teemu Roos p35741-35754 from Advances in Neural Information Processing Systems 35
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  • A MULTISCALE ANALYSIS OF HYGROEXPANSION IN WOOD

    World Conference on Timber Engineering 2025

    A MULTISCALE ANALYSIS OF HYGROEXPANSION IN WOOD

    Sara Florisson, Marie Hartwig-Nair, Nil Tabudlong Jonasson, Klara Hackenstrass, Erik Kristofer Gamstedt, Malin Wohlert p672-680 from 14th World Conference on Timber Engineering 2025 (WCTE 2025)
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  • A Near-optimal Algorithm for Learning Margin Halfspaces with Massart Noise

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    A Near-optimal Algorithm for Learning Margin Halfspaces with Massart Noise

    Ilias Diakonikolas, Nikos Zarifis p88605-88626 from Advances in Neural Information Processing Systems 37
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  • A Near-Optimal Best-Of-Both-Worlds Algorithm for Online Learning with Feedback Graphs

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    A Near-Optimal Best-Of-Both-Worlds Algorithm for Online Learning with Feedback Graphs

    Nicolò Cesa-Bianchi, Chloé Rouyer, Yevgeny Seldin, Dirk Van Der Hoeven p35035-35048 from Advances in Neural Information Processing Systems 35
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  • A Near-Optimal Primal-Dual Method for Off-Policy Learning in CMDP

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    A Near-Optimal Primal-Dual Method for Off-Policy Learning in CMDP

    Fan Chen, Zaiwen Wen, Junyu Zhang p10521-10532 from Advances in Neural Information Processing Systems 35
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  • A Nearly Optimal and Low-Switching Algorithm for Reinforcement Learning with General Function Approximation

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    A Nearly Optimal and Low-Switching Algorithm for Reinforcement Learning with General Function Approximation

    Quanquan Gu, Jiafan He, Heyang Zhao p94684-94735 from Advances in Neural Information Processing Systems 37
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  • A Neural Collapse Perspective on Feature Evolution in Graph Neural Networks

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    A Neural Collapse Perspective on Feature Evolution in Graph Neural Networks

    Joan Bruna, Vignesh Kothapalli, Tom Tirer p14134-14191 from Advances in Neural Information Processing Systems 36
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