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ORCIDMario Lucic
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Publications
- 2018
[c16]Olivier Bachem, Mario Lucic, Andreas Krause:
Scalable k -Means Clustering via Lightweight Coresets. KDD 2018: 1119-1127- 2017
- [j1]Mario Lucic, Matthew Faulkner, Andreas Krause
, Dan Feldman:
Training Gaussian Mixture Models at Scale via Coresets. J. Mach. Learn. Res. 18: 160:1-160:25 (2017) - [c12]Olivier Bachem, Mario Lucic, S. Hamed Hassani, Andreas Krause:
Uniform Deviation Bounds for k-Means Clustering. ICML 2017: 283-291 - [c11]Olivier Bachem, Mario Lucic, Andreas Krause:
Distributed and Provably Good Seedings for k-Means in Constant Rounds. ICML 2017: 292-300 - [c10]Mohammad Reza Karimi, Mario Lucic, S. Hamed Hassani, Andreas Krause:
Stochastic Submodular Maximization: The Case of Coverage Functions. NIPS 2017: 6853-6863 - [i10]Olivier Bachem, Mario Lucic, Andreas Krause:
Scalable and Distributed Clustering via Lightweight Coresets. CoRR abs/1702.08248 (2017) - [i9]Olivier Bachem, Mario Lucic, S. Hamed Hassani, Andreas Krause:
Uniform Deviation Bounds for Unbounded Loss Functions like k-Means. CoRR abs/1702.08249 (2017) - [i8]Mohammad Reza Karimi, Mario Lucic, S. Hamed Hassani, Andreas Krause:
Stochastic Submodular Maximization: The Case of Coverage Functions. CoRR abs/1711.01566 (2017) - 2016
- [c9]Olivier Bachem, Mario Lucic, S. Hamed Hassani, Andreas Krause:
Approximate K-Means++ in Sublinear Time. AAAI 2016: 1459-1467 - [c8]Mario Lucic, Olivier Bachem, Andreas Krause:
Strong Coresets for Hard and Soft Bregman Clustering with Applications to Exponential Family Mixtures. AISTATS 2016: 1-9 - [c6]Mario Lucic, Olivier Bachem, Morteza Zadimoghaddam, Andreas Krause:
Horizontally Scalable Submodular Maximization. ICML 2016: 2981-2989 - [c5]Mario Lucic, Olivier Bachem, Andreas Krause:
Linear-Time Outlier Detection via Sensitivity. IJCAI 2016: 1795-1801 - [c4]Olivier Bachem, Mario Lucic, Seyed Hamed Hassani, Andreas Krause:
Fast and Provably Good Seedings for k-Means. NIPS 2016: 55-63 - [i5]Mario Lucic, Olivier Bachem, Andreas Krause:
Linear-time Outlier Detection via Sensitivity. CoRR abs/1605.00519 (2016) - [i4]Mario Lucic, Mesrob I. Ohannessian, Amin Karbasi, Andreas Krause:
Tradeoffs for Space, Time, Data and Risk in Unsupervised Learning. CoRR abs/1605.00529 (2016) - [i3]Mario Lucic, Olivier Bachem, Morteza Zadimoghaddam, Andreas Krause:
Horizontally Scalable Submodular Maximization. CoRR abs/1605.09619 (2016) - 2015
- [c3]Mario Lucic, Mesrob I. Ohannessian, Amin Karbasi, Andreas Krause:
Tradeoffs for Space, Time, Data and Risk in Unsupervised Learning. AISTATS 2015 - [c2]Olivier Bachem, Mario Lucic, Andreas Krause:
Coresets for Nonparametric Estimation - the Case of DP-Means. ICML 2015: 209-217 - [i2]Mario Lucic, Olivier Bachem, Andreas Krause:
Strong Coresets for Hard and Soft Bregman Clustering with Applications to Exponential Family Mixtures. CoRR abs/1508.05243 (2015)
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