Implicit Convex Regularizers of CNN Architectures: Convex Optimization of Two- and Three-Layer Networks in Polynomial Time
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Cites background from "Implicit Convex Regularizers of CNN..."
...In addition, a recent series of work (Pilanci & Ergen, 2020; Ergen & Pilanci, 2021; Sahiner et al., 2021; Gupta et al., 2021) showed that regularized two-layer ReLU network training problems exhibit a convex loss landscape in a higher dimensional space, which was previously attributed to the benign…...
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Cites background or methods from "Implicit Convex Regularizers of CNN..."
...The most relevant to our work are (Pilanci & Ergen, 2020; Ergen & Pilanci, 2020b) which put forth a convex duality framework for two-layer ReLU networks with a single output....
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...It is however restricted to scalar-output networks, and considers either fully-connected networks (Pilanci & Ergen, 2020), or, CNNs with average pooling (Ergen & Pilanci, 2020b)....
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...Convex neural networks were introduced in (Bach, 2017; Bengio et al., 2006), and later in (Pilanci & Ergen, 2020; Ergen & Pilanci, 2020a;b)....
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References
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"Implicit Convex Regularizers of CNN..." refers methods in this paper
...Next, we use real-valued Radon measures with the uniform norms (Rudin, 1964)....
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