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ORCIDLuka Rimanic
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2020 – today
- 2023
[c9]Cédric Renggli, Luka Rimanic, Luka Kolar, Wentao Wu
, Ce Zhang:
Automatic Feasibility Study via Data Quality Analysis for ML: A Case-Study on Label Noise. ICDE 2023: 218-231- 2022
- [j3]Cédric Renggli, Xiaozhe Yao, Luka Kolar, Luka Rimanic, Ana Klimovic, Ce Zhang:
SHiFT: An Efficient, Flexible Search Engine for Transfer Learning. Proc. VLDB Endow. 16(2): 304-316 (2022) - [c8]Cédric Renggli, André Susano Pinto, Luka Rimanic, Joan Puigcerver, Carlos Riquelme, Ce Zhang, Mario Lucic:
Which Model to Transfer? Finding the Needle in the Growing Haystack. CVPR 2022: 9195-9204 - [c7]Jue Wang, Binhang Yuan, Luka Rimanic, Yongjun He, Tri Dao, Beidi Chen, Christopher Ré, Ce Zhang:
Fine-tuning Language Models over Slow Networks using Activation Quantization with Guarantees. NeurIPS 2022 - [i10]Cédric Renggli, Xiaozhe Yao, Luka Kolar, Luka Rimanic, Ana Klimovic, Ce Zhang:
SHiFT: An Efficient, Flexible Search Engine for Transfer Learning. CoRR abs/2204.01457 (2022) - [i9]Jue Wang, Binhang Yuan, Luka Rimanic, Yongjun He, Tri Dao, Beidi Chen, Christopher Ré, Ce Zhang:
Fine-tuning Language Models over Slow Networks using Activation Compression with Guarantees. CoRR abs/2206.01299 (2022) - 2021
- [j2]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): 11-23 (2021) - [c6]Linyi Li, Maurice Weber, Xiaojun Xu, Luka Rimanic, Bhavya Kailkhura, Tao Xie, Ce Zhang, Bo Li:
TSS: Transformation-Specific Smoothing for Robustness Certification. CCS 2021: 535-557 - [c5]Boxin Wang, Fan Wu, Yunhui Long, Luka Rimanic, Ce Zhang, Bo Li:
DataLens: Scalable Privacy Preserving Training via Gradient Compression and Aggregation. CCS 2021: 2146-2168 - [c4]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:
Ease.ML: A Lifecycle Management System for Machine Learning. CIDR 2021 - [c3]Nezihe Merve Gürel, Xiangyu Qi, Luka Rimanic, Ce Zhang, Bo Li:
Knowledge Enhanced Machine Learning Pipeline against Diverse Adversarial Attacks. ICML 2021: 3976-3987 - [c2]Cédric Renggli, Luka Rimanic, Nora Hollenstein, Ce Zhang:
Evaluating Bayes Error Estimators on Real-World Datasets with FeeBee. NeurIPS Datasets and Benchmarks 2021 - [i8]Cédric Renggli, Luka Rimanic, Nezihe Merve Gürel, Bojan Karlas, Wentao Wu, Ce Zhang:
A Data Quality-Driven View of MLOps. CoRR abs/2102.07750 (2021) - [i7]Boxin Wang, Fan Wu, Yunhui Long, Luka Rimanic, Ce Zhang, Bo Li:
DataLens: Scalable Privacy Preserving Training via Gradient Compression and Aggregation. CoRR abs/2103.11109 (2021) - [i6]Nezihe Merve Gürel, Xiangyu Qi, Luka Rimanic, Ce Zhang, Bo Li:
Knowledge Enhanced Machine Learning Pipeline against Diverse Adversarial Attacks. CoRR abs/2106.06235 (2021) - [i5]Cédric Renggli, Luka Rimanic, Nora Hollenstein, Ce Zhang:
Evaluating Bayes Error Estimators on Read-World Datasets with FeeBee. CoRR abs/2108.13034 (2021) - 2020
- [j1]Cédric Renggli, Luka Rimanic, Luka Kolar, Wentao Wu, Ce Zhang:
Ease.ml/snoopy in Action: Towards Automatic Feasibility Analysis for Machine Learning Application Development. Proc. VLDB Endow. 13(12): 2837-2840 (2020) - [c1]Luka Rimanic, Cédric Renggli, Bo Li, Ce Zhang:
On Convergence of Nearest Neighbor Classifiers over Feature Transformations. NeurIPS 2020 - [i4]Linyi Li, Maurice Weber, Xiaojun Xu, Luka Rimanic, Tao Xie, Ce Zhang, Bo Li:
Provable Robust Learning Based on Transformation-Specific Smoothing. CoRR abs/2002.12398 (2020) - [i3]Cédric Renggli, André Susano Pinto, Luka Rimanic, Joan Puigcerver, Carlos Riquelme, Ce Zhang, Mario Lucic:
Which Model to Transfer? Finding the Needle in the Growing Haystack. CoRR abs/2010.06402 (2020) - [i2]Luka Rimanic, Cédric Renggli, Bo Li, Ce Zhang:
On Convergence of Nearest Neighbor Classifiers over Feature Transformations. CoRR abs/2010.07765 (2020) - [i1]Cédric Renggli, Luka Rimanic, Luka Kolar, Nora Hollenstein, Wentao Wu, Ce Zhang:
On Automatic Feasibility Study for Machine Learning Application Development with ease.ml/snoopy. CoRR abs/2010.08410 (2020)
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