A Nonparametric Bayesian model for the Multiple Annotators problem

  • Artes-Rodriguez A.
  • G-Moreno P.
  • Perez-Cruz F.

We propose a generative classification algorithm for a multiple annotators problem, in which the training examples have been simultaneously labeled by a set of imperfect annotators. This algorithm allows us to infer the characteristics (sensitivity and specificity) of each annotator, the ground truth of the training set and build a classifier for test examples. In addition, we consider that the performance of the annotators can be in-homogeneous across the instance space due to several factors like his past experience with similar examples. To capture this behavior, our algorithm uses a Dirichlet Process Mixture Model to divide the instance space in different areas across which the annotators are consistent and resort to variational inference to approximate the posterior of the parameters of the model. Several experiments with synthetic and real databases are performed to prove that the method exhibits high accuracy outperforming state-of-the-art algorithms. In addition, the method offers an interpretable solution and provides an estimation of the performance of the annotators in each of the components, allowing to better understanding the decision process undertaken by the annotators.

Recent Publications

August 09, 2017

A Cloud Native Approach to 5G Network Slicing

  • Francini A.
  • Miller R.
  • Sharma S.

5G networks will have to support a set of very diverse and often extreme requirements. Network slicing offers an effective way to unlock the full potential of 5G networks and meet those requirements on a shared network infrastructure. This paper presents a cloud native approach to network slicing. The cloud ...

August 01, 2017

Modeling and simulation of RSOA with a dual-electrode configuration

  • De Valicourt G.
  • Liu Z.
  • Violas M.
  • Wang H.
  • Wu Q.

Based on the physical model of a bulk reflective semiconductor optical amplifier (RSOA) used as a modulator in radio over fiber (RoF) links, the distributions of carrier density, signal photon density, and amplified spontaneous emission photon density are demonstrated. One of limits in the use of RSOA is the lower ...

July 12, 2017

PrivApprox: Privacy-Preserving Stream Analytics

  • Chen R.
  • Christof Fetzer
  • Le D.
  • Martin Beck
  • Pramod Bhatotia
  • Thorsten Strufe

How to preserve users' privacy while supporting high-utility analytics for low-latency stream processing? To answer this question: we describe the design, implementation and evaluation of PRIVAPPROX, a data analytics system for privacy-preserving stream processing. PRIVAPPROX provides three properties: (i) Privacy: zero-knowledge privacy (ezk) guarantees for users, a privacy bound tighter ...