Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
Results
Showing 1 to 6 of 6 for “"Bandit algorithm"”.
-
ONLINE LEARNING WITH BANDITS FOR COVERAGE
… propose a novel online reinforcement learning algorithm inspired by the Multi-Armed Bandit problem to solve the online recommendation system problem. We introduce a graph-based mechanism to improve the user coverage by recommended items and show that the mechanism can facilitate the …
-
Analytics for online markets
… to predict demand of new products and develop an algorithm to efficiently solve the subsequent multi-product price optimization. We then create and implement this algorithm into a pricing decision support tool for Rue La La's daily use. We conduct a controlled field experiment which estimates an …
-
Carbon Accounting for Sustainable Computing in Cloud Provisioned Data Centers
… used to distribute workloads using a multi-armed bandit algorithm using Thompson Sampling. This work illustrates that embodied emissions can constitute anywhere from five to thirty percent of a server's total environmental impact. Workloads can be more than 11 times higher between workloads given …
-
Unsupervised query expansion for theme queries by exploration and fusion
Theme queries are a subtype of informational queries that cover broader topics than those expressed explicitly in the query terms. For this type of query, it is natural to resort to query reformation techniques such as query expansion. While traditional query expansion may be used to improve the …
-
NON-STATIONARY MULTIARMED BANDITS FOR SATIATION AND SEASONALITY PHENOMENA IN MUSIC RECOMMENDER SYSTEMS
… theoretical aspects of non-stationary multiarmed bandits, motivated by their application to music recommender systems. An intrinsic challenge of such systems lies in evolving user preferences. Rather than finding a single optimal item, the objective is to craft an ordered sequence of items …
-
DISTRIBUTED AND DELAYED ONLINE LEARNING
… of distributed and delayed online learning algorithms. First, we introduce delayed online learning, where model updates rely on feedback arriving with variable delays. We study the online learning problem with curved losses and delayed feedback, designing algorithms that exploit loss …