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2020 – today
- 2024
[c8]Scott Sussex, Pier Giuseppe Sessa, Anastasia Makarova, Andreas Krause:
Adversarial Causal Bayesian Optimization. ICLR 2024- 2023
- [j1]Christopher König, Miks Ozols, Anastasia Makarova, Efe C. Balta
, Andreas Krause, Alisa Rupenyan:
Safe Risk-Averse Bayesian Optimization for Controller Tuning. IEEE Robotics Autom. Lett. 8(12): 8208-8215 (2023) - [c7]Scott Sussex, Anastasia Makarova, Andreas Krause:
Model-based Causal Bayesian Optimization. ICLR 2023 - [i6]Christopher König, Miks Ozols, Anastasia Makarova, Efe C. Balta, Andreas Krause, Alisa Rupenyan:
Safe Risk-averse Bayesian Optimization for Controller Tuning. CoRR abs/2306.13479 (2023) - 2022
- [c6]Anastasia Makarova, Huibin Shen, Valerio Perrone, Aaron Klein, Jean Baptiste Faddoul, Andreas Krause, Matthias W. Seeger, Cédric Archambeau:
Automatic Termination for Hyperparameter Optimization. AutoML 2022: 7/1-21 - 2021
- [c5]Mikhail Usvyatsov, Anastasia Makarova, Rafael Ballester-Ripoll, Maxim V. Rakhuba, Andreas Krause, Konrad Schindler:
Cherry-Picking Gradients: Learning Low-Rank Embeddings of Visual Data via Differentiable Cross-Approximation. ICCV 2021: 11406-11415 - [c4]Anastasia Makarova, Ilnura Usmanova, Ilija Bogunovic, Andreas Krause:
Risk-averse Heteroscedastic Bayesian Optimization. NeurIPS 2021: 17235-17245 - [i5]Anastasia Makarova, Huibin Shen, Valerio Perrone, Aaron Klein, Jean Baptiste Faddoul, Andreas Krause, Matthias W. Seeger, Cédric Archambeau:
Overfitting in Bayesian Optimization: an empirical study and early-stopping solution. CoRR abs/2104.08166 (2021) - [i4]Mikhail Usvyatsov, Anastasia Makarova, Rafael Ballester-Ripoll, Maxim V. Rakhuba, Andreas Krause, Konrad Schindler:
Cherry-Picking Gradients: Learning Low-Rank Embeddings of Visual Data via Differentiable Cross-Approximation. CoRR abs/2105.14250 (2021) - [i3]Anastasia Makarova, Ilnura Usmanova, Ilija Bogunovic, Andreas Krause:
Risk-averse Heteroscedastic Bayesian Optimization. CoRR abs/2111.03637 (2021) - 2020
- [c3]Ankit Dhall, Anastasia Makarova, Octavian Ganea, Dario Pavllo, Michael Greeff, Andreas Krause:
Hierarchical Image Classification using Entailment Cone Embeddings. CVPR Workshops 2020: 3649-3658 - [c2]Erik A. Daxberger, Anastasia Makarova, Matteo Turchetta, Andreas Krause:
Mixed-Variable Bayesian Optimization. IJCAI 2020: 2633-2639 - [i2]Ankit Dhall, Anastasia Makarova, Octavian Ganea, Dario Pavllo, Michael Greeff, Andreas Krause:
Hierarchical Image Classification using Entailment Cone Embeddings. CoRR abs/2004.03459 (2020)
2010 – 2019
- 2019
- [c1]Teodora Vukovic, Nora Muheim, Olivier Winistörfer, Ivan Simko, Anastasia Makarova, Sanja Bradjan:
Corpora and Processing Tools for Non-standard Contemporary and Diachronic Balkan Slavic. RANLP Student Research Workshop 2019: 62-68 - [i1]Erik A. Daxberger, Anastasia Makarova, Matteo Turchetta, Andreas Krause:
Mixed-Variable Bayesian Optimization. CoRR abs/1907.01329 (2019)
Coauthor Index
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