Szemerédi's Theorem in the Primes von Rimanić, Luka, Wolf, Julia

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On Side Lengths of Corners in Positive Density Subsets of the Euclidean Space von Durcik, Polona, Kovač, Vjekoslav, Rimanić, Luka

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LONELY RUNNERS IN FUNCTION FIELDS von Chow, Sam, Rimanić, Luka

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SHiFT: an efficient, flexible search engine for transfer learning von Renggli, Cedric, Yao, Xiaozhe, Kolar, Luka, Rimanic, Luka, Klimovic, Ana, Zhang, Ce

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Ease.ml/snoopy in Action: Towards Automatic Feasibility Analysis for Machine Learning Application Development von Renggli, Cedric, Rimanic, Luka, Kolar, Luka, Wu, Wentao, Zhang, Ce

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Lonely runners in function fields von Chow, Sam, Rimanic, Luka

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Szemer\'edi's theorem in the primes von Rimanic, Luka, Wolf, Julia

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Evaluating Bayes Error Estimators on Real-World Datasets with FeeBee von Renggli, Cedric, Rimanic, Luka, Hollenstein, Nora, Zhang, Ce

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Automatic Feasibility Study via Data Quality Analysis for ML: A Case-Study on Label Noise von Renggli, Cedric, Rimanic, Luka, Kolar, Luka, Wu, Wentao, Zhang, Ce

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SHiFT: An Efficient, Flexible Search Engine for Transfer Learning von Renggli, Cedric, Yao, Xiaozhe, Kolar, Luka, Rimanic, Luka, Klimovic, Ana, Zhang, Ce

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On Convergence of Nearest Neighbor Classifiers over Feature Transformations von Rimanic, Luka, Renggli, Cedric, Li, Bo, Zhang, Ce

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Fine-tuning Language Models over Slow Networks using Activation Compression with Guarantees von Wang, Jue, Yuan, Binhang, Rimanic, Luka, He, Yongjun, Dao, Tri, Chen, Beidi, Re, Christopher, Zhang, Ce

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DataLens: Scalable Privacy Preserving Training via Gradient Compression and Aggregation von Wang, Boxin, Wu, Fan, Long, Yunhui, Rimanic, Luka, Zhang, Ce, Li, Bo

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Knowledge Enhanced Machine Learning Pipeline against Diverse Adversarial Attacks von Gürel, Nezihe Merve, Qi, Xiangyu, Rimanic, Luka, Zhang, Ce, Li, Bo

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A Data Quality-Driven View of MLOps von Renggli, Cedric, Rimanic, Luka, Gürel, Nezihe Merve, Karlaš, Bojan, Wu, Wentao, Zhang, Ce

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Automatic Feasibility Study via Data Quality Analysis for ML: A Case-Study on Label Noise von Renggli, Cedric, Rimanic, Luka, Kolar, Luka, Wu, Wentao, Zhang, Ce

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Which Model to Transfer? Finding the Needle in the Growing Haystack von Renggli, Cedric, Pinto, André Susano, Rimanic, Luka, Puigcerver, Joan, Riquelme, Carlos, Zhang, Ce, Lucic, Mario

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Szemerédi's theorem in the primes von Rimanic, Luka, Wolf, Julia

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TSS: Transformation-Specific Smoothing for Robustness Certification von Li, Linyi, Weber, Maurice, Xu, Xiaojun, Rimanic, Luka, Kailkhura, Bhavya, Xie, Tao, Zhang, Ce, Li, Bo

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Evaluating Bayes Error Estimators on Real-World Datasets with FeeBee von Renggli, Cedric, Rimanic, Luka, Hollenstein, Nora, Zhang, Ce

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