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ORCIDJerome H. Friedman
Person information
- affiliation: Stanford University, Stanford, USA
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2020 – today
- 2024
[i5]Jerome H. Friedman:
Function Trees: Transparent Machine Learning. CoRR abs/2403.13141 (2024)- 2022
- [j14]Gilmer Valdes
, Jerome H. Friedman, Fei Jiang, Efstathios D. Gennatas:
Representational Gradient Boosting: Backpropagation in the Space of Functions. IEEE Trans. Pattern Anal. Mach. Intell. 44(12): 10186-10195 (2022) - 2021
- [i4]Gilmer Valdes, Wilmer Arbelo, Yannet Interian, Jerome H. Friedman:
Lockout: Sparse Regularization of Neural Networks. CoRR abs/2107.07160 (2021) - 2020
- [i3]Jerome H. Friedman:
Predicting Regression Probability Distributions with Imperfect Data Through Optimal Transformations. CoRR abs/2001.10102 (2020)
2010 – 2019
- 2019
- [i2]Efstathios D. Gennatas, Jerome H. Friedman, Lyle H. Ungar, Romain Pirracchio, Eric Eaton, L. Reichman, Yannet Interian, Charles B. Simone II, A. Auerbach, E. Delgado, Mark J. van der Laan, Timothy D. Solberg, Gilmer Valdes:
Expert-Augmented Machine Learning. CoRR abs/1903.09731 (2019) - [i1]Jerome H. Friedman:
Contrast Trees and Distribution Boosting. CoRR abs/1912.03785 (2019) - 2017
- [j13]Maarten M. Kampert, Jacqueline J. Meulman, Jerome H. Friedman:
rCOSA: A Software Package for Clustering Objects on Subsets of Attributes. J. Classif. 34(3): 514-547 (2017) - 2016
- [j12]Eugene Dubossarsky, Jerome H. Friedman, John T. Ormerod, Matthew P. Wand:
Wavelet-based gradient boosting. Stat. Comput. 26(1-2): 93-105 (2016)
2000 – 2009
- 2009
- [b2]Trevor Hastie, Robert Tibshirani, Jerome H. Friedman:
The Elements of Statistical Learning: Data Mining, Inference, and Prediction, 2nd Edition. Springer Series in Statistics, Springer 2009, ISBN 9780387848570, pp. I-XXII, 1-745 - 2008
- [c6]Vito Di Gesù, Giosuè Lo Bosco, Jerome H. Friedman:
Intruders pattern identification. ICPR 2008: 1-4 - [c5]Trevor Hastie, Jerome H. Friedman, Robert Tibshirani:
Regularization paths and coordinate descent. KDD 2008: 3 - 2006
- [j11]Jerome H. Friedman:
Recent Advances in Predictive (Machine) Learning. J. Classif. 23(2): 175-197 (2006) - 2005
- [c4]Vito Di Gesù, Jerome H. Friedman:
New Similarity Rules for Mining Data. WIRN/NAIS 2005: 179-187 - 2003
- [j10]Trevor Hastie, Robert Tibshirani, Jerome H. Friedman:
Note on "Comparison of Model Selection for Regression" by Vladimir Cherkassky and Yunqian Ma. Neural Comput. 15(7): 1477-1480 (2003) - 2001
- [b1]Trevor Hastie, Jerome H. Friedman, Robert Tibshirani:
The Elements of Statistical Learning: Data Mining, Inference, and Prediction. Springer Series in Statistics, Springer 2001, ISBN 978-1-4899-0519-2, pp. 1-536
1990 – 1999
- 1999
- [j9]Jerome H. Friedman, Nicholas I. Fisher:
Bump hunting in high-dimensional data. Stat. Comput. 9(2): 123-143 (1999) - 1997
- [j8]Jerome H. Friedman:
On Bias, Variance, 0/1-Loss, and the Curse-of-Dimensionality. Data Min. Knowl. Discov. 1(1): 55-77 (1997) - 1996
- [c3]Jerome H. Friedman, Ron Kohavi, Yeogirl Yun:
Lazy Decision Trees. AAAI/IAAI, Vol. 1 1996: 717-724 - 1990
- [c2]Jerome H. Friedman:
Adaptive Spline Networks. NIPS 1990: 675-683
1980 – 1989
- 1981
- [j7]Jerome H. Friedman, Margaret H. Wright:
A Nested Partitioning Procedure for Numerical Multiple Integration. ACM Trans. Math. Softw. 7(1): 76-92 (1981)
1970 – 1979
- 1979
- [j6]Jon Louis Bentley, Jerome H. Friedman:
Data Structures for Range Searching. ACM Comput. Surv. 11(4): 397-409 (1979) - 1978
- [j5]Jon Louis Bentley, Jerome H. Friedman:
Fast Algorithms for Constructing Minimal Spanning Trees in Coordinate Spaces. IEEE Trans. Computers 27(2): 97-105 (1978) - 1977
- [j4]Jerome H. Friedman:
A Recursive Partitioning Decision Rule for Nonparametric Classification. IEEE Trans. Computers 26(4): 404-408 (1977) - [j3]Jerome H. Friedman, Jon Louis Bentley, Raphael A. Finkel:
An Algorithm for Finding Best Matches in Logarithmic Expected Time. ACM Trans. Math. Softw. 3(3): 209-226 (1977) - 1975
- [j2]Jerome H. Friedman, Forest Baskett, Leonard J. Shustek:
An Algorithm for Finding Nearest Neighbors. IEEE Trans. Computers 24(10): 1000-1006 (1975) - [c1]Mary Anne Fisherkeller, Jerome H. Friedman, John W. Tukey:
PRIM-9: An Interactive Multi-dimensional Data Display and Analysis System. ACM Pacific 1975: 140-145 - 1974
- [j1]Jerome H. Friedman, John W. Tukey:
A Projection Pursuit Algorithm for Exploratory Data Analysis. IEEE Trans. Computers 23(9): 881-890 (1974)
Coauthor Index
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