4 citations · 4 across the 1 of their papers we have counts for
4 papers
Top- eXtreme Contextual Bandits with Arm Hierarchy
Rajat Sen, Alexander Rakhlin, Lexing Ying +4
Motivated by modern applications, such as online advertisement and recommender systems, we study the top- extreme contextual bandits problem, where the total number of arms can…
A Zero Attention Model for Personalized Product Search
Qingyao Ai, Daniel N. Hill, S. V. N. Vishwanathan +1
Product search is one of the most popular methods for people to discover and purchase products on e-commerce websites. Because personal preferences often have an important influenc…
An Efficient Bandit Algorithm for Realtime Multivariate Optimization
Daniel N Hill, Houssam Nassif, Yi Liu +2
Optimization is commonly employed to determine the content of web pages, such as to maximize conversions on landing pages or click-through rates on search engine result pages. Ofte…
Adaptive, Personalized Diversity for Visual Discovery
Choon Hui Teo, Houssam Nassif, Daniel Hill +4
Search queries are appropriate when users have explicit intent, but they perform poorly when the intent is difficult to express or if the user is simply looking to be inspired. Vis…