Soroush Aramideh

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All published works

Action	Title	Year	Authors
+	Monotone Tree-Based GAMI Models by Adapting XGBoost	2023	Linwei Hu Soroush Aramideh Jie Chen Vijayan N. Nair
+ PDF Chat	Supervised Machine Learning Techniques: An Overview with Applications to Banking	2021	Linwei Hu Jie Chen Joel Vaughan Soroush Aramideh Hanyu Yang Kelly Wang Agus Sudjianto Vijayan N. Nair

Common Coauthors

Coauthor	Papers Together
Vijayan N. Nair	2
Linwei Hu	2
Joel Vaughan	1
Agus Sudjianto	1
Jie Chen	1
Hanyu Yang	1
Jie Chen	1
Kelly Wang	1

Commonly Cited References

Action	Title	Year	Authors	# of times referenced
+ PDF Chat	Fifty Years of Classification and Regression Trees	2014	Wei‐Yin Loh	1
+	A new derivative based importance criterion for groups of variables and its link with the global sensitivity indices	2010	I. M. Sobol Sergei Kucherenko	1
+	Predictive learning via rule ensembles	2008	Jerome H. Friedman Bogdan Popescu	1
+	Stochastic gradient boosting	2002	Jerome H. Friedman	1
+ PDF Chat	Statistical Modeling: The Two Cultures (with comments and a rejoinder by the author)	2001	Leo Breiman	1
+ PDF Chat	Projection Pursuit Regression	1981	Jerome H. Friedman Werner Stuetzle	1
+	Global sensitivity indices for nonlinear mathematical models and their Monte Carlo estimates	2001	I. M. Sobol	1
+ PDF Chat	Unbiased Recursive Partitioning: A Conditional Inference Framework	2006	Torsten Hothorn Kurt Hornik Achim Zeileis	1
+ PDF Chat	Peeking Inside the Black Box: Visualizing Statistical Learning With Plots of Individual Conditional Expectation	2014	Alex Goldstein Adam Kapelner Justin Bleich Emil Pitkin	1
+	An Exploratory Technique for Investigating Large Quantities of Categorical Data	1980	Gordon V. Kass	1
+ PDF Chat	Deep Residual Learning for Image Recognition	2016	Kaiming He Xiangyu Zhang Shaoqing Ren Jian Sun	1
+ PDF Chat	Layer-Wise Relevance Propagation for Neural Networks with Local Renormalization Layers	2016	Alexander Binder Grégoire Montavon Sebastian Lapuschkin Klaus‐Robert Müller Wojciech Samek	1
+	Axiomatic Attribution for Deep Networks	2017	Mukund Sundararajan Ankur Taly Qiqi Yan	1
+	Learning Important Features Through Propagating Activation Differences	2017	Avanti Shrikumar Peyton Greenside Anshul Kundaje	1
+ PDF Chat	The Elements of Statistical Learning	2009	Trevor Hastie Robert Tibshirani Jerome H. Friedman	1
+	Explainable Neural Networks based on Additive Index Models	2018	Joel Vaughan Agus Sudjianto Erind Brahimi Jie Chen Vijayan N. Nair	1
+	Learning Single Index Models in Gaussian Space	2018	Rishabh Dudeja Daniel Hsu	1
+	A Unified Approach to Interpreting Model Predictions	2017	Scott Lundberg Su‐In Lee	1
+ PDF Chat	Distribution-Free Predictive Inference for Regression	2017	Jing Lei Max G’Sell Alessandro Rinaldo Ryan J. Tibshirani Larry Wasserman	1
+ PDF Chat	Explainable Artificial Intelligence (XAI): Concepts, taxonomies, opportunities and challenges toward responsible AI	2019	Alejandro Barredo Arrieta Natalia Díaz-Rodríguez Javier Del Ser Adrien Bennetot Siham Tabik Alberto Barbado Salvador García Sergio Gil-López Daniel Molina Richard Benjamins	1
+	Adaptive Explainable Neural Networks (AxNNs)	2020	Jie Chen Joel Vaughan Vijayan N. Nair Agus Sudjianto	1
+ PDF Chat	Visualizing the Effects of Predictor Variables in Black Box Supervised Learning Models	2020	Daniel W. Apley Jingyu Zhu	1
+	Surrogate Locally-Interpretable Models with Supervised Machine Learning Algorithms	2020	Linwei Hu Jie Chen Vijayan N. Nair Agus Sudjianto	1
+	XGBoost	2016	Tianqi Chen Carlos Guestrin	1
+ PDF Chat	Adaptive Explainable Neural Networks (Axnns)	2020	Jie Chen Joel Vaughan Vijay Nair Agus Sudjianto	1
+ PDF Chat	Bagging predictors	1996	Leo Breiman	1