Sep 12, 2023 · Under the information bottleneck (IB) principle, we associate with this classification problem a representation learning problem, which we call ...
We consider the problem of learning a neural network classifier. Under the information bottleneck (IB) principle, we associate with this classification problem ...
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Nov 3, 2023 · Abstract—We consider the problem of learning a neural network classifier. Under the information bottleneck (IB) principle, we as-.
Sep 12, 2023 · Under the information bottleneck (IB) principle, we associate with this classification problem a representation learning problem, which we call ...
Abstract. Based on the notion of information bottleneck. (IB), we formulate a quantization problem called. “IB quantization”. We show that IB quantization.
Jul 26, 2018 · Abstract:Based on the notion of information bottleneck (IB), we formulate a quantization problem called "IB quantization".
Aggregated Learning (AgrLearn) is a vector-quantization approach to learning neural network classifiers. It builds on an equivalence between IB learning and IB ...
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We consider the problem of learning a neural network classifier. Under the information bottleneck (IB) principle, we associate with this classification problem ...
Sep 22, 2023 · ... Information Bottleneck and Aggregated Learning”. This is a work done by my former PhD student Masoumeh Soflaei during her PhD, in ...
Under the information bottleneck (IB) principle, we as- sociate with this classification problem a representation learn- ing problem, which we call “IB learning ...