57 search results - page 2 / 12 » Relative Loss Bounds for Multidimensional Regression Problem... |
COLT
2004
Springer
13 years 8 months ago
2004
Springer
This paper introduces a new method using dyadic decision trees for estimating a classification or a regression function in a multiclass classification problem. The estimator is bas...
COLT
1999
Springer
13 years 9 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...
CORR
2011
Springer
12 years 8 months ago
2011
Springer
We propose Shotgun, a parallel coordinate descent algorithm for minimizing L1regularized losses. Though coordinate descent seems inherently sequential, we prove convergence bounds...
NIPS
2008
13 years 6 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...
MP
2010
13 years 3 months ago
2010
Convex optimization problems arising in applications, possibly as approximations of intractable problems, are often structured and large scale. When the data are noisy, it is of i...