56 search results - page 6 / 12 » Minimizing Convex Functions with Bounded Perturbations |
103
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NIPS
2008
14 years 11 months ago
2008
This paper addresses the important tradeoff between privacy and learnability, when designing algorithms for learning from private databases. We focus on privacy-preserving logisti...
CDC
2008
IEEE
15 years 4 months ago
2008
IEEE
— In modern robust control, control synthesis may be cast as an interpolation problem where the interpolant relates to robustness and performance criteria. In particular, robustn...
108
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MP
2011
14 years 4 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...
COLT
1999
Springer
15 years 1 months ago
1999
Springer
We present a unified framework for reasoning about worst-case regret bounds for learning algorithms. This framework is based on the theory of duality of convex functions. It brin...
JMLR
2006
14 years 9 months ago
2006
We determine the asymptotic behaviour of the function computed by support vector machines (SVM) and related algorithms that minimize a regularized empirical convex loss function i...