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