Machine Learning algorithms and
optimization techniques have become central to most applications of
computing ranging from search, ads, data-mining, data-analytics in large
databases, information retrieval and extraction, natural language
processing including machine translation, speech, vision, gaming, user
adaptation of computing systems, as well as security, privacy, and the
broad topic of crowd-sourcing. Our goal is to conduct research in
theoretical and practical aspects of Machine Learning and Optimization
including:
- Novel machine learning algorithms and paradigms
- Foundational aspects of optimization techniques, including new algorithms and applications to machine learning
- Theoretical analysis of machine learning and optimization algorithms
- Performance analysis and enhancement of machine learning and optimization algorithms
- Applications in search and IR, vision, NLP and other areas
- Data mining and data analytics for very large data sets
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