Paper

  • Navigating the Effect of Parametrization for Dimensionality Reduction

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Navigating the Effect of Parametrization for Dimensionality Reduction

    Haiyang Huang, Yingfan Wang, Cynthia Rudin p12977-13019 from Advances in Neural Information Processing Systems 37
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  • Navigating the Maze of Explainable AI: A Systematic Approach to Evaluating Methods and Metrics

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Navigating the Maze of Explainable AI: A Systematic Approach to Evaluating Methods and Metrics

    Lukas Klein, Carsten Lüth, Udo Schlegel, Till Bungert, Mennatallah El-Assady, Paul Jäger p67106-67146 from Advances in Neural Information Processing Systems 37
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  • Navigating the Pitfalls of Active Learning Evaluation: A Systematic Framework for Meaningful Performance Assessment

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Navigating the Pitfalls of Active Learning Evaluation: A Systematic Framework for Meaningful Performance Assessment

    Carsten Lüth, Till Bungert, Lukas Klein, Paul Jaeger p9789-9836 from Advances in Neural Information Processing Systems 36
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  • Navigating the Safety Landscape: Measuring Risks in Finetuning Large Language Models

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Navigating the Safety Landscape: Measuring Risks in Finetuning Large Language Models

    Sheng Peng, Pin-Yu Chen, Matthew Hull, Duen Chau p95692-95715 from Advances in Neural Information Processing Systems 37
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  • NAVSIM: Data-Driven Non-Reactive Autonomous Vehicle Simulation and Benchmarking

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    NAVSIM: Data-Driven Non-Reactive Autonomous Vehicle Simulation and Benchmarking

    Daniel Dauner, Marcel Hallgarten, Tianyu Li, Xinshuo Weng, Zhiyu Huang, Zetong Yang, Hongyang Li, Igor Gilitschenski, Boris Ivanovic, Marco Pavone, Andreas Geiger, Kashyap Chitta p28706-28719 from Advances in Neural Information Processing Systems 37
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  • NCDL:  A Framework for Deep Learning on non-Cartesian Lattices

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    NCDL: A Framework for Deep Learning on non-Cartesian Lattices

    Joshua Horacsek, Usman Alim p79363-79375 from Advances in Neural Information Processing Systems 36
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  • NCP: Neural Correspondence Prior for Effective Unsupervised Shape Matching

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    NCP: Neural Correspondence Prior for Effective Unsupervised Shape Matching

    Souhaib Attaiki, Maks Ovsjanikov p28842-28857 from Advances in Neural Information Processing Systems 35
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  • Near Instance-Optimal PAC Reinforcement Learning for Deterministic MDPs

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Near Instance-Optimal PAC Reinforcement Learning for Deterministic MDPs

    Andrea Tirinzoni, Aymen Al Marjani, Emilie Kaufmann p8785-8798 from Advances in Neural Information Processing Systems 35
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  • Near Optimal Reconstruction of Spherical Harmonic Expansions

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Near Optimal Reconstruction of Spherical Harmonic Expansions

    Amir Zandieh, Insu Han, Haim Avron p23968-23989 from Advances in Neural Information Processing Systems 36
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  • Near-Isometric Properties of Kronecker-Structured Random Tensor Embeddings

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Near-Isometric Properties of Kronecker-Structured Random Tensor Embeddings

    Qijia Jiang p10191-10202 from Advances in Neural Information Processing Systems 35
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  • Near-Linear Time Algorithm for the Chamfer Distance

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Near-Linear Time Algorithm for the Chamfer Distance

    Ainesh Bakshi, Piotr Indyk, Rajesh Jayaram, Sandeep Silwal, Erik Waingarten p66833-66844 from Advances in Neural Information Processing Systems 36
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  • Near-Minimax-Optimal Distributional Reinforcement Learning with a Generative Model

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Near-Minimax-Optimal Distributional Reinforcement Learning with a Generative Model

    Mark Rowland, Li Wenliang, Rémi Munos, Clare Lyle, Yunhao Tang, Will Dabney p132774-132823 from Advances in Neural Information Processing Systems 37
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