๐ฎ
๐ฎ
The Ethereal
Conditional distribution variability measures for causality detection
January 25, 2016 ยท Declared Dead ยท ๐ Cause Effect Pairs in Machine Learning
"No code URL or promise found in abstract"
Evidence collected by the PWNC Scanner
Authors
Josรฉ A. R. Fonollosa
arXiv ID
1601.06680
Category
stat.ML: Machine Learning (Stat)
Cross-listed
cs.LG
Citations
50
Venue
Cause Effect Pairs in Machine Learning
Last Checked
3 months ago
Abstract
In this paper we derive variability measures for the conditional probability distributions of a pair of random variables, and we study its application in the inference of causal-effect relationships. We also study the combination of the proposed measures with standard statistical measures in the the framework of the ChaLearn cause-effect pair challenge. The developed model obtains an AUC score of 0.82 on the final test database and ranked second in the challenge.
Community Contributions
Found the code? Know the venue? Think something is wrong? Let us know!
๐ Similar Papers
In the same crypt โ Machine Learning (Stat)
๐ฎ
๐ฎ
The Ethereal
Layer Normalization
๐ฎ
๐ฎ
The Ethereal
Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles
R.I.P.
๐ป
Ghosted
Variational Inference with Normalizing Flows
๐
๐
The Cartographer
Towards A Rigorous Science of Interpretable Machine Learning
R.I.P.
๐ป
Ghosted
Optimization Methods for Large-Scale Machine Learning
Died the same way โ ๐ป Ghosted
R.I.P.
๐ป
Ghosted
Federated Learning: Strategies for Improving Communication Efficiency
R.I.P.
๐ป
Ghosted
In-Datacenter Performance Analysis of a Tensor Processing Unit
R.I.P.
๐ป
Ghosted
Deep Convolutional Neural Networks for Computer-Aided Detection: CNN Architectures, Dataset Characteristics and Transfer Learning
R.I.P.
๐ป
Ghosted