In this paper, we introduce Target-Aware Weighted Training (TAWT), a wei...
We consider the online linear regression problem, where the predictor ve...
In the context of Multi Instance Learning, we analyze the Single Instanc...
We study a sequential resource allocation problem between a fixed number...
In extreme classification problems, learning algorithms are required to ...
The Multi-Armed Bandits (MAB) framework highlights the tension between
a...
We present a new recommendation setting for picking out two items from a...
This paper introduces a new probabilistic model for online learning whic...
We derive a convex optimization problem for the task of segmenting seque...
Advice-efficient prediction with expert advice (in analogy to label-effi...
The goal of a learner, in standard online learning, is to have the cumul...
Discriminative linear models are a popular tool in machine learning. The...
Algorithms for learning distributions over weight-vectors, such as AROW ...