Bayesian Optimization in High Dimensions via Random Embeddings. Z Wang, M Zoghi, F Hutter, D Matheson, N De Freitas IJCAI, 1778-1784, 2013 | 248 | 2013 |
Bayesian optimization in a billion dimensions via random embeddings Z Wang, F Hutter, M Zoghi, D Matheson, N de Feitas Journal of Artificial Intelligence Research 55, 361-387, 2016 | 221 | 2016 |
Exponential regret bounds for Gaussian process bandits with deterministic observations N De Freitas, A Smola, M Zoghi arXiv preprint arXiv:1206.6457, 2012 | 97 | 2012 |
Relative upper confidence bound for the k-armed dueling bandit problem M Zoghi, S Whiteson, R Munos, M Rijke International conference on machine learning, 10-18, 2014 | 93 | 2014 |
Copeland dueling bandits M Zoghi, Z Karnin, S Whiteson, M De Rijke arXiv preprint arXiv:1506.00312, 2015 | 64 | 2015 |
Online learning to rank in stochastic click models M Zoghi, T Tunys, M Ghavamzadeh, B Kveton, C Szepesvari, Z Wen International Conference on Machine Learning, 4199-4208, 2017 | 54 | 2017 |
Contextual dueling bandits M Dudík, K Hofmann, RE Schapire, A Slivkins, M Zoghi Conference on Learning Theory, 563-587, 2015 | 48 | 2015 |
Mergerucb: A method for large-scale online ranker evaluation M Zoghi, S Whiteson, M de Rijke Proceedings of the Eighth ACM International Conference on Web Search and …, 2015 | 42 | 2015 |
Relative confidence sampling for efficient on-line ranker evaluation M Zoghi, SA Whiteson, M De Rijke, R Munos Proceedings of the 7th ACM international conference on Web search and data …, 2014 | 40 | 2014 |
Click-based hot fixes for underperforming torso queries M Zoghi, T Tunys, L Li, D Jose, J Chen, CM Chin, M de Rijke Proceedings of the 39th International ACM SIGIR conference on Research and …, 2016 | 23 | 2016 |
Revisiting approximate metric optimization in the age of deep neural networks S Bruch, M Zoghi, M Bendersky, M Najork Proceedings of the 42nd International ACM SIGIR Conference on Research and …, 2019 | 22 | 2019 |
Advancements in Dueling Bandits. Y Sui, M Zoghi, K Hofmann, Y Yue IJCAI, 5502-5510, 2018 | 19 | 2018 |
The Gromov width of coadjoint orbits of compact Lie groups M Zoghi University of Toronto, 2010 | 14 | 2010 |
BubbleRank: Safe online learning to re-rank via implicit click feedback C Li, B Kveton, T Lattimore, I Markov, M de Rijke, C Szepesvári, M Zoghi Uncertainty in Artificial Intelligence, 196-206, 2020 | 13* | 2020 |
Regret bounds for deterministic gaussian process bandits N de Freitas, A Smola, M Zoghi arXiv preprint arXiv:1203.2177, 2012 | 11 | 2012 |
Instance-dependent regret bounds for dueling bandits A Balsubramani, Z Karnin, RE Schapire, M Zoghi Conference on Learning Theory, 336-360, 2016 | 10 | 2016 |
An effective orbifold groupoid is determined up to Morita equivalence by its underlying diffeological orbifold Y Karshon, M Zoghi preprint, 2008 | 5 | 2008 |
Using confidence bounds for efficient on-line ranker evaluation M Zoghi, S Whiteson, M de Rijke, R Munos WSDM 14, 24, 2014 | 4 | 2014 |
Merge double Thompson sampling for large scale online ranker evaluation C Li, I Markov, M de Rijke, M Zoghi arXiv preprint arXiv:1812.04412, 2018 | 3 | 2018 |
MergeDTS: A Method for Effective Large-scale Online Ranker Evaluation C Li, I Markov, MD Rijke, M Zoghi ACM Transactions on Information Systems (TOIS) 38 (4), 1-28, 2020 | 2 | 2020 |