Neural Information Processing Systems Foundation, Inc. (NeurIPS)

  • Why Do Tree-Based Models Still Outperform Deep Learning on Typical Tabular Data?

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Why Do Tree-Based Models Still Outperform Deep Learning on Typical Tabular Data?

    Leo Grinsztajn, Edouard Oyallon, Gael Varoquaux p507-520 from Advances in Neural Information Processing Systems 35
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  • Why Do We Need Large Batchsizes in Contrastive Learning? A Gradient-Bias Perspective

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Why Do We Need Large Batchsizes in Contrastive Learning? A Gradient-Bias Perspective

    Changyou Chen, Liqun Chen, Yiran Chen, Trishul Chilimbi, Jiali Duan, Son Tran, Yi Xu, Belinda Zeng, Jianyi Zhang p33860-33875 from Advances in Neural Information Processing Systems 35
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  • Why Do We Need Weight Decay in Modern Deep Learning?

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Why Do We Need Weight Decay in Modern Deep Learning?

    Maksym Andriushchenko, Francesco D'Angelo, Nicolas Flammarion, Aditya Varre p23191-23223 from Advances in Neural Information Processing Systems 37
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  • Why Does Sharpness-Aware Minimization Generalize Better Than SGD?

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Why Does Sharpness-Aware Minimization Generalize Better Than SGD?

    Xiangning Chen, Zixiang Chen, Quanquan Gu, Cho-Jui Hsieh, Yiwen Kou, Junkai Zhang p72325-72376 from Advances in Neural Information Processing Systems 36
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  • Why Go Full? Elevating Federated Learning Through Partial Network Updates

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Why Go Full? Elevating Federated Learning Through Partial Network Updates

    Wenkai Guo, Xuefeng Liu, Jianwei Niu, Shaojie Tang, Haolin Wang p99773-99799 from Advances in Neural Information Processing Systems 37
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  • Why Neural Networks Find Simple Solutions: The Many Regularizers of Geometric Complexity

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Why Neural Networks Find Simple Solutions: The Many Regularizers of Geometric Complexity

    David Barrett, Benoit Dherin, Michael Munn, Mihaela Rosca p2333-2349 from Advances in Neural Information Processing Systems 35
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  • Why Robust Generalization in Deep Learning is Difficult: Perspective of Expressive Power

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Why Robust Generalization in Deep Learning is Difficult: Perspective of Expressive Power

    John Hopcroft, Jikai Jin, Binghui Li, Liwei Wang, Han Zhong p4370-4384 from Advances in Neural Information Processing Systems 35
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  • Why So Pessimistic? Estimating Uncertainties for Offline RL Through Ensembles, and Why Their Independence Matters

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Why So Pessimistic? Estimating Uncertainties for Offline RL Through Ensembles, and Why Their Independence Matters

    Kamyar Ghasemipour, Shixiang Shane Gu, Ofir Nachum p18267-18281 from Advances in Neural Information Processing Systems 35
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  • Why the Metric Backbone Preserves Community Structure

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Why the Metric Backbone Preserves Community Structure

    Charbel Chucri, Maximilien Dreveton, Matthias Grossglauser, Patrick Thiran p37439-37472 from Advances in Neural Information Processing Systems 37
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  • Why think step by step? Reasoning emerges from the locality of experience

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Why think step by step? Reasoning emerges from the locality of experience

    Noah Goodman, Michael Li, Ben Prystawski p70926-70947 from Advances in Neural Information Processing Systems 36
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  • Why Transformers Need Adam: A Hessian Perspective

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Why Transformers Need Adam: A Hessian Perspective

    Congliang Chen, Tian Ding, Ziniu Li, Zhi-Quan Luo, Ruoyu Sun, Yushun Zhang p131786-131823 from Advances in Neural Information Processing Systems 37
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  • Why Warmup the Learning Rate? Underlying Mechanisms and Improvements

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Why Warmup the Learning Rate? Underlying Mechanisms and Improvements

    Maissam Barkeshli, Dayal Singh Kalra p111760-111801 from Advances in Neural Information Processing Systems 37
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  • Wide Neural Networks as Gaussian Processes: Lessons from Deep Equilibrium Models

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Wide Neural Networks as Gaussian Processes: Lessons from Deep Equilibrium Models

    Hongyang Gao, Tianxiang Gao, Xiaokai Huo, Hailiang Liu p54918-54951 from Advances in Neural Information Processing Systems 36
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  • Wide Two-Layer Networks can Learn from Adversarial Perturbations

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Wide Two-Layer Networks can Learn from Adversarial Perturbations

    Hiroshi Kera, Soichiro Kumano, Toshihiko Yamasaki p59755-59807 from Advances in Neural Information Processing Systems 37
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  • WikiContradict: A Benchmark for Evaluating LLMs on Real-World Knowledge Conflicts from Wikipedia

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    WikiContradict: A Benchmark for Evaluating LLMs on Real-World Knowledge Conflicts from Wikipedia

    Javier Carnerero-Cano, Elizabeth Daly, Yufang Hou, Radu Marinescu, Inkit Padhi, Alessandra Pascale, Prasanna Sattigeri, Tigran Tchrakian p109701-109747 from Advances in Neural Information Processing Systems 37
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  • WikiDBs: A Large-Scale Corpus Of Relational Databases From Wikidata

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    WikiDBs: A Large-Scale Corpus Of Relational Databases From Wikidata

    Carsten Binnig, Jan-Micha Bodensohn, Liane Vogel p41186-41201 from Advances in Neural Information Processing Systems 37
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  • WikiDO: A New Benchmark Evaluating Cross-Modal Retrieval for Vision-Language Models

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    WikiDO: A New Benchmark Evaluating Cross-Modal Retrieval for Vision-Language Models

    Aditi Chaudhary, Sahil Dharod, Preethi Jyothi, T Kalyan, Azeem Motiwala, Piyush Pasi, Krishna Srinivasan p140812-140827 from Advances in Neural Information Processing Systems 37
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  • Wild-GS: Real-Time Novel View Synthesis from Unconstrained Photo Collections

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Wild-GS: Real-Time Novel View Synthesis from Unconstrained Photo Collections

    Yiqun Mei, Vishal Patel, Jiacong Xu p103334-103355 from Advances in Neural Information Processing Systems 37
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  • Wild-Time: A Benchmark of in-The-Wild Distribution Shift Over Time

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Wild-Time: A Benchmark of in-The-Wild Distribution Shift Over Time

    Bochuan Cao, Caroline Choi, Chelsea Finn, Pang Wei Koh, Yoonho Lee, Huaxiu Yao p10309-10324 from Advances in Neural Information Processing Systems 35
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  • WildfireSpreadTS: A dataset of multi-modal time series for wildfire spread prediction

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    WildfireSpreadTS: A dataset of multi-modal time series for wildfire spread prediction

    Sebastian Gerard, Josephine Sullivan, Yu Zhao p74515-74529 from Advances in Neural Information Processing Systems 36
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  • WildGaussians: 3D Gaussian Splatting In the Wild

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    WildGaussians: 3D Gaussian Splatting In the Wild

    Zuzana Kukelova, Jonas Kulhanek, Songyou Peng, Marc Pollefeys, Torsten Sattler p21271-21288 from Advances in Neural Information Processing Systems 37
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  • WildGuard: Open One-stop Moderation Tools for Safety Risks, Jailbreaks, and Refusals of LLMs

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    WildGuard: Open One-stop Moderation Tools for Safety Risks, Jailbreaks, and Refusals of LLMs

    Yejin Choi, Nouha Dziri, Allyson Ettinger, Seungju Han, Liwei Jiang, Nathan Lambert, Bill Yuchen Lin, Kavel Rao p8093-8131 from Advances in Neural Information Processing Systems 37
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  • WildPPG: A Real-World PPG Dataset of Long Continuous Recordings

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    WildPPG: A Real-World PPG Dataset of Long Continuous Recordings

    Berken Utku Demirel, Christian Holz, Manuel Meier p2246-2266 from Advances in Neural Information Processing Systems 37
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  • WildTeaming at Scale: From In-the-Wild Jailbreaks to (Adversarially) Safer Language Models

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    WildTeaming at Scale: From In-the-Wild Jailbreaks to (Adversarially) Safer Language Models

    Faeze Brahman, Yejin Choi, Nouha Dziri, Allyson Ettinger, Seungju Han, Liwei Jiang, Sachin Kumar, Ximing Lu, Niloofar Mireshghallah, Kavel Rao, Maarten Sap p47094-47165 from Advances in Neural Information Processing Systems 37
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