Zobrazeno 1 - 8
of 8
pro vyhledávání: '"Masrour Zoghi"'
Publikováno v:
ACM Transactions on Information Systems, 38(4):40. Association for Computing Machinery (ACM)
Online ranker evaluation is one of the key challenges in information retrieval. While the preferences of rankers can be inferred by interleaving methods, the problem of how to effectively choose the ranker pair that generates the interleaved list wit
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::0fe6d7c84170b5b3f5afd8b976238479
https://hdl.handle.net/11245.1/5cee56c9-8de8-4ae6-801c-819a86f00634
https://hdl.handle.net/11245.1/5cee56c9-8de8-4ae6-801c-819a86f00634
Publikováno v:
SIGIR
Learning-to-Rank is a branch of supervised machine learning that seeks to produce an ordering of a list of items such that the utility of the ranked list is maximized. Unlike most machine learning techniques, however, the objective cannot be directly
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::5aad67607ac6ff2751eb763ffe335f29
https://doi.org/10.1145/3331184.3331347
https://doi.org/10.1145/3331184.3331347
Publikováno v:
Journal of Artificial Intelligence Research. 55:361-387
Bayesian optimization techniques have been successfully applied to robotics, planning, sensor placement, recommendation, advertising, intelligent user interfaces and automatic algorithm configuration. Despite these successes, the approach is restrict
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::8c52f97808e6e0b9e4ac6f14e79ed7bb
https://doi.org/10.1613/jair.4806
https://doi.org/10.1613/jair.4806
Publikováno v:
IJCAI
The dueling bandits problem is an online learning framework where learning happens ``on-the-fly'' through preference feedback, i.e., from comparisons between a pair of actions. Unlike conventional online learning settings that require absolute feedba
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::1c9f40a4377a3f7e269dcb7f15f8a072
https://doi.org/10.24963/ijcai.2018/776
https://doi.org/10.24963/ijcai.2018/776
Autor:
Masrour Zoghi
In every domain where a service or a product is provided, an important question is that of evaluation: given a set of possible choices for deployment, what is the best one? An important example, which is considered in this work, is that of ranker eva
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::77215acd0300679113106c62e5571b7e
https://doi.org/10.3990/1.9789036542876
https://doi.org/10.3990/1.9789036542876
Autor:
Chun Ming Chin, Masrour Zoghi, Maarten de Rijke, Damien Jose, Lihong Li, Junyan Chen, Tomas Tunys
Publikováno v:
SIGIR
Ranking documents using their historical click-through rate (CTR) can improve relevance for frequently occurring queries, i.e., so-called head queries. It is difficult to use such click signals on non-head queries as they receive fewer clicks. In thi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::bcc6b17cd670ae84bcea9980aec0cf99
https://doi.org/10.1145/2911451.2911500
https://doi.org/10.1145/2911451.2911500
Publikováno v:
WSDM'15: proceedings of the Eighth ACM International Conference on Web Search and Data Mining: Jan. 31-Feb. 6, 2015, Shanghai, China, 17-26
STARTPAGE=17;ENDPAGE=26;TITLE=WSDM'15: proceedings of the Eighth ACM International Conference on Web Search and Data Mining: Jan. 31-Feb. 6, 2015, Shanghai, China
WSDM
STARTPAGE=17;ENDPAGE=26;TITLE=WSDM'15: proceedings of the Eighth ACM International Conference on Web Search and Data Mining: Jan. 31-Feb. 6, 2015, Shanghai, China
WSDM
A key challenge in information retrieval is that of on-line ranker evaluation: determining which one of a finite set of rankers performs the best in expectation on the basis of user clicks on presented document lists. When the presented lists are con
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ddc7b0734fd09ff55ce912251ca6aa46
https://dare.uva.nl/personal/pure/en/publications/mergerucb-a-method-for-largescale-online-ranker-evaluation(ccc80b1c-dda3-40cf-9866-35f468b73dc8).html
https://dare.uva.nl/personal/pure/en/publications/mergerucb-a-method-for-largescale-online-ranker-evaluation(ccc80b1c-dda3-40cf-9866-35f468b73dc8).html
Publikováno v:
WSDM '14: proceedings of the 7th ACM International Conference on Web Search and Data Mining: February 24-28, 2014, New York, New York, USA, 73-82
STARTPAGE=73;ENDPAGE=82;TITLE=WSDM '14: proceedings of the 7th ACM International Conference on Web Search and Data Mining: February 24-28, 2014, New York, New York, USA
WSDM
STARTPAGE=73;ENDPAGE=82;TITLE=WSDM '14: proceedings of the 7th ACM International Conference on Web Search and Data Mining: February 24-28, 2014, New York, New York, USA
WSDM
A key challenge in information retrieval is that of on-line ranker evaluation: determining which one of a finite set of rankers performs the best in expectation on the basis of user clicks on presented document lists. When the presented lists are con
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::bcf1ca1070a1f9a9349b2ae454fdf03b
https://hdl.handle.net/11245/1.439274
https://hdl.handle.net/11245/1.439274