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FOCS
2010
IEEE
13 years 2 months ago
Learning Convex Concepts from Gaussian Distributions with PCA
We present a new algorithm for learning a convex set in n-dimensional space given labeled examples drawn from any Gaussian distribution. The complexity of the algorithm is bounded ...
Santosh Vempala
ECCC
2010
124views more  ECCC 2010»
13 years 4 months ago
Lower Bounds and Hardness Amplification for Learning Shallow Monotone Formulas
Much work has been done on learning various classes of "simple" monotone functions under the uniform distribution. In this paper we give the first unconditional lower bo...
Vitaly Feldman, Homin K. Lee, Rocco A. Servedio
COLT
2001
Springer
13 years 9 months ago
Intrinsic Complexity of Learning Geometrical Concepts from Positive Data
Intrinsic complexity is used to measure the complexity of learning areas limited by broken-straight lines (called open semi-hulls) and intersections of such areas. Any strategy le...
Sanjay Jain, Efim B. Kinber
FOCS
2008
IEEE
13 years 11 months ago
Learning Geometric Concepts via Gaussian Surface Area
We study the learnability of sets in Rn under the Gaussian distribution, taking Gaussian surface area as the “complexity measure” of the sets being learned. Let CS denote the ...
Adam R. Klivans, Ryan O'Donnell, Rocco A. Servedio
COMPGEOM
2011
ACM
12 years 8 months ago
Three problems about dynamic convex hulls
We present three results related to dynamic convex hulls: • A fully dynamic data structure for maintaining a set of n points in the plane so that we can find the edges of the c...
Timothy M. Chan