Information theoretic active learning has been widely studied for probabilistic models. For simple regression an optimal myopic policy is easily tractable. However, for other tasks and with moreâ€¦ (More)

We propose a probabilistic matrix factorization model for collaborative filtering that learns from data that is missing not at random (MNAR). Matrix factorization models exhibit state-of-the-artâ€¦ (More)

Entity linking involves labeling phrases in text with their referent entities, such as Wikipedia or Freebase entries. This task is challenging due to the large number of possible entities, in theâ€¦ (More)

â€¢ General approach: model a user with a latent â€˜utilityâ€™ function f such that f (xi) > f (xj) when item i is preferred to item j, where xi and xj are feature vectors for the items. â€¢ GP models areâ€¦ (More)

We frame Question Answering as a Reinforcement Learning task, an approach that we call Active Question Answering. We propose an agent that sits between the user and a black box question-answeringâ€¦ (More)

We present a new matrix factorization model for rating data and a corresponding active learning strategy to address the cold-start problem. Coldstart is one of the most challenging tasks forâ€¦ (More)

Fully observed large binary matrices appear in a wide variety of contexts. To model them, probabilistic matrix factorization (PMF) methods are an attractive solution. However, current batchâ€¦ (More)

In this paper we revisit the problem of optimal design of quantum tomographic experiments. In contrast to previous approaches where an optimal set of measurements is decided in advance of theâ€¦ (More)

K. S. Kravtsov,1 S. S. Straupe,2,* I. V. Radchenko,1 N. M. T. Houlsby,3 F. HuszÃ¡r,3 and S. P. Kulik2 1A. M. Prokhorov General Physics Institute RAS, Moscow, Russia 2Faculty of Physics, M. V.â€¦ (More)

Many automatic visualization methods have been proposed. However, a visualization that is automatically generated might be different to how a user wants to arrange the objects in visualization space.â€¦ (More)