Abstract Deep Learning enabled tremendous breakthroughs in visual understanding and speech recognition. Ostensibly, this is not the case in natural language processing (NLP) and higher level reasoning. However, it only appears that way because there[…]

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Abstract: The action of reading, understanding and combining words to create meaningful phrases comes naturally to most people. Still, the processes that govern semantic composition in the human brain are not well understood. In this[…]

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ABSTRACT: This is an updated version of a talk given at ASRU 2013 in Olomouc. Automatic pattern classifiers that output soft, probabilistic classifications—rather than hard decisions—can be more widely and more profitably applied, provided the[…]

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ABSTRACT: An important challenge in extracting useful structured information from text collections is relation extraction, i.e. identifying the types of relations between entities that are expressed in text. Due to the variety in how relations[…]

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November 20 @ 12:00 PM – 1:15 PM Abstract Using random matrix theory, we now have some very easy to understand and fast to use methods of computing low rank representations of matrices.  I have[…]

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Abstract Semantic parsing, the task of mapping sentences to logical form meaning representations, has recently received significant attention. We propose a grammar induction technique for AMR semantic parsing. While previous grammar induction techniques were designed[…]

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Abstract In the last few years DNNs have become the dominant technique for acoustic modeling in automatic speech recognition (ASR). The diverse set of approaches proposed to further improve ASR performance includes DNN- based acoustic[…]

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