Nezihe Merve Gürel

36 papers A* 6A 4B 2Journal 22Unranked 1

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	Active Model Selection for Large Language Models. CoRR Yavuz Durmazkeser, Patrik Okanovic, Andreas Kirsch, Torsten Hoefler, Nezihe Merve Gürel
2025	A	`conf`	All models are wrong, some are useful: Model Selection with Limited Labels. AISTATS Patrik Okanovic, Andreas Kirsch, Jannes Kasper, Torsten Hoefler, Andreas Krause, Nezihe Merve Gürel
2025	J	`jnl`	Evaluating the Limits of Large Language Models in Multilingual Legal Reasoning. CoRR Antreas Ioannou, Andreas Shiamishis, Nora Hollenstein, Nezihe Merve Gürel
2024	J	`jnl`	All models are wrong, some are useful: Model Selection with Limited Labels. CoRR Patrik Okanovic, Andreas Kirsch, Jannes Kasper, Torsten Hoefler, Andreas Krause, Nezihe Merve Gürel
2024	A*	`conf`	C-RAG: Certified Generation Risks for Retrieval-Augmented Language Models. ICML Mintong Kang, Nezihe Merve Gürel, Ning Yu, Dawn Song, Bo Li
2024	J	`jnl`	C-RAG: Certified Generation Risks for Retrieval-Augmented Language Models. CoRR Mintong Kang, Nezihe Merve Gürel, Ning Yu, Dawn Song, Bo Li
2024	A*	`conf`	COLEP: Certifiably Robust Learning-Reasoning Conformal Prediction via Probabilistic Circuits. ICLR Mintong Kang, Nezihe Merve Gürel, Linyi Li, Bo Li
2024	J	`jnl`	COLEP: Certifiably Robust Learning-Reasoning Conformal Prediction via Probabilistic Circuits. CoRR Mintong Kang, Nezihe Merve Gürel, Linyi Li, Bo Li
2024	B	`conf`	Collaboratively Learning Federated Models from Noisy Decentralized Data. IEEE Big Data Haoyuan Li, Mathias Funk, Nezihe Merve Gürel, Aaqib Saeed
2024	J	`jnl`	Collaboratively Learning Federated Models from Noisy Decentralized Data. CoRR Haoyuan Li, Mathias Funk, Nezihe Merve Gürel, Aaqib Saeed
2024	J	`jnl`	DMLR: Data-centric Machine Learning Research - Past, Present and Future. J. Data-centric Mach. Learn. Res. 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 Bollacker, Lora Aroyo, Ce Zhang, Joaquin Vanschoren, Isabelle Guyon, Peter Mattson
2024	A*	`conf`	Repeated Random Sampling for Minimizing the Time-to-Accuracy of Learning. ICLR Patrik Okanovic, Roger Waleffe, Vasilis Mageirakos, Konstantinos E. Nikolakakis, Amin Karbasi, Dionysios S. Kalogerias, Nezihe Merve Gürel, Theodoros Rekatsinas
2023	J	`jnl`	DMLR: Data-centric Machine Learning Research - Past, Present and Future. CoRR 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 M. Alaa, Adji Bousso Dieng, Natasha F. Noy, Vijay Janapa Reddi, James Zou, Praveen K. Paritosh, Mihaela van der Schaar, Kurt Bollacker, Lora Aroyo, Ce Zhang, Joaquin Vanschoren, Isabelle Guyon, Peter Mattson
2023	J	`jnl`	Repeated Random Sampling for Minimizing the Time-to-Accuracy of Learning. CoRR Patrik Okanovic, Roger Waleffe, Vasilis Mageirakos, Konstantinos E. Nikolakakis, Amin Karbasi, Dionysios S. Kalogerias, Nezihe Merve Gürel, Theodoros Rekatsinas
2022	—	`—`	Advancing Cost Efficiency and Robustness of Machine Learning through the Lens of Data. Nezihe Merve Gürel
2021	J	`jnl`	A Data Quality-Driven View of MLOps. CoRR Cédric Renggli, Luka Rimanic, Nezihe Merve Gürel, Bojan Karlas, Wentao Wu, Ce Zhang
2021	J	`jnl`	A Data Quality-Driven View of MLOps. IEEE Data Eng. Bull. Cédric Renggli, Luka Rimanic, Nezihe Merve Gürel, Bojan Karlas, Wentao Wu, Ce Zhang
2021	A*	`conf`	DeGNN: Improving Graph Neural Networks with Graph Decomposition. KDD Xupeng Miao, Nezihe Merve Gürel, Wentao Zhang, Zhichao Han, Bo Li, Wei Min, Susie Xi Rao, Hansheng Ren, Yinan Shan, Yingxia Shao, Yujie Wang, Fan Wu, Hui Xue, Yaming Yang, Zitao Zhang, Yang Zhao, Shuai Zhang, Yujing Wang, Bin Cui, Ce Zhang
2021	A	`conf`	Ease.ML: A Lifecycle Management System for Machine Learning. CIDR Leonel Aguilar Melgar, David Dao, Shaoduo Gan, Nezihe Merve Gürel, Nora Hollenstein, Jiawei Jiang, Bojan Karlas, Thomas Lemmin, Tian Li, Yang Li, Susie Xi Rao, Johannes Rausch, Cédric Renggli, Luka Rimanic, Maurice Weber, Shuai Zhang, Zhikuan Zhao, Kevin Schawinski, Wentao Wu, Ce Zhang
2021	A*	`conf`	FIVES: Feature Interaction Via Edge Search for Large-Scale Tabular Data. KDD Yuexiang Xie, Zhen Wang, Yaliang Li, Bolin Ding, Nezihe Merve Gürel, Ce Zhang, Minlie Huang, Wei Lin, Jingren Zhou
2021	A*	`conf`	Knowledge Enhanced Machine Learning Pipeline against Diverse Adversarial Attacks. ICML Nezihe Merve Gürel, Xiangyu Qi, Luka Rimanic, Ce Zhang, Bo Li
2021	J	`jnl`	Knowledge Enhanced Machine Learning Pipeline against Diverse Adversarial Attacks. CoRR Nezihe Merve Gürel, Xiangyu Qi, Luka Rimanic, Ce Zhang, Bo Li
2021	A	`conf`	Online Active Model Selection for Pre-trained Classifiers. AISTATS Mohammad Reza Karimi, Nezihe Merve Gürel, Bojan Karlas, Johannes Rausch, Ce Zhang, Andreas Krause
2020	J	`jnl`	Compressive Sensing Using Iterative Hard Thresholding With Low Precision Data Representation: Theory and Applications. IEEE Trans. Signal Process. Nezihe Merve Gürel, Kaan Kara, Alen Stojanov, Tyler M. Smith, Thomas Lemmin, Dan Alistarh, Markus Püschel, Ce Zhang
2020	J	`jnl`	Interactive Feature Generation via Learning Adjacency Tensor of Feature Graph. CoRR Yuexiang Xie, Zhen Wang, Yaliang Li, Bolin Ding, Nezihe Merve Gürel, Ce Zhang, Minlie Huang, Wei Lin, Jingren Zhou
2020	J	`jnl`	Nearest Neighbor Classifiers over Incomplete Information: From Certain Answers to Certain Predictions. CoRR Bojan Karlas, Peng Li, Renzhi Wu, Nezihe Merve Gürel, Xu Chu, Wentao Wu, Ce Zhang
2020	J	`jnl`	Nearest Neighbor Classifiers over Incomplete Information: From Certain Answers to Certain Predictions. Proc. VLDB Endow. Bojan Karlas, Peng Li, Renzhi Wu, Nezihe Merve Gürel, Xu Chu, Wentao Wu, Ce Zhang
2020	J	`jnl`	Online Active Model Selection for Pre-trained Classifiers. CoRR Mohammad Reza Karimi, Nezihe Merve Gürel, Bojan Karlas, Johannes Rausch, Ce Zhang, Andreas Krause
2019	J	`jnl`	An Anatomy of Graph Neural Networks Going Deep via the Lens of Mutual Information: Exponential Decay vs. Full Preservation. CoRR Nezihe Merve Gürel, Hansheng Ren, Yujing Wang, Hui Xue, Yaming Yang, Ce Zhang
2019	J	`jnl`	Efficient Task-Specific Data Valuation for Nearest Neighbor Algorithms. CoRR Ruoxi Jia, David Dao, Boxin Wang, Frances Ann Hubis, Nezihe Merve Gürel, Bo Li, Ce Zhang, Costas J. Spanos, Dawn Song
2019	J	`jnl`	Efficient Task-Specific Data Valuation for Nearest Neighbor Algorithms. Proc. VLDB Endow. Ruoxi Jia, David Dao, Boxin Wang, Frances Ann Hubis, Nezihe Merve Gürel, Bo Li, Ce Zhang, Costas J. Spanos, Dawn Song
2019	A	`conf`	Towards Efficient Data Valuation Based on the Shapley Value. AISTATS Ruoxi Jia, David Dao, Boxin Wang, Frances Ann Hubis, Nick Hynes, Nezihe Merve Gürel, Bo Li, Ce Zhang, Dawn Song, Costas J. Spanos
2019	J	`jnl`	Towards Efficient Data Valuation Based on the Shapley Value. CoRR Ruoxi Jia, David Dao, Boxin Wang, Frances Ann Hubis, Nick Hynes, Nezihe Merve Gürel, Bo Li, Ce Zhang, Dawn Song, Costas J. Spanos
2018	J	`jnl`	Compressive Sensing with Low Precision Data Representation: Radio Astronomy and Beyond. CoRR Nezihe Merve Gürel, Kaan Kara, Dan Alistarh, Ce Zhang
2018	—	`conf`	Towards More Accurate Radio Telescope Images. CVPR Workshops Nezihe Merve Gürel
2017	B	`conf`	Denoising radio interferometric images by subspace clustering. ICIP Nezihe Merve Gürel, Paul Hurley, Matthieu Simeoni