세미나 및 콜로퀴엄

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구글 Calendar나 iPhone 등에서 구독하면 세미나 시작 전에 알림을 받을 수 있습니다.

With the goal of reducing the number of annotated data necessary for current deep learning (DL) algorithms, semi-supervised learning (SSL) algorithms use unlabeled data which is vastly more accessible than their labeled counterpart to enhance the performance of deep neural networks (DNNs) when trained on a small number of labeled data. As an example, state-of-the-art SSL algorithms can achieve up to ~84% accuracy on the CIFAR10 dataset using 1 image per class, as long as the single image is of “prototypical” quality. This session will introduce common SSL settings considered in recent works and cover DL-based SSL algorithms in a chronological fashion. While existing SSL algorithms are mainly heuristics (they lack theoretical justifications), the intuition underlying such algorithms will also be discussed in relation to the merging consensus in DL-based generalization theory/studies.
Host: 이창옥     미정     2020-07-10 10:50:34
A classical result in Monge-Ampere equation states the paraboloids are the only convex entire solutions to $\det D^2 u = 1$. In this talk, we discuss a recent progress on the generalization of this classification in 2-dimension when the right-hand side is $(1+|Dx|^2)^{\beta}$. This corresponds to the classification of translating solitons to the flow by power of the Gauss curvature. Our proof combines spectral analysis from the linear theory and the theory of Monge-Ampere equation. This is a joint work with Kyeongsu Choi and Soojung Kim.
Meeting ID: 914 3828 0517 Password: 633013
Host: 권순식     미정     2020-07-03 09:55:18