2019/4/3 16:11

要旨

Title Variational Network Inference: Strong and Stable with Concrete Support

Abstract Traditional methods for the discovery of latent network structures are limited in two ways: they either assume that all the signal comes from the network (i.e. there is no source of signal outside the network) or they place constraints on the network parameters to ensure model or algorithmic stability. We address these limitations by proposing a model that incorporates a Gaussian process prior on a network-independent component and formally proving that we get algorithmic stability for free, while providing a novel perspective on model stability as well as robustness results and precise intervals for key inference parameters. We show that, on three applications, our approach outperforms previous methods consistently.

詳細情報

日時 2019/04/23(火) 10:30 - 12:00
URL https://c5dc59ed978213830355fc8978.doorkeeper.jp/events/89250

場所

〒103-0027 東京都中央区日本橋1-4-1 日本橋一丁目三井ビルディング 15階