Luka Rimanic

According to our database, Luka Rimanic authored at least 16 papers between 2020 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2023

Automatic Feasibility Study via Data Quality Analysis for ML: A Case-Study on Label Noise.

Cédric Renggli, Luka Rimanic, Luka Kolar, Wentao Wu, Ce Zhang

Proceedings of the 39th IEEE International Conference on Data Engineering, 2023

2022

SHiFT: An Efficient, Flexible Search Engine for Transfer Learning.

Cédric Renggli, Xiaozhe Yao, Luka Kolar, Luka Rimanic, Ana Klimovic, Ce Zhang

Proc. VLDB Endow., 2022

Fine-tuning Language Models over Slow Networks using Activation Compression with Guarantees.

Jue Wang, Binhang Yuan, Luka Rimanic, Yongjun He, Tri Dao, Beidi Chen, Christopher Ré, Ce Zhang

CoRR, 2022

Fine-tuning Language Models over Slow Networks using Activation Quantization with Guarantees.

Jue Wang, Binhang Yuan, Luka Rimanic, Yongjun He, Tri Dao, Beidi Chen, Christopher Ré, Ce Zhang

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Which Model to Transfer? Finding the Needle in the Growing Haystack.

Cédric Renggli, André Susano Pinto, Luka Rimanic, Joan Puigcerver, Carlos Riquelme, Ce Zhang, Mario Lucic

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

2021

A Data Quality-Driven View of MLOps.

Cédric Renggli, Luka Rimanic, Nezihe Merve Gürel, Bojan Karlas, Wentao Wu, Ce Zhang

IEEE Data Eng. Bull., 2021

Evaluating Bayes Error Estimators on Read-World Datasets with FeeBee.

Cédric Renggli, Luka Rimanic, Nora Hollenstein, Ce Zhang

CoRR, 2021

Evaluating Bayes Error Estimators on Real-World Datasets with FeeBee.

Cédric Renggli, Luka Rimanic, Nora Hollenstein, Ce Zhang

Proceedings of the Neural Information Processing Systems Track on Datasets and Benchmarks 1, 2021

Knowledge Enhanced Machine Learning Pipeline against Diverse Adversarial Attacks.

Nezihe Merve Gürel, Xiangyu Qi, Luka Rimanic, Ce Zhang, Bo Li

Proceedings of the 38th International Conference on Machine Learning, 2021

Ease.ML: A Lifecycle Management System for Machine Learning.

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

Proceedings of the 11th Conference on Innovative Data Systems Research, 2021

DataLens: Scalable Privacy Preserving Training via Gradient Compression and Aggregation.

Boxin Wang, Fan Wu, Yunhui Long, Luka Rimanic, Ce Zhang, Bo Li

Proceedings of the CCS '21: 2021 ACM SIGSAC Conference on Computer and Communications Security, Virtual Event, Republic of Korea, November 15, 2021

TSS: Transformation-Specific Smoothing for Robustness Certification.

Linyi Li, Maurice Weber, Xiaojun Xu, Luka Rimanic, Bhavya Kailkhura, Tao Xie, Ce Zhang, Bo Li

Proceedings of the CCS '21: 2021 ACM SIGSAC Conference on Computer and Communications Security, Virtual Event, Republic of Korea, November 15, 2021

2020

Ease.ml/snoopy in Action: Towards Automatic Feasibility Analysis for Machine Learning Application Development.

Cédric Renggli, Luka Rimanic, Luka Kolar, Wentao Wu, Ce Zhang

Proc. VLDB Endow., 2020

On Automatic Feasibility Study for Machine Learning Application Development with ease.ml/snoopy.

Cédric Renggli, Luka Rimanic, Luka Kolar, Nora Hollenstein, Wentao Wu, Ce Zhang

CoRR, 2020

Provable Robust Learning Based on Transformation-Specific Smoothing.

Linyi Li, Maurice Weber, Xiaojun Xu, Luka Rimanic, Tao Xie, Ce Zhang, Bo Li

CoRR, 2020

On Convergence of Nearest Neighbor Classifiers over Feature Transformations.

Luka Rimanic, Cédric Renggli, Bo Li, Ce Zhang

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020