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ICML
2010
IEEE
13 years 2 months ago
Implicit Online Learning
Online learning algorithms have recently risen to prominence due to their strong theoretical guarantees and an increasing number of practical applications for large-scale data ana...
Brian Kulis, Peter L. Bartlett
KDD
2012
ACM
187views Data Mining» more  KDD 2012»
11 years 7 months ago
Online learning to diversify from implicit feedback
In order to minimize redundancy and optimize coverage of multiple user interests, search engines and recommender systems aim to diversify their set of results. To date, these dive...
Karthik Raman, Pannaga Shivaswamy, Thorsten Joachi...
CDC
2010
IEEE
123views Control Systems» more  CDC 2010»
12 years 11 months ago
Implicit learning for explicit discount targeting in Online Social networks
Online Social networks are increasingly being seen as a means of obtaining awareness of user preferences. Such awareness could be used to target goods and services at them. We cons...
Srinivas Shakkottai, Lei Ying, Sankalp Sah
WWW
2007
ACM
14 years 5 months ago
Summarization of online image collections via implicit feedback
The availability of map interfaces and location-aware devices makes a growing amount of unstructured, geo-referenced information available on the Web. In particular, over twelve m...
Shane Ahern, Simon King, Mor Naaman, Rahul Nair
ECIR
2011
Springer
12 years 8 months ago
Balancing Exploration and Exploitation in Learning to Rank Online
Abstract. As retrieval systems become more complex, learning to rank approaches are being developed to automatically tune their parameters. Using online learning to rank approaches...
Katja Hofmann, Shimon Whiteson, Maarten de Rijke