Co-Director, Autonomous Learning Lab
Associate Editor, Journal of Machine Learning Research
Research Areas:
Artificial Intelligence
Representation Discovery
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Co-Director, Autonomous Learning Lab Associate Editor, Journal of Machine Learning Research Research Areas: Artificial Intelligence Representation Discovery |
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My research interests are broadly in the areas of artificial intelligence, decision-making, and machine learning. Many successful intelligent systems over the past 50 years have relied on human expertise to carefully handcode a representation. A major new challenge for AI research is automating representation discovery by developing algorthms for automatically constructing features or basis functions that reflect the nonlinear geometry of a data or state space. My current research into representation discovery builds on harmonic analysis, a subfield of mathematics where spatial and temporal data is transformed into a frequency oriented coordinate system. I am exploring both global Fourier techniques based on diagonalization principles, such as eigenvector representations (e.g. Laplacian eigenfunctions), as well as multiscale representations, such as diffusion wavelet analysis. I am also exploring group representation theory for building compact basis functions on large "symmetric" spaces. Applications include 3D computer graphics, information retrieval, Markov decision processes, natural language processing, and robot learning.
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Check out my new book on Representation Discovery |
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My earlier book on Robot Learning |
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Contact InformationSridhar MahadevanDepartment of Computer Science 140 Governor's Drive University of Massachusetts Amherst, MA 01003 Administrative Assistant: Gwyn Mitchell, mitchell@cs.umass.edu VOICE: (413)545-3140
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