A real‐world evaluation of the implementation of NLP technology in abstract screening of a systematic review von Perlman‐Arrow, Sara, Loo, Noel, Bobrovitz, Niklas, Yan, Tingting, Arora, Rahul K.

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Linear Projections of Teacher Embeddings for Few-Class Distillation von Loo, Noel, Iliopoulos, Fotis, Hu, Wei, Vee, Erik

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Leveraging Low-Rank and Sparse Recurrent Connectivity for Robust Closed-Loop Control von Tumma, Neehal, Lechner, Mathias, Loo, Noel, Hasani, Ramin, Rus, Daniela

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Dataset Distillation with Convexified Implicit Gradients von Loo, Noel, Hasani, Ramin, Lechner, Mathias, Rus, Daniela

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Understanding Reconstruction Attacks with the Neural Tangent Kernel and Dataset Distillation von Loo, Noel, Hasani, Ramin, Lechner, Mathias, Amini, Alexander, Rus, Daniela

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Efficient Dataset Distillation Using Random Feature Approximation von Loo, Noel, Hasani, Ramin, Amini, Alexander, Rus, Daniela

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Evolution of Neural Tangent Kernels under Benign and Adversarial Training von Loo, Noel, Hasani, Ramin, Amini, Alexander, Rus, Daniela

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Generalized Variational Continual Learning von Loo, Noel, Swaroop, Siddharth, Turner, Richard E

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On the Size and Approximation Error of Distilled Sets von Maalouf, Alaa, Tukan, Murad, Loo, Noel, Hasani, Ramin, Lechner, Mathias, Rus, Daniela

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SYSTEMS AND METHODS FOR EFFICIENT DATASET DISTILLATION USING NON-DETERMINISTIC FEATURE APPROXIMATION von AMINI, Alexander A, RUS, Daniela, LOO, Noel, HASANI, Ramin

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Linear Projections of Teacher Embeddings for Few-Class Distillation von Loo, Noel, Iliopoulos, Fotis, Hu, Wei, Vee, Erik

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SYSTEMS AND METHODS FOR EFFICIENT DATASET DISTILLATION USING NON-DETERMINISTIC FEATURE APPROXIMATION von AMINI, Alexander A, RUS, Daniela, LOO, Noel, HASANI, Ramin

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SYSTEMS AND METHODS FOR EFFICIENT DATASET DISTILLATION USING NON-DETERMINISTIC FEATURE APPROXIMATION von Loo, Noel, Rus, Daniela, Amini, Alexander A, Hasani, Ramin

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Leveraging Low-Rank and Sparse Recurrent Connectivity for Robust Closed-Loop Control von Tumma, Neehal, Lechner, Mathias, Loo, Noel, Hasani, Ramin, Rus, Daniela

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Understanding Reconstruction Attacks with the Neural Tangent Kernel and Dataset Distillation von Loo, Noel, Hasani, Ramin, Lechner, Mathias, Amini, Alexander, Rus, Daniela

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Dataset Distillation with Convexified Implicit Gradients von Loo, Noel, Hasani, Ramin, Lechner, Mathias, Rus, Daniela

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Evolution of Neural Tangent Kernels under Benign and Adversarial Training von Loo, Noel, Hasani, Ramin, Amini, Alexander, Rus, Daniela

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Efficient Dataset Distillation Using Random Feature Approximation von Loo, Noel, Hasani, Ramin, Amini, Alexander, Rus, Daniela

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Generalized Variational Continual Learning von Loo, Noel, Swaroop, Siddharth, Turner, Richard E

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On the Size and Approximation Error of Distilled Sets von Maalouf, Alaa, Tukan, Murad, Loo, Noel, Hasani, Ramin, Lechner, Mathias, Rus, Daniela

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