no code implementations • 31 Oct 2023 • Haolun Wu, Ofer Meshi, Masrour Zoghi, Fernando Diaz, Xue Liu, Craig Boutilier, Maryam Karimzadehgan
Accurate modeling of the diverse and dynamic interests of users remains a significant challenge in the design of personalized recommender systems.
1 code implementation • 29 Oct 2023 • Li Ding, Masrour Zoghi, Guy Tennenholtz, Maryam Karimzadehgan
We introduce EV3, a novel meta-optimization framework designed to efficiently train scalable machine learning models through an intuitive explore-assess-adapt protocol.
1 code implementation • 25 Jan 2023 • Javad Azizi, Ofer Meshi, Masrour Zoghi, Maryam Karimzadehgan
The recent literature on online learning to rank (LTR) has established the utility of prior knowledge to Bayesian ranking bandit algorithms.
1 code implementation • 11 Dec 2018 • Chang Li, Ilya Markov, Maarten de Rijke, Masrour Zoghi
Our main finding is that for large-scale Condorcet ranker evaluation problems, MergeDTS outperforms the state-of-the-art dueling bandit algorithms.
no code implementations • 15 Jun 2018 • Chang Li, Branislav Kveton, Tor Lattimore, Ilya Markov, Maarten de Rijke, Csaba Szepesvari, Masrour Zoghi
In this paper, we study the problem of safe online learning to re-rank, where user feedback is used to improve the quality of displayed lists.
no code implementations • ICML 2017 • Masrour Zoghi, Tomas Tunys, Mohammad Ghavamzadeh, Branislav Kveton, Csaba Szepesvari, Zheng Wen
In this work, we propose BatchRank, the first online learning to rank algorithm for a broad class of click models.
no code implementations • NeurIPS 2015 • Masrour Zoghi, Zohar Karnin, Shimon Whiteson, Maarten de Rijke
A version of the dueling bandit problem is addressed in which a Condorcet winner may not exist.
no code implementations • 23 Feb 2015 • Miroslav Dudík, Katja Hofmann, Robert E. Schapire, Aleksandrs Slivkins, Masrour Zoghi
The first of these algorithms achieves particularly low regret, even when data is adversarial, although its time and space requirements are linear in the size of the policy space.
no code implementations • 12 Dec 2013 • Masrour Zoghi, Shimon Whiteson, Remi Munos, Maarten de Rijke
This paper proposes a new method for the K-armed dueling bandit problem, a variation on the regular K-armed bandit problem that offers only relative feedback about pairs of arms.
1 code implementation • 9 Jan 2013 • Ziyu Wang, Frank Hutter, Masrour Zoghi, David Matheson, Nando de Freitas
Bayesian optimization techniques have been successfully applied to robotics, planning, sensor placement, recommendation, advertising, intelligent user interfaces and automatic algorithm configuration.