Writing the future of machine learning and invention

June's NAACL conference saw machine learning specialists from technology company Iprova present a paper introducing a new and effective method for the unsupervised training of machine learning algorithms to infer sentence embeddings. The NAACL (North American Chapter of the Association for Computational Linguistics) Human Language Technologies (HLT) conference took place at the Hyatt Regency New Orleans hotel, Louisiana, from June 1–6, 2018. The research paper, entitled "Unsupervised Learning of Sentence Embeddings using Compositional n-Gram Features", will be presented by Matteo Pagliardini. Pagliardini is a senior machine learning engineer at Iprova and one of the three scientists that authored the research paper and developed the new model for unsupervised training, Sent2Vec. While there have been several successes in deep learning in recent years, the paper notes that these have almost exclusively relied on supervised training.