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Provable and Efficient Dataset Distillation for Kernel Ridge Regression
Our code is available at GitHub.
Technology: Information Technology > Artificial Intelligence > Machine Learning > Neural Networks > Deep Learning (1.00)
We thank the reviewers for their careful reading of our work and for their helpful comments
We thank the reviewers for their careful reading of our work and for their helpful comments. We will also clarify that the text in sections 2.1 and 2.2 In terms of experimental predictions, our work predicts the synaptic weights in the SFA circuit. One mechanism for implementing a quadratic expansion are so-called "Sigma-Pi units" (Rumelhart, Hinton and (Mel and Koch, 1990). In this case, the derivation proceeds exactly as laid out in the paper. Thank you for pointing out the typos.
On Mixtures of Markov Chains
Our algorithm is spectral in nature, and is easy to implement.
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Technology: Information Technology > Artificial Intelligence > Machine Learning > Learning Graphical Models > Undirected Networks > Markov Models (0.88)
Provable and Efficient Dataset Distillation for Kernel Ridge Regression
Our code is available at GitHub.
Technology: Information Technology > Artificial Intelligence > Machine Learning > Neural Networks > Deep Learning (1.00)
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