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A Theory of Statistical Inference for Ensuring the Robustness of
  Scientific Results

A Theory of Statistical Inference for Ensuring the Robustness of Scientific Results

23 April 2018
Beau Coker
Cynthia Rudin
Gary King
ArXivPDFHTML

Papers citing "A Theory of Statistical Inference for Ensuring the Robustness of Scientific Results"

6 / 6 papers shown
Title
The Curious Case of Arbitrariness in Machine Learning
Prakhar Ganesh
Afaf Taik
G. Farnadi
59
2
0
28 Jan 2025
Amazing Things Come From Having Many Good Models
Amazing Things Come From Having Many Good Models
Cynthia Rudin
Chudi Zhong
Lesia Semenova
Margo Seltzer
Ronald E. Parr
Jiachang Liu
Srikar Katta
Jon Donnelly
Harry Chen
Zachery Boner
28
23
0
05 Jul 2024
Exploring and Interacting with the Set of Good Sparse Generalized
  Additive Models
Exploring and Interacting with the Set of Good Sparse Generalized Additive Models
Chudi Zhong
Zhi Chen
Jiachang Liu
Margo Seltzer
Cynthia Rudin
33
11
0
28 Mar 2023
On the Existence of Simpler Machine Learning Models
On the Existence of Simpler Machine Learning Models
Lesia Semenova
Cynthia Rudin
Ronald E. Parr
26
85
0
05 Aug 2019
Variable Importance Clouds: A Way to Explore Variable Importance for the
  Set of Good Models
Variable Importance Clouds: A Way to Explore Variable Importance for the Set of Good Models
Jiayun Dong
Cynthia Rudin
FAtt
18
25
0
10 Jan 2019
Learning Certifiably Optimal Rule Lists for Categorical Data
Learning Certifiably Optimal Rule Lists for Categorical Data
E. Angelino
Nicholas Larus-Stone
Daniel Alabi
Margo Seltzer
Cynthia Rudin
60
195
0
06 Apr 2017
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