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Nesime Tatbul
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Publications
- 2022
- [j30]Abdul Wasay, Nesime Tatbul, Justin Gottschlich:
Machine Programming: Turning Data into Programmer Productivity. Proc. VLDB Endow. 15(12): 3754-3757 (2022) - 2020
- [i10]Fangke Ye, Shengtian Zhou, Anand Venkat, Ryan Marcus, Nesime Tatbul, Jesmin Jahan Tithi, Paul Petersen, Timothy G. Mattson, Tim Kraska, Pradeep Dubey, Vivek Sarkar, Justin Gottschlich:
MISIM: An End-to-End Neural Code Similarity System. CoRR abs/2006.05265 (2020) - [i8]Akhilesh Gupta, Nesime Tatbul, Ryan Marcus, Shengtian Zhou, Insup Lee, Justin Gottschlich:
Class-Weighted Evaluation Metrics for Imbalanced Data Classification. CoRR abs/2010.05995 (2020) - 2019
- [c46]Mejbah Alam, Justin Gottschlich, Nesime Tatbul, Javier S. Turek, Tim Mattson, Abdullah Muzahid:
A Zero-Positive Learning Approach for Diagnosing Software Performance Regressions. NeurIPS 2019: 11623-11635 - 2018
- [c43]Nesime Tatbul, Tae Jun Lee, Stan Zdonik, Mejbah Alam, Justin Gottschlich:
Precision and Recall for Time Series. NeurIPS 2018: 1924-1934 - [c42]Justin Gottschlich, Armando Solar-Lezama, Nesime Tatbul, Michael Carbin, Martin C. Rinard, Regina Barzilay, Saman P. Amarasinghe, Joshua B. Tenenbaum, Tim Mattson:
The three pillars of machine programming. MAPL@PLDI 2018: 69-80 - [i5]Tae-Jun Lee, Justin Gottschlich, Nesime Tatbul, Eric Metcalf, Stan Zdonik:
Greenhouse: A Zero-Positive Machine Learning System for Time-Series Anomaly Detection. CoRR abs/1801.03168 (2018) - [i4]Tae Jun Lee, Justin Gottschlich, Nesime Tatbul, Eric Metcalf, Stan Zdonik:
Precision and Recall for Range-Based Anomaly Detection. CoRR abs/1801.03175 (2018) - [i3]Nesime Tatbul, Tae Jun Lee, Stan Zdonik, Justin Gottschlich:
A New Model for Evaluating Range-Based Anomaly Detection Algorithms. CoRR abs/1803.03639 (2018) - [i2]Justin Gottschlich, Armando Solar-Lezama, Nesime Tatbul, Michael Carbin, Martin C. Rinard, Regina Barzilay, Saman P. Amarasinghe, Joshua B. Tenenbaum, Tim Mattson:
The Three Pillars of Machine-Based Programming. CoRR abs/1803.07244 (2018)
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