Colloquium, Research, and Reading Group Meetings Quantum Algorithms for Natural Language Processing

Colloquium, Research, and Reading Group Meetings during summer 2018

If you are interested in participating in a research and reading group on prosodic and supra-segmental speech processing, knowledge graphs, Deep Learning, and in particular Linear Algebra and Quantum Algorithms using Linear Algebra, we are meetings weekly this summer. Send me a note, if you want to be put on the mailing list.

The two projects are:

Speech Processing, Prosody, Intonation, Pragmatics, and Semantics

• speech processing focusing on prosody, intonation contours, focus intonation etc. to detect speech or dialog acts for AIs like Alexa, Google Assistant, etc. The goals are to develop a unique data set for training and evaluation (speech and transcriptions), train Deep Learning models that detect the speech acts, and evaluate the results, document everything and prepare papers and presentations

Open Information Extraction, Event Detection, Knowledge Graphs, Deep Learning, Reasoning, Search

• Open Information Extraction (Open IE) for extraction of events, identification of event types, timelines, locations, causal relations, involved parties, etc., extracting from unstructured text, parsing the content using NLP and Deep Learning, and mapping it into Knowledge Graph representations using Neo4J, Stardog, TigerGraph, etc. Similar to the project above, creating corpora for training and testing, running experiments and preparing final reports

The two projects meet independently, they can and should be related.

Reading Group on Quantum Algorithms via Linear Algebra for Computational Linguistics and Natural Language Processing

In addition there is a reading group that meets also independently. The focus is on Linear Algebra, Deep Learning, and Quantum Algorithms using Linear Algebra, with the main goal to study and understand Quantum Machine Learning for Natural Language Processing (NLP). We will also look at the programming languages or environments for Quantum Computing, listed below.

The textbooks that we will use are:

• Quantum Algorithms via Linear Algebra by Richard J. Lipton and Kenneth W. Regan, MIT Press.
• Deep Learning by Ian Goodfellow, Yoshua Bengio, Aaron Courville, MIT Press.
• Coding the Matrix by Philip N. Klein, Newtonian Press.

We are interested in the Quantum Algorithms via Linear Algebra book, primarily, and in understanding ways how Quantum Algorithms could be utilized in NLP in general, and in Deep Learning approaches in particular.

There are various environments and projects that we are interested in, in this context:

• The Microsoft Quantum Development Kit
• The IBM Q project and the Python-based QISKit SDK for quantum algorithms
• Programming languages like Quipper

If you want to join this reading group (starting in the last May week of 2018), let me know, please!