In counterfactual learning to rank (CLTR) user interactions are used as ...
As the size and complexity of models and datasets grow, so does the need...
Unbiased CLTR requires click propensities to compensate for the differen...
Contextual bandit problems are a natural fit for many information retrie...
The visual appearance of a webpage carries valuable information about it...
Online learning to rank (OLTR) via implicit feedback has been extensivel...
Online ranker evaluation is one of the key challenges in information
ret...
We study the problem of online learning to re-rank, where users provide
...
Getting a better understanding of user behavior is important for advanci...
Conversational interfaces are likely to become more efficient, intuitive...