701 search results - page 111 / 141 » Self Bounding Learning Algorithms |
NIPS
2007
13 years 9 months ago
2007
We present a general boosting method extending functional gradient boosting to optimize complex loss functions that are encountered in many machine learning problems. Our approach...
PKDD
2010
Springer
13 years 6 months ago
2010
Springer
Abstract. Bayesian reinforcement learning (RL) is aimed at making more efficient use of data samples, but typically uses significantly more computation. For discrete Markov Decis...
JMLR
2006
13 years 7 months ago
2006
Receiver Operating Characteristic (ROC) curves are a standard way to display the performance of a set of binary classifiers for all feasible ratios of the costs associated with fa...
PKDD
2010
Springer
13 years 5 months ago
2010
Springer
We consider the problem of numerical stability and model density growth when training a sparse linear model from massive data. We focus on scalable algorithms that optimize certain...
JMLR
2012
11 years 10 months ago
2012
Variable selection is an important and practical problem that arises in analysis of many high-dimensional datasets. Convex optimization procedures that arise from relaxing the NP-...