74 search results - page 14 / 15 » Regret Bounds for Gaussian Process Bandit Problems |
JMLR
2010
13 years 6 months ago
2010
A wide variety of machine learning problems can be described as minimizing a regularized risk functional, with different algorithms using different notions of risk and differen...
SIAMCO
2002
13 years 7 months ago
2002
There is a large literature on the rate of convergence problem for general unconstrained stochastic approximations. Typically, one centers the iterate n about the limit point then...
CDC
2008
IEEE
13 years 7 months ago
2008
IEEE
Minimizing the rank of a matrix subject to constraints is a challenging problem that arises in many applications in control theory, machine learning, and discrete geometry. This c...
CSDA
2010
13 years 7 months ago
2010
The Gaussian kernel density estimator is known to have substantial problems for bounded random variables with high density at the boundaries. For i.i.d. data several solutions hav...
MP
2011
13 years 2 months ago
2011
Minimizing the rank of a matrix subject to constraints is a challenging problem that arises in many applications in machine learning, control theory, and discrete geometry. This c...