Deep Learning
New computational algorithms make it possible to build neural networks with many input nodes and many layers, and distinguish "deep learning" of these networks from previous work on artificial neural nets.
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Fast Model Debias with Machine Unlearning
Neural Information Processing Systems
Such error correlations not only affect the model's ability to make robust predictions but also
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coVarianceNeuralNetworks
Neural Information Processing Systems
Convolutional neural networks (CNN) are among the most popular deep learning (DL) architectures due to their demonstrated ability to learn latent features from Euclidean data adaptively and automatically [1].
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Learning Audio-Visual Dynamics Using Scene Graphs for Audio Source Separation
Neural Information Processing Systems
There exists an unequivocal distinction between the sound produced by a static source and that produced by a moving one, especially when the source moves towards or away from the microphone.
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