… This leads to learned ranking functions that produce rankings with redundant … ranks is often
preferred. We present two online learning algorithms that directly learn a diverse ranking of …

… queries often have different meanings for different users (such as jaguar). We present a new
multi-armed bandit learning algorithm that directly learns a diverse ranking of results based …

… a Multi-Armed Bandits based algorithm [26] that improves both thematic and item diversity
during … [43] use MABs for learning diverse rankings of web documents based on user clicks, …

… , thus applying immense pressure to newly added individuals (or cells) while the opposite
is true with curiosity-based selection; (b) parent selection in this paper is performed by ranking …

… that explicitly takes document similarity and ranking context into account. Our … multi-armed
bandit models from the literature: ranked bandits (Radlinski et al., 2008) and Lipschitz bandits (…

… content to students in order to maximize their learning gains over … MAPLE (Multi-Armed
Bandits based Personalization for Learning … a field study in the wild where students used different …

… (2) We present three multi-armed bandit based algorithms for this and derive the regret and
… by using a diverse ranking strategy. This connection between diversity in ranking and CLV …

… To test the effectiveness of exploration provided by Algorithm 1 with different scoring functions
S, we compare them with ϵ-greedy [34], which is the simplest and widely used way to add …

… learning settings, active/adaptive querying is possible, but the number of rounds of adaptivity
is limited. We study … in a stochastic multi-armed bandit, and the problem of top-$ k $ ranking …

… ’s satisfaction by combining relevance and diversity. Kleinberg and colleagues (Radlinski, …
and diversity and presented a multi-armed bandit algorithm that learns a diversified ranking of …