Aspects of Semi-supervised and Active Learning in Conditional Random Fields

Semi-supervised and Active Training of Conditional Random Fields for Activity Recognition

Automated human activity recognition has attracted increasing attention in the past decade. However, the application of machine learning and probabilistic methods for activity recognition problems has been studied only in the past couple of years. For the first time, this thesis explores the application of semi-supervised and active learning in activity recognition. We present a new and efficie...

Painless Semi-Supervised Morphological Segmentation using Conditional Random Fields

We discuss data-driven morphological segmentation, in which word forms are segmented into morphs, that is the surface forms of morphemes. We extend a recent segmentation approach based on conditional random fields from purely supervised to semi-supervised learning by exploiting available unsupervised segmentation techniques. We integrate the unsupervised techniques into the conditional random f...

Generalized Expectation Criteria for Semi-Supervised Learning of Conditional Random Fields

This paper presents a semi-supervised training method for linear-chain conditional random fields that makes use of labeled features rather than labeled instances. This is accomplished by using generalized expectation criteria to express a preference for parameter settings in which the model’s distribution on unlabeled data matches a target distribution. We induce target conditional probability ...

Joint semi-supervised learning of Hidden Conditional Random Fields and Hidden Markov Models

Efficient Computation of Entropy Gradient for Semi-Supervised Conditional Random Fields

Entropy regularization is a straightforward and successful method of semi-supervised learning that augments the traditional conditional likelihood objective function with an additional term that aims to minimize the predicted label entropy on unlabeled data. It has previously been demonstrated to provide positive results in linear-chain CRFs, but the published method for calculating the entropy...