Phd thesis on natural language processing

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I have broad interests in natural language processing and machine learning in particular, deep learning. My research is mostly driven by two goals: Developing effective and fundamental methods for learning representations of language and knowledge, and their interplay. I am specifically interested in how human knowledge e. Building practical systems including question answering, information extraction and conversational agents. I am mostly excited about simple and principled approaches which can be scalable and generalizable to real-world scenarios.
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Natural Language Processing and Computational Linguistics

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Natural Language Processing | Doctoral Program - Information Engineering and Computer Science

Researchers in network science have traditionally relied on user-defined heuristics to extract features from complex networks e. However, recent years have seen a surge in approaches that automatically learn to encode network structure into low-dimensional embeddings, using techniques based on deep learning and nonlinear dimensionality reduction. These network representation learning NRL approaches remove the need for painstaking feature engineering and have led to state-of-the-art results in network-based tasks, such as node classification, node clustering, and link prediction. In this tutorial, we will cover key advancements in NRL over the last decade, with an emphasis on fundamental advancements made in the last two years. We will discuss classic matrix factorization-based methods, random-walk based algorithms e. We will cover methods to embed individual nodes as well as approaches to embed entire sub graphs, and in doing so, we will present a unified framework for NRL.
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PHD RESEARCH TOPIC IN TEXT MINING

The Department of Biological Sciences offers a program of advanced study in the areas of molecular and cellular biology, neurobiology, physiology, immunology, genetics, structural and computational biology, developmental biology, molecular biophysics, bioinformatics, and chemical biology. The graduate program provides each student with a strong background in contemporary biology and an in-depth knowledge of one or more of the above areas. During the first year, all students take an intensive core course that provides a solid background in structural biochemistry, cell biology, genetics, and molecular biology. Two additional elective courses are required, which are generally completed in the second year. A departmental colloquium is held each Monday at noon throughout the academic year.
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All сomments (8)

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