When learning to rank from user interactions, search and recommendation
...
Since its inception, the field of unbiased learning to rank (ULTR) has
r...
User interaction data is an important source of supervision in counterfa...
Structured State Spaces for Sequences (S4) is a recently proposed sequen...
A common way to avoid overfitting in supervised learning is early stoppi...
There are several measures for fairness in ranking, based on different
u...
We study the problem of recommending relevant products to users in relat...
In counterfactual learning to rank (CLTR) user interactions are used as ...
Besides position bias, which has been well-studied, trust bias is anothe...
Unbiased CLTR requires click propensities to compensate for the differen...