Date & Location: June 24th in NYC in conjunction with ICML 2016, in the O'Neill Room at Marriott Marquis (4th floor).
From online news to online shopping to scholarly research, we are inundated with a torrent of information on a daily basis. With our limited time, money and attention, we often struggle to extract actionable knowledge and make informed decisions from this deluge of data. A common approach for addressing this challenge is personalization, where results are automatically filtered to match the tastes, preferences and goals of individual people.
This workshop aims to bring together researchers from industry and academia in order to describe recent advances and discuss future research directions pertaining to computational frameworks for personalization, broadly construed. We aim to highlight new and emerging research opportunities for the machine learning community that arise from the evolving needs for personalization.
Personalization has already made a huge impact in online recommender systems. Furthermore, there are many emerging applications where personalization has begun to show great promise, such as education and medicine. We are particularly interested in understanding what are the common computational challenges that underlie all these applications, with the goal of accelerating the development of personalization frameworks across a broad range of domains.
Our technical topics of interest include (but are not limited to):
Call for Submissions:
We invite workshop submissions on preliminary or recently published research related to any topic from the above list.
We are grateful for sponsorship by: