Paper

  • On the Asymptotic Learning Curves of Kernel Ridge Regression under Power-law Decay

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    On the Asymptotic Learning Curves of Kernel Ridge Regression under Power-law Decay

    Yicheng Li, Qian Lin, Haobo Zhang p49341-49364 from Advances in Neural Information Processing Systems 36
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  • On the Benefits of Public Representations for Private Transfer Learning under Distribution Shift

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    On the Benefits of Public Representations for Private Transfer Learning under Distribution Shift

    Amrith Setlur, Virginia Smith, Pratiksha Thaker, Zhiwei Wu p27088-27120 from Advances in Neural Information Processing Systems 37
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  • On the choice of Perception Loss Function for Learned Video Compression

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    On the choice of Perception Loss Function for Learned Video Compression

    Jun Chen, Ashish Khisti, Truong Buu Phan, Sadaf Salehkalaibar, Wei Yu p48226-48274 from Advances in Neural Information Processing Systems 36
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  • On the cohesion and separability of average-link for hierarchical agglomerative clustering

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    On the cohesion and separability of average-link for hierarchical agglomerative clustering

    Miguel Batista, Eduardo Laber p48710-48739 from Advances in Neural Information Processing Systems 37
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  • On the Comparison between Multi-modal and Single-modal Contrastive Learning

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    On the Comparison between Multi-modal and Single-modal Contrastive Learning

    Yuan Cao, Yongqiang Chen, Andi Han, Wei Huang, Taiji Suzuki, Zhiqiang Xu p81549-81605 from Advances in Neural Information Processing Systems 37
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  • On the Complexity of Adversarial Decision Making

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    On the Complexity of Adversarial Decision Making

    Dylan J Foster, Alexander Rakhlin, Ayush Sekhari, Karthik Sridharan p35404-35417 from Advances in Neural Information Processing Systems 35
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  • On the Complexity of Differentially Private Best-Arm Identification with Fixed Confidence

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    On the Complexity of Differentially Private Best-Arm Identification with Fixed Confidence

    Aymen Al Marjani, Achraf Azize, Debabrota Basu, Marc Jourdan p71150-71194 from Advances in Neural Information Processing Systems 36
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  • On the Complexity of Identification in Linear Structural Causal Models

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    On the Complexity of Identification in Linear Structural Causal Models

    Markus Bläser, Julian Dörfler, Maciej Liśkiewicz, Benito van der Zander p100108-100130 from Advances in Neural Information Processing Systems 37
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  • On the Complexity of Learning Sparse Functions with Statistical and Gradient Queries

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    On the Complexity of Learning Sparse Functions with Statistical and Gradient Queries

    Nirmit Joshi, Theodor Misiakiewicz, Nathan Srebro p103198-103241 from Advances in Neural Information Processing Systems 37
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  • On the Complexity of Teaching a Family of Linear Behavior Cloning Learners

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    On the Complexity of Teaching a Family of Linear Behavior Cloning Learners

    Shubham Bharti, Adish Singla, Stephen Wright, Jerry Zhu p103945-103965 from Advances in Neural Information Processing Systems 37
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  • On the Computational Complexity of Private High-dimensional Model Selection

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    On the Computational Complexity of Private High-dimensional Model Selection

    Saptarshi Roy, Ambuj Tewari, Zehua Wang p36683-36716 from Advances in Neural Information Processing Systems 37
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  • On the Computational Landscape of Replicable Learning

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    On the Computational Landscape of Replicable Learning

    Alkis Kalavasis, Amin Karbasi, Grigoris Velegkas, Felix Zhou p105887-105927 from Advances in Neural Information Processing Systems 37
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