Wei-Cheng Lee — accepted AI-conference papers

2018

MixLasso: Generalized Mixed Regression via Convex Atomic-Norm Regularization

Ian En-Hsu Yen, Wei-Cheng Lee, Kai Zhong, Sung-En Chang, Pradeep K Ravikumar, Shou-De Lin

NeurIPS 2018poster

We consider a generalization of mixed regression where the response is an additive combination of several mixture components. Standard mixed regression is a special case where each response is generated from exactly one component. Typical approaches to the mixture regression problem employ local sea…

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2017

Latent Feature Lasso

Ian En-Hsu Yen, Wei-Cheng Lee, Sung-En Chang, Arun Sai Suggala, Shou-De Lin, Pradeep Ravikumar

ICML 2017poster

The latent feature model (LFM), proposed in (Griffiths \& Ghahramani, 2005), but possibly with earlier origins, is a generalization of a mixture model, where each instance is generated not from a single latent class but from a combination of

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