Robert Busa-Fekete
Robert Busa-Fekete
Research scientist, Google Research
Verified email at
Cited by
Cited by
Bacterial evolution of antibiotic hypersensitivity
V Lázár, G Pal Singh, R Spohn, I Nagy, B Horváth, M Hrtyan, ...
Molecular systems biology 9 (1), 700, 2013
Antagonism between bacteriostatic and bactericidal antibiotics is prevalent
PS Ocampo, V Lázár, B Papp, M Arnoldini, P Abel zur Wiesch, ...
Antimicrobial agents and chemotherapy 58 (8), 4573-4582, 2014
Genome-wide analysis captures the determinants of the antibiotic cross-resistance interaction network
V Lázár, I Nagy, R Spohn, B Csörgő, Á Györkei, Á Nyerges, B Horváth, ...
Nature communications 5 (1), 4352, 2014
State-of-the-art anonymization of medical records using an iterative machine learning framework
G Szarvas, R Farkas, R Busa-Fekete
Journal of the American Medical Informatics Association 14 (5), 574-580, 2007
Extreme f-measure maximization using sparse probability estimates
K Jasinska, K Dembczynski, R Busa-Fekete, K Pfannschmidt, T Klerx, ...
International conference on machine learning, 1435-1444, 2016
Boosting products of base classifiers
B Kégl, R Busa-Fekete
Proceedings of the 26th annual international conference on machine learning …, 2009
Gossip-based distributed stochastic bandit algorithms
B Szorenyi, R Busa-Fekete, I Hegedus, R Ormándi, M Jelasity, B Kégl
International conference on machine learning, 19-27, 2013
MultiBoost: a multi-purpose boosting package
D Benbouzid, R Busa-Fekete, N Casagrande, FD Collin, B Kégl
The Journal of Machine Learning Research 13 (1), 549-553, 2012
A no-regret generalization of hierarchical softmax to extreme multi-label classification
M Wydmuch, K Jasinska, M Kuznetsov, R Busa-Fekete, K Dembczynski
Advances in neural information processing systems 31, 2018
Preference-based online learning with dueling bandits: A survey
V Bengs, R Busa-Fekete, A El Mesaoudi-Paul, E Hüllermeier
Journal of Machine Learning Research 22 (7), 1-108, 2021
Online rank elicitation for plackett-luce: A dueling bandits approach
B Szörényi, R Busa-Fekete, A Paul, E Hüllermeier
Advances in neural information processing systems 28, 2015
Top-k selection based on adaptive sampling of noisy preferences
R Busa-Fekete, B Szorenyi, W Cheng, P Weng, E Hüllermeier
International Conference on Machine Learning, 1094-1102, 2013
Fast classification using sparse decision DAGs
D Benbouzid, R Busa-Fekete, B Kégl
arXiv preprint arXiv:1206.6387, 2012
Preference-based rank elicitation using statistical models: The case of mallows
R Busa-Fekete, E Hüllermeier, B Szörényi
International conference on machine learning, 1071-1079, 2014
Preference-based reinforcement learning: evolutionary direct policy search using a preference-based racing algorithm
R Busa-Fekete, B Szörényi, P Weng, W Cheng, E Hüllermeier
Machine learning 97, 327-351, 2014
Assessing the degree of nativeness and Parkinson's condition using Gaussian processes and deep rectifier neural networks
T Grósz, R Busa-Fekete, G Gosztolya, L Tóth
Sixteenth Annual Conference of the International Speech Communication …, 2015
A survey of preference-based online learning with bandit algorithms
R Busa-Fekete, E Hüllermeier
Algorithmic Learning Theory: 25th International Conference, ALT 2014, Bled …, 2014
Fast boosting using adversarial bandits
R Busa-Fekete, B Kégl
27th International Conference on Machine Learning (ICML 2010), 143-150, 2010
Detecting autism, emotions and social signals using adaboost.
G Gosztolya, R Busa-Fekete, L Tóth
INTERSPEECH, 220-224, 2013
Qualitative multi-armed bandits: A quantile-based approach
B Szorenyi, R Busa-Fekete, P Weng, E Hüllermeier
International Conference on Machine Learning, 1660-1668, 2015
The system can't perform the operation now. Try again later.
Articles 1–20