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Yaser Abu Mostafa
Yaser Abu Mostafa
Professor of Electrical Engineering and Computer Science
Yaser Abu-Mostafa's group works on the theory, algorithms, and applications of machine learning (ML). Their goal is to understand the principles of how learning works and to develop learning solutions for real-life problems. They have successfully applied ML to a variety of practical problems. Among the applications they have worked on are financial forecasting, medical image classification, industrial inspection, recommender systems, and credit approval. All of these problems, and many others, share the same premise of a data set generated by an underlying process. The process cannot be mathematically pinned down, and ML enables us to infer what the process is based on the available data.
Publications
- Cramer, Estee Y.;Huang, Yuxin et al. (2022) The United States COVID-19 Forecast Hub datasetScientific Data
- Yurk, Dominic;Abu-Mostafa, Yaser (2021) County-Specific, Real-Time Projection of the Effect of Business Closures on the COVID-19 Pandemic
- González, Carlos R.;Abu-Mostafa, Yaser S. (2015) Mismatched Training and Test Distributions Can Outperform Matched OnesNeural Computation
- Abu-Mostafa, Yaser S. (2012) Machines that Think for ThemselvesScientific American
- Li, Ling;Abu-Mostafa, Yaser S. (2006) Data complexity in machine learning
- Angelova, Anelia;Abu-Mostafa, Yaser S. et al. (2005) Pruning training sets for learning of object categories
- Li, Ling;Pratap, Amrit et al. (2005) Improving Generalization by Data Categorization
- Li, Ling;Martinoli, Alcherio et al. (2004) Learning and Measuring Specialization in Collaborative Swarm SystemsAdaptive Behavior
- Abu-Mostafa, Yaser;Song, Xubo et al. (2004) The Bin Model
- Magdon-Ismail, Malik;Atiya, Amir F. et al. (2004) On the Maximum Drawdown of a Brownian MotionJournal of Applied Probability