The document discusses data programming, which uses labeling functions created by domain experts to quickly generate large training datasets. It describes how labeling functions work independently to label examples, and a generative model is used to determine the accuracy of each function and estimate true labels. Dependencies between functions can also be modeled to improve accuracy. Experimental results show data programming outperforms other techniques in generating training data.

1. Data Programming:
Creating Large Training Sets, Quickly
Recruit Communications, Engineer
Kotaro Tanahashi
Alexander Ratner, Christopher De Sa, Sen Wu, Daniel Selsam, Christopher Ré
Stanford University
NIPS 2016, reading meet up

2. [https://www.youtube.com/watch?v=iSQHelJ1xxU]
ML model requires lots of training data
Problem:

3. [https://www.youtube.com/watch?v=iSQHelJ1xxU]
💡Key Idea: using labeling function created by domain experts

4. Examples of Labeling Function

6. Independent Labeling Functions
λ is true λ is false λ gives no label
family of generative model
αi : probability labeling the object correctly
βi : probability labeling an object
determine α, β by MAP estimation

7. Training of w
final goal is training w in
optimal w is obtained by
f(x) : arbitrary feature mapping
noise-aware empirical risk

8. [https://www.youtube.com/watch?v=iSQHelJ1xxU]

9. Handling Dependencies
In some cases, the dependency among labeling functions
is obvious like
considering the dependency can improve accuracy
fix: whenever λ2 labels, λ1 labels
when λ1,λ2 disagree, λ2 is correct
reinforce: when λ1,λ2 typically agree

10. Generalization of Generative Model
λ is true λ is false λ gives no label
generalize
h is a factor function
α, β → θ

11. Represent Dependency by h
For a fixing dependency
whenever λj labels, λi labels
λj is true and λi is false
θ
Training procedure is same as before

12. Experimental Results
coverage: % of #label > 0
overlap: % of #label > 1
|S|: #generated label
Data Programing outperforms LSTM

13. [https://www.youtube.com/watch?v=iSQHelJ1xxU]

14. RCO tech-blog
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