Analysis of Semi-Supervised Learning with the Yarowsky Algorithm

06/20/2012
by   Gholam Reza Haffari, et al.
0

The Yarowsky algorithm is a rule-based semi-supervised learning algorithm that has been successfully applied to some problems in computational linguistics. The algorithm was not mathematically well understood until (Abney 2004) which analyzed some specific variants of the algorithm, and also proposed some new algorithms for bootstrapping. In this paper, we extend Abney's work and show that some of his proposed algorithms actually optimize (an upper-bound on) an objective function based on a new definition of cross-entropy which is based on a particular instantiation of the Bregman distance between probability distributions. Moreover, we suggest some new algorithms for rule-based semi-supervised learning and show connections with harmonic functions and minimum multi-way cuts in graph-based semi-supervised learning.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
05/28/2019

A Review of Semi Supervised Learning Theories and Recent Advances

Semi-supervised learning, which has emerged from the beginning of this c...
research
02/16/2017

Semi-supervised Learning for Discrete Choice Models

We introduce a semi-supervised discrete choice model to calibrate discre...
research
03/15/2012

Online Semi-Supervised Learning on Quantized Graphs

In this paper, we tackle the problem of online semi-supervised learning ...
research
05/22/2018

Semi-supervised learning: When and why it works

Semi-supervised learning deals with the problem of how, if possible, to ...
research
09/06/2018

Wasserstein Soft Label Propagation on Hypergraphs: Algorithm and Generalization Error Bounds

Inspired by recent interests of developing machine learning and data min...
research
09/17/2017

Semi-supervised learning

Semi-supervised learning deals with the problem of how, if possible, to ...
research
10/05/2021

Extensions of Karger's Algorithm: Why They Fail in Theory and How They Are Useful in Practice

The minimum graph cut and minimum s-t-cut problems are important primiti...

Please sign up or login with your details

Forgot password? Click here to reset