Luka Rimanic

Publication Activity (10 Years)

Years Active: 2020-2023
Publications (10 Years): 22

Top Topics

Nearest Neighbor Classifiers

Application Development

Machine Learning

Top Venues

Proc. VLDB Endow.

Publications

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)
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)
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) (2022)
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)
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 (2022)
Cédric Renggli, Xiaozhe Yao, Luka Kolar, Luka Rimanic, Ana Klimovic, Ce Zhang
SHiFT: An Efficient, Flexible Search Engine for Transfer Learning. CoRR (2022)
Cédric Renggli, Luka Rimanic, Nora Hollenstein, Ce Zhang
Evaluating Bayes Error Estimators on Read-World Datasets with FeeBee. CoRR (2021)
Nezihe Merve Gürel, Xiangyu Qi, Luka Rimanic, Ce Zhang, Bo Li
Knowledge Enhanced Machine Learning Pipeline against Diverse Adversarial Attacks. CoRR (2021)
Boxin Wang, Fan Wu, Yunhui Long, Luka Rimanic, Ce Zhang, Bo Li
DataLens: Scalable Privacy Preserving Training via Gradient Compression and Aggregation. CoRR (2021)
Cédric Renggli, Luka Rimanic, Nora Hollenstein, Ce Zhang
Evaluating Bayes Error Estimators on Real-World Datasets with FeeBee. NeurIPS Datasets and Benchmarks (2021)
Cédric Renggli, Luka Rimanic, Nezihe Merve Gürel, Bojan Karlas, Wentao Wu, Ce Zhang
A Data Quality-Driven View of MLOps. CoRR (2021)
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)
Boxin Wang, Fan Wu, Yunhui Long, Luka Rimanic, Ce Zhang, Bo Li
DataLens: Scalable Privacy Preserving Training via Gradient Compression and Aggregation. CCS (2021)
Nezihe Merve Gürel, Xiangyu Qi, Luka Rimanic, Ce Zhang, Bo Li
Knowledge Enhanced Machine Learning Pipeline against Diverse Adversarial Attacks. ICML (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)
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 (2020)
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 (2020)
Linyi Li, Maurice Weber, Xiaojun Xu, Luka Rimanic, Tao Xie, Ce Zhang, Bo Li
Provable Robust Learning Based on Transformation-Specific Smoothing. CoRR (2020)
Luka Rimanic, Cédric Renggli, Bo Li, Ce Zhang
On Convergence of Nearest Neighbor Classifiers over Feature Transformations. NeurIPS (2020)
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) (2020)
Luka Rimanic, Cédric Renggli, Bo Li, Ce Zhang
On Convergence of Nearest Neighbor Classifiers over Feature Transformations. CoRR (2020)