Perceptron

This paper proposes a new discriminative training method, called minimum sample risk (MSR), of estimating parameters of language models for text input. While most existing discriminative training methods use a …...

The classification problem derived from information extraction (IE) has an imbal- anced training set. This is particularly true when learning from smaller datasets which often have a few positive training …...

In this paper, we propose a linear model-based general framework to combine k-best parse outputs from multiple parsers. The proposed framework leverages on the strengths of pre- vious system combination …...

General natural language processing and text-to-speech applications require certain (lexical level) processing steps in order to solve some frequent tasks such as lemmatization, syllabification, lexical stress prediction and phonetic transcription. …...

AbstractDue to the nature of complex NLP problems, structured prediction algorithms have been important modeling tools for a wide range of tasks. While there exists evidence showing that linear Structural …...

Online learning algorithms like the percep- tron are widely used for structured predic- tion tasks. For sequential search problems, like left-to-right tagging and parsing, beam search has been successfully combined …...

AbstractThis report describes the methods employed by the Democritus University of Thrace (DUTH) team for participating in SemEval-2019 Task 8: Fact Checking in Community Question Answering Forums. Our team dealt …...