4 accepted papers
Active learning is commonly used to train label-efficient models by adaptively selecting the most informative queries. However, most active learning strategies are designed to either learn a representation of the data (e.g., embedding or metric learning) or perform well on a task (e.g., classificati…
A common problem in recommendation systems is to learn a model of user preferences based only on comparisons of the relative attractiveness of different items. We consider this problem in the context of an ideal point model of user preference, where each user can be represented as a point in a low-d…
Hawkes processes are a class of auto-regressive point processes that are commonly used in modeling data in which events tend to cluster and influence the likelihood of future events. Because of their ability to model and explain how events or processes can influence each other, Hawkes processes (and…
We develop a framework for localizing an unknown point w using paired comparisons of the form "w is closer to point x <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">i</sub> than to x <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http…