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  • title: Active Deep Probabilistic Subsampling
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            Active Deep Probabilistic Subsampling

            19. července 2021

            Řečníci

            HVG

            Hans Van Gorp

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            IH

            Iris Huijben

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            BV

            Bastiaan Veeling

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            Organizátor

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            ICML 2021

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            O organizátorovi (ICML 2021)

            The International Conference on Machine Learning (ICML) is the premier gathering of professionals dedicated to the advancement of the branch of artificial intelligence known as machine learning. ICML is globally renowned for presenting and publishing cutting-edge research on all aspects of machine learning used in closely related areas like artificial intelligence, statistics and data science, as well as important application areas such as machine vision, computational biology, speech recognition, and robotics. ICML is one of the fastest growing artificial intelligence conferences in the world. Participants at ICML span a wide range of backgrounds, from academic and industrial researchers, to entrepreneurs and engineers, to graduate students and postdocs.

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            PAGE: A Simple and Optimal Probabilistic Gradient Estimator for Nonconvex Optimization
            11:53

            PAGE: A Simple and Optimal Probabilistic Gradient Estimator for Nonconvex Optimization

            Zhize Li, …

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            ICML 2021 4 years ago

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            Best Model Identiication: A Rested Bandit Formulation
            05:05

            Best Model Identiication: A Rested Bandit Formulation

            Leonardo Cella, …

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            ICML 2021 4 years ago

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            Context-Aware Online Collective Inference for Templated Graphical Models
            05:19

            Context-Aware Online Collective Inference for Templated Graphical Models

            Charles Dickens, …

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            ICML 2021 4 years ago

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            Beyond Implicit Regularization: Avoiding Overfitting via Regularizer Mirror Descent
            20:38

            Beyond Implicit Regularization: Avoiding Overfitting via Regularizer Mirror Descent

            Navid Azizan, …

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            ICML 2021 4 years ago

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            Opening remarks
            04:10

            Opening remarks

            Alessandra Tosi

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            ICML 2021 4 years ago

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            Tight Bounds on the Smallest Eigenvalue of the Neural Tangent Kernel for Deep ReLU Networks
            05:04

            Tight Bounds on the Smallest Eigenvalue of the Neural Tangent Kernel for Deep ReLU Networks

            Quynh Nguyen, …

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            ICML 2021 4 years ago

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