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TIT
1998
70views more  TIT 1998»
13 years 4 months ago
The Importance of Convexity in Learning with Squared Loss
We show that if the closureof a function class F under the metric induced by some probability distribution is not convex, then the sample complexity for agnostically learning F wi...
Wee Sun Lee, Peter L. Bartlett, Robert C. Williams...
EC
2008
103views ECommerce» more  EC 2008»
13 years 4 months ago
A Graphical Model for Evolutionary Optimization
We present a statistical model of empirical optimization that admits the creation of algorithms with explicit and intuitively defined desiderata. Because No Free Lunch theorems di...
Christopher K. Monson, Kevin D. Seppi
COLT
1994
Springer
13 years 8 months ago
Lower Bounds on the VC-Dimension of Smoothly Parametrized Function Classes
We examine the relationship between the VCdimension and the number of parameters of a smoothly parametrized function class. We show that the VC-dimension of such a function class ...
Wee Sun Lee, Peter L. Bartlett, Robert C. Williams...
COLT
2001
Springer
13 years 8 months ago
Rademacher and Gaussian Complexities: Risk Bounds and Structural Results
We investigate the use of certain data-dependent estimates of the complexity of a function class, called Rademacher and Gaussian complexities. In a decision theoretic setting, we ...
Peter L. Bartlett, Shahar Mendelson
CDC
2009
IEEE
172views Control Systems» more  CDC 2009»
13 years 9 months ago
Approximate dynamic programming using fluid and diffusion approximations with applications to power management
—TD learning and its refinements are powerful tools for approximating the solution to dynamic programming problems. However, the techniques provide the approximate solution only...
Wei Chen, Dayu Huang, Ankur A. Kulkarni, Jayakrish...