A Factored Generalized Additive Model for Clinical Decision Support in the Operating Room

1 code implementation • 29 Jul 2019 • Zhicheng Cui, Bradley A Fritz, Christopher R King, Michael S Avidan, Yixin Chen

In this paper, we propose a factored generalized additive model (F-GAM) to preserve the model interpretability for targeted features while allowing a rich model for interaction with features fixed within the individual.

Additive models Respiratory Failure

D-VAE: A Variational Autoencoder for Directed Acyclic Graphs

2 code implementations • NeurIPS 2019 • Muhan Zhang, Shali Jiang, Zhicheng Cui, Roman Garnett, Yixin Chen

Graph structured data are abundant in the real world.

Bayesian Optimization BIG-bench Machine Learning +2

An End-to-End Deep Learning Architecture for Graph Classification

2 code implementations • AAAI-18 2018 • Muhan Zhang, Zhicheng Cui, Marion Neumann, Yixin Chen

Neural networks are typically designed to deal with data in tensor forms.

General Classification Graph Classification

Extracting Actionability from Machine Learning Models by Sub-optimal Deterministic Planning

no code implementations • 3 Nov 2016 • Qiang Lyu, Yixin Chen, Zhaorong Li, Zhicheng Cui, Ling Chen, Xing Zhang, Haihua Shen

Our work represents a new application of automated planning on an emerging and challenging machine learning paradigm.

Attribute BIG-bench Machine Learning +1

Multi-Scale Convolutional Neural Networks for Time Series Classification

2 code implementations • 22 Mar 2016 • Zhicheng Cui, Wenlin Chen, Yixin Chen

These methods are ad-hoc and separate the feature extraction part with the classification part, which limits their accuracy performance.

Classification Dynamic Time Warping +4

Optimal Action Extraction for Random Forests and Boosted Trees

1 code implementation • 13 Aug 2015 • Zhicheng Cui, Wenlin Chen, Yujie He, Yixin Chen

To address this problem, we present a novel framework to post-process any ATM classifier to extract an optimal actionable plan that can change a given input to a desired class with a minimum cost.