Rocco Servedio
University/Research Lab: Columbia University
Location: (New York, NY)
Personal Research Web Page: http://www.cs.columbia.edu/~rocco
Keywords: computational learning theory, complexity theory, randomness in computation, property testing, Fourier analysis, communication complexity, lower bounds
Location: (New York, NY)
Personal Research Web Page: http://www.cs.columbia.edu/~rocco
Keywords: computational learning theory, complexity theory, randomness in computation, property testing, Fourier analysis, communication complexity, lower bounds
Posted on: Wednesday, June 3rd, 2009
Broad Research Area: AI / Machine Learning / Robotics / Vision, Theory / Algorithms
Research Interests:
I am interested in a range of topics in learning theory and complexity theory and adjacent areas. Recent topics of interest in complexity theory include property testing, structural properties of Boolean functions such as halfspaces and threshold functions, Fourier analysis, and pseudorandomness. Recent topics of interest in learning theory include boosting algorithms and efficient algorithms for various noisy learning problems. A recurring theme in my work is the application of complexity-theoretic ideas and tools to solve problems in learning theory (and vice versa).
