Bojan Karlas

Publication Activity (10 Years)

Years Active: 2016-2024
Publications (10 Years): 32

Top Topics

Nearest Neighbor Classifiers

Top Venues

Proc. VLDB Endow.

Publications

Bojan Karlas, David Dao, Matteo Interlandi, Sebastian Schelter, Wentao Wu, Ce Zhang
Data Debugging with Shapley Importance over Machine Learning Pipelines. ICLR (2024)
Sebastian Schelter, Stefan Grafberger, Shubha Guha, Bojan Karlas, Ce Zhang
Proactively Screening Machine Learning Pipelines with ARGUSEYES. SIGMOD Conference Companion (2023)
Maurice Weber, Xiaojun Xu, Bojan Karlas, Ce Zhang, Bo Li
RAB: Provable Robustness Against Backdoor Attacks. SP (2023)
Mark Mazumder, Colby R. Banbury, Xiaozhe Yao, Bojan Karlas, William Gaviria Rojas, Sudnya Frederick Diamos, Greg Diamos, Lynn He, Alicia Parrish, Hannah Rose Kirk, Jessica Quaye, Charvi Rastogi, Douwe Kiela, David Jurado, David Kanter, Rafael Mosquera, Will Cukierski, Juan Ciro, Lora Aroyo, Bilge Acun, Lingjiao Chen, Mehul Raje, Max Bartolo, Evan Sabri Eyuboglu, Amirata Ghorbani, Emmett D. Goodman, Addison Howard, Oana Inel, Tariq Kane, Christine R. Kirkpatrick, D. Sculley, Tzu-Sheng Kuo, Jonas W. Mueller, Tristan Thrush, Joaquin Vanschoren, Margaret Warren, Adina Williams, Serena Yeung, Newsha Ardalani, Praveen K. Paritosh, Ce Zhang, James Y. Zou, Carole-Jean Wu, Cody Coleman, Andrew Y. Ng, Peter Mattson, Vijay Janapa Reddi
DataPerf: Benchmarks for Data-Centric AI Development. NeurIPS (2023)
Luis Oala, Manil Maskey, Lilith Bat-Leah, Alicia Parrish, Nezihe Merve Gürel, Tzu-Sheng Kuo, Yang Liu, Rotem Dror, Danilo Brajovic, Xiaozhe Yao, Max Bartolo, William Gaviria Rojas, Ryan Hileman, Rainier Aliment, Michael W. Mahoney, Meg Risdal, Matthew Lease, Wojciech Samek, Debojyoti Dutta, Curtis G. Northcutt, Cody Coleman, Braden Hancock, Bernard Koch, Girmaw Abebe Tadesse, Bojan Karlas, Ahmed Alaa, Adji Bousso Dieng, Natasha F. Noy, Vijay Janapa Reddi, James Zou, Praveen K. Paritosh, Mihaela van der Schaar, Kurt D. Bollacker, Lora Aroyo, Ce Zhang, Joaquin Vanschoren, Isabelle Guyon, Peter Mattson
DMLR: Data-centric Machine Learning Research - Past, Present and Future. CoRR (2023)
Sebastian Schelter, Stefan Grafberger, Shubha Guha, Olivier Sprangers, Bojan Karlas, Ce Zhang
Screening Native Machine Learning Pipelines with ArgusEyes. CIDR (2022)
Mark Mazumder, Colby R. Banbury, Xiaozhe Yao, Bojan Karlas, William Gaviria Rojas, Sudnya Frederick Diamos, Greg Diamos, Lynn He, Douwe Kiela, David Jurado, David Kanter, Rafael Mosquera, Juan Ciro, Lora Aroyo, Bilge Acun, Sabri Eyuboglu, Amirata Ghorbani, Emmett D. Goodman, Tariq Kane, Christine R. Kirkpatrick, Tzu-Sheng Kuo, Jonas Mueller, Tristan Thrush, Joaquin Vanschoren, Margaret Warren, Adina Williams, Serena Yeung, Newsha Ardalani, Praveen K. Paritosh, Ce Zhang, James Zou, Carole-Jean Wu, Cody Coleman, Andrew Y. Ng, Peter Mattson, Vijay Janapa Reddi
DataPerf: Benchmarks for Data-Centric AI Development. CoRR (2022)
Bojan Karlas, David Dao, Matteo Interlandi, Bo Li, Sebastian Schelter, Wentao Wu, Ce Zhang
Data Debugging with Shapley Importance over End-to-End Machine Learning Pipelines. CoRR (2022)
Zhuolin Yang, Zhikuan Zhao, Boxin Wang, Jiawei Zhang, Linyi Li, Hengzhi Pei, Bojan Karlas, Ji Liu, Heng Guo, Ce Zhang, Bo Li
Improving Certified Robustness via Statistical Learning with Logical Reasoning. NeurIPS (2022)
Fotis Psallidas, Yiwen Zhu, Bojan Karlas, Jordan Henkel, Matteo Interlandi, Subru Krishnan, Brian Kroth, K. Venkatesh Emani, Wentao Wu, Ce Zhang, Markus Weimer, Avrilia Floratou, Carlo Curino, Konstantinos Karanasos
Data Science Through the Looking Glass: Analysis of Millions of GitHub Notebooks and ML.NET Pipelines. SIGMOD Rec. 51 (2) (2022)
Sabri Eyuboglu, Bojan Karlas, Christopher Ré, Ce Zhang, James Zou
dcbench: a benchmark for data-centric AI systems. DEEM@SIGMOD (2022)
Cédric Renggli, Luka Rimanic, Nezihe Merve Gürel, Bojan Karlas, Wentao Wu, Ce Zhang
A Data Quality-Driven View of MLOps. CoRR (2021)
Mohammad Reza Karimi, Nezihe Merve Gürel, Bojan Karlas, Johannes Rausch, Ce Zhang, Andreas Krause
Online Active Model Selection for Pre-trained Classifiers. AISTATS (2021)
Leonel Aguilar Melgar, David Dao, Shaoduo Gan, Nezihe Merve Gürel, Nora Hollenstein, Jiawei Jiang, Bojan Karlas, Thomas Lemmin, Tian Li, Yang Li, Xi Rao, Johannes Rausch, Cédric Renggli, Luka Rimanic, Maurice Weber, Shuai Zhang, Zhikuan Zhao, Kevin Schawinski, Wentao Wu, Ce Zhang
Ease.ML: A Lifecycle Management System for Machine Learning. CIDR (2021)
Cédric Renggli, Luka Rimanic, Nezihe Merve Gürel, Bojan Karlas, Wentao Wu, Ce Zhang
A Data Quality-Driven View of MLOps. IEEE Data Eng. Bull. 44 (1) (2021)
Zhuolin Yang, Zhikuan Zhao, Hengzhi Pei, Boxin Wang, Bojan Karlas, Ji Liu, Heng Guo, Bo Li, Ce Zhang
End-to-end Robustness for Sensing-Reasoning Machine Learning Pipelines. CoRR (2020)
Bojan Karlas, Peng Li, Renzhi Wu, Nezihe Merve Gürel, Xu Chu, Wentao Wu, Ce Zhang
Nearest Neighbor Classifiers over Incomplete Information: From Certain Answers to Certain Predictions. Proc. VLDB Endow. 14 (3) (2020)
Bojan Karlas, Peng Li, Renzhi Wu, Nezihe Merve Gürel, Xu Chu, Wentao Wu, Ce Zhang
Nearest Neighbor Classifiers over Incomplete Information: From Certain Answers to Certain Predictions. CoRR (2020)
Bojan Karlas, Matteo Interlandi, Cédric Renggli, Wentao Wu, Ce Zhang, Deepak Mukunthu Iyappan Babu, Jordan Edwards, Chris Lauren, Andy Xu, Markus Weimer
Building Continuous Integration Services for Machine Learning. KDD (2020)
Mohammad Reza Karimi, Nezihe Merve Gürel, Bojan Karlas, Johannes Rausch, Ce Zhang, Andreas Krause
Online Active Model Selection for Pre-trained Classifiers. CoRR (2020)
Maurice Weber, Xiaojun Xu, Bojan Karlas, Ce Zhang, Bo Li
RAB: Provable Robustness Against Backdoor Attacks. CoRR (2020)
Chen Yu, Bojan Karlas, Jie Zhong, Ce Zhang, Ji Liu
AutoML from Service Provider's Perspective: Multi-device, Multi-tenant Model Selection with GP-EI. AISTATS (2019)
Cédric Renggli, Bojan Karlas, Bolin Ding, Feng Liu, Kevin Schawinski, Wentao Wu, Ce Zhang
Continuous Integration of Machine Learning Models with ease.ml/ci: Towards a Rigorous Yet Practical Treatment. MLSys (2019)
Cédric Renggli, Frances Ann Hubis, Bojan Karlas, Kevin Schawinski, Wentao Wu, Ce Zhang
Ease.ml/ci and Ease.ml/meter in Action: Towards Data Management for Statistical Generalization. Proc. VLDB Endow. 12 (12) (2019)
Fotis Psallidas, Yiwen Zhu, Bojan Karlas, Matteo Interlandi, Avrilia Floratou, Konstantinos Karanasos, Wentao Wu, Ce Zhang, Subru Krishnan, Carlo Curino, Markus Weimer
Data Science through the looking glass and what we found there. CoRR (2019)
Vojislav Dukic, Sangeetha Abdu Jyothi, Bojan Karlas, Muhsen Owaida, Ce Zhang, Ankit Singla
Is advance knowledge of flow sizes a plausible assumption? NSDI (2019)
Cédric Renggli, Bojan Karlas, Bolin Ding, Feng Liu, Kevin Schawinski, Wentao Wu, Ce Zhang
Continuous Integration of Machine Learning Models with ease.ml/ci: Towards a Rigorous Yet Practical Treatment. CoRR (2019)
Vojislav Dukic, Sangeetha Abdu Jyothi, Bojan Karlas, Muhsen Owaida, Ce Zhang, Ankit Singla
Network Scheduling in the Dark. SoCC (2018)
Bojan Karlas, Ji Liu, Wentao Wu, Ce Zhang
Ease.ml in Action: Towards Multi-tenant Declarative Learning Services. Proc. VLDB Endow. 11 (12) (2018)
Chen Yu, Bojan Karlas, Jie Zhong, Ce Zhang, Ji Liu
Multi-device, Multi-tenant Model Selection with GP-EI. CoRR (2018)
Hamza Harkous, Rameez Rahman, Bojan Karlas, Karl Aberer
The Curious Case of the PDF Converter that Likes Mozart: Dissecting and Mitigating the Privacy Risk of Personal Cloud Apps. Proc. Priv. Enhancing Technol. 2016 (4) (2016)
Hamza Harkous, Rameez Rahman, Bojan Karlas, Karl Aberer
The Curious Case of the PDF Converter that Likes Mozart: Dissecting and Mitigating the Privacy Risk of Personal Cloud Apps. CoRR (2016)