Learning to Analyze Sequences

Google Tech Talks April 12, 2007 ABSTRACT Sequential data --- speech, text, genomic sequences --- floods our storage servers. Much useful information in these data is carried by implicit structure: phonemes and prosody in speech, syntactic structure in text, genes and regulatory elements in genomic sequences. Over the last six years, several of us have been investigating structured linear models, a unified discriminative learning approach to sequence analysis problems. I will review the approach and illustrate it with applications to information extraction and gene finding. I will conclude with a summary of other applications and current research questions. Credits: Speaker:Fernando Pereira