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An Augmentation Overlap Theory of Contrastive Learning
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An Augmentation Overlap Theory of Contrastive Learning
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An Augmentation Overlap Theory of Contrastive Learning
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Diffeomorphism-based feature learning using Poincaré inequalities on augmented input space
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Diffeomorphism-based feature learning using Poincaré inequalities on augmented input space
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Diffeomorphism-based feature learning using Poincaré inequalities on augmented input space
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Enhancing sentiment classification on small datasets through data augmentation and transfer learning
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HPoolGCL: Augmentation‐Free Cross‐Granularity Graph Contrastive Learning With Hierarchical Pooling
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On the Ability of Deep Networks to Learn Symmetries from Data: A Neural Kernel Theory
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On the Ability of Deep Networks to Learn Symmetries from Data: A Neural Kernel Theory
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On the Ability of Deep Networks to Learn Symmetries from Data: A Neural Kernel Theory
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Sparse SVM with Hard-Margin Loss: a Newton-Augmented Lagrangian Method in Reduced Dimensions
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Sparse SVM with Hard-Margin Loss: a Newton-Augmented Lagrangian Method in Reduced Dimensions
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Sparse SVM with Hard-Margin Loss: a Newton-Augmented Lagrangian Method in Reduced Dimensions
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Correction: A survey on augmenting knowledge graphs (KGs) with large language models (LLMs): models, evaluation metrics, benchmarks, and challenges
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Statistical field theory for Markov decision processes under uncertainty
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Statistical field theory for Markov decision processes under uncertainty
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Statistical field theory for Markov decision processes under uncertainty
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On Non-asymptotic Theory of Recurrent Neural Networks in Temporal Point Processes
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Prominent Roles of Conditionally Invariant Components in Domain Adaptation: Theory and Algorithms
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On Non-asymptotic Theory of Recurrent Neural Networks in Temporal Point Processes
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Prominent Roles of Conditionally Invariant Components in Domain Adaptation: Theory and Algorithms
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On Non-asymptotic Theory of Recurrent Neural Networks in Temporal Point Processes
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Prominent Roles of Conditionally Invariant Components in Domain Adaptation: Theory and Algorithms