Neural Information Processing Systems Foundation, Inc. (NeurIPS)

  • An Efficient Memory Module for Graph Few-Shot Class-Incremental Learning

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    An Efficient Memory Module for Graph Few-Shot Class-Incremental Learning

    Junqi Gao, Dong Li, Biqing Qi, Aijia Zhang p130084-130108 from Advances in Neural Information Processing Systems 37
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  • An Efficient Recipe for Long Context Extension via Middle-Focused Positional Encoding

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    An Efficient Recipe for Long Context Extension via Middle-Focused Positional Encoding

    Tong Wu, Yanpeng Zhao, Zilong Zheng p56349-56373 from Advances in Neural Information Processing Systems 37
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  • An Embarrassingly Simple Approach to Semi-Supervised Few-Shot Learning

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    An Embarrassingly Simple Approach to Semi-Supervised Few-Shot Learning

    Yuxin Peng, Xiu-Shen Wei, H.-Y. Xu, Faen Zhang, Wei Zhou p14489-14500 from Advances in Neural Information Processing Systems 35
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  • An Empirical Study on Disentanglement of Negative-Free Contrastive Learning

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    An Empirical Study on Disentanglement of Negative-Free Contrastive Learning

    Jinkun Cao, Yang Gao, Jialei Huang, Ruiqian Nai, Qing Yang p1210-1222 from Advances in Neural Information Processing Systems 35
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  • An Empirical Study Towards Prompt-Tuning for Graph Contrastive Pre-Training in Recommendations

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    An Empirical Study Towards Prompt-Tuning for Graph Contrastive Pre-Training in Recommendations

    Hongxu Chen, Yicong Li, Guandong Xu, Haoran Yang, Xiangyu Zhao p62853-62868 from Advances in Neural Information Processing Systems 36
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  • An End-To-End Graph Attention Network Hashing for Cross-Modal Retrieval

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    An End-To-End Graph Attention Network Hashing for Cross-Modal Retrieval

    Huilong Jin, Feifei Kou, Jia Luo, Lei Shi, Jiapeng Yang, Shuang Zhang, Yingxue Zhang, Chuangying Zhu p2106-2126 from Advances in Neural Information Processing Systems 37
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  • An engine not a camera: Measuring performative power of online search

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    An engine not a camera: Measuring performative power of online search

    Gabriele Carovano, Moritz Hardt, Celestine Mendler-Dünner p59266-59288 from Advances in Neural Information Processing Systems 37
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  • An Equivalence Between Static and Dynamic Regret Minimization

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    An Equivalence Between Static and Dynamic Regret Minimization

    Andrew Jacobsen, Francesco Orabona p98835-98870 from Advances in Neural Information Processing Systems 37
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  • An exactly solvable model for emergence and scaling laws in the multitask sparse parity problem

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    An exactly solvable model for emergence and scaling laws in the multitask sparse parity problem

    Nayara Fonseca, Seok Lee, Ard Louis, Chris Mingard, Yoonsoo Nam p39632-39693 from Advances in Neural Information Processing Systems 37
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  • An Expectation-Maximization Algorithm for Training Clean Diffusion Models from Corrupted Observations

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    An Expectation-Maximization Algorithm for Training Clean Diffusion Models from Corrupted Observations

    Weimin Bai, Wenzheng Chen, He Sun, Yifei Wang p19447-19471 from Advances in Neural Information Processing Systems 37
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  • An Exploration-by-Optimization Approach to Best of Both Worlds in Linear Bandits

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    An Exploration-by-Optimization Approach to Best of Both Worlds in Linear Bandits

    Shinji Ito, Kei Takemura p71582-71602 from Advances in Neural Information Processing Systems 36
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  • An eye for an ear: zero-shot audio description leveraging an image captioner with audio-visual token distribution matching

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    An eye for an ear: zero-shot audio description leveraging an image captioner with audio-visual token distribution matching

    Slim Essid, Stéphane Lathuiliere, Hugo Malard, Michel Olvera p38720-38743 from Advances in Neural Information Processing Systems 37
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  • An Image is Worth 32 Tokens for Reconstruction and Generation

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    An Image is Worth 32 Tokens for Reconstruction and Generation

    Liang-Chieh Chen, Daniel Cremers, Xueqing Deng, Xiaohui Shen, Mark Weber, Qihang Yu p128940-128966 from Advances in Neural Information Processing Systems 37
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  • An Improved Empirical Fisher Approximation for Natural Gradient Descent

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    An Improved Empirical Fisher Approximation for Natural Gradient Descent

    Philip Woodland, Xiaodong Wu, Wenyi Yu, Chao Zhang p134151-134194 from Advances in Neural Information Processing Systems 37
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  • An Improved Relaxation for Oracle-Efficient Adversarial Contextual Bandits

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    An Improved Relaxation for Oracle-Efficient Adversarial Contextual Bandits

    Kiarash Banihashem, Mohammadtaghi Hajiaghayi, Suho Shin, Max Springer p67471-67486 from Advances in Neural Information Processing Systems 36
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  • An In-depth Investigation of Sparse Rate Reduction in Transformer-like Models

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    An In-depth Investigation of Sparse Rate Reduction in Transformer-like Models

    Yunzhe Hu, Dong Xu, Difan Zou p116815-116837 from Advances in Neural Information Processing Systems 37
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  • An In-Depth Study of Stochastic Backpropagation

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    An In-Depth Study of Stochastic Backpropagation

    Hao Chen, Jun Fang, Bing Shuai, Joseph Tighe, Zhuowen Tu, Mingze Xu p21819-21830 from Advances in Neural Information Processing Systems 35
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  • An Inductive Bias for Tabular Deep Learning

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    An Inductive Bias for Tabular Deep Learning

    Ege Beyazit, Bilal Fadlallah, Jonathan Kozaczuk, Bo Li, Vanessa Wallace p43108-43135 from Advances in Neural Information Processing Systems 36
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  • An Information Theoretic Perspective on Conformal Prediction

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    An Information Theoretic Perspective on Conformal Prediction

    Arash Behboodi, Alvaro Correia, Christos Louizos, Fabio Massoli p101000-101041 from Advances in Neural Information Processing Systems 37
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  • An Information Theory Perspective on Variance-Invariance-Covariance Regularization

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    An Information Theory Perspective on Variance-Invariance-Covariance Regularization

    Randall Balestriero, Kenji Kawaguchi, Yann Lecun, Tim G. J. Rudner, Ravid Shwartz-Ziv p33965-33998 from Advances in Neural Information Processing Systems 36
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  • An Information-Theoretic Evaluation of Generative Models in Learning Multi-modal Distributions

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    An Information-Theoretic Evaluation of Generative Models in Learning Multi-modal Distributions

    Farzan Farnia, Mohammad Jalali, Cheuk Ting Li p9931-9943 from Advances in Neural Information Processing Systems 36
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  • An Information-Theoretic Framework for Deep Learning

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    An Information-Theoretic Framework for Deep Learning

    Hong Jun Jeon, Benjamin Van Roy p3279-3291 from Advances in Neural Information Processing Systems 35
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  • An information-theoretic quantification of the content of communication between brain regions

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    An information-theoretic quantification of the content of communication between brain regions

    Malte Bieler, Jan Bím, Andrea Brovelli, Marco Celotto, Daniel Chicharro, Vito De Feo, Tobias Donner, Ileana Hanganu-Opatz, Stefan Lemke, Hamed Nili, Stefano Panzeri, Alejandro Tlaie, Alessandro Toso p64213-64265 from Advances in Neural Information Processing Systems 36
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  • An Inverse Scaling Law for CLIP Training

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    An Inverse Scaling Law for CLIP Training

    Xianhang Li, Zeyu Wang, Cihang Xie p49068-49087 from Advances in Neural Information Processing Systems 36
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