225 search results - page 25 / 45 » On Learning Decision Trees with Large Output Domains |
KDD
2010
ACM
13 years 11 months ago
2010
ACM
In this paper we propose a novel algorithm for multi-task learning with boosted decision trees. We learn several different learning tasks with a joint model, explicitly addressing...
EDBT
2009
ACM
14 years 11 days ago
2009
ACM
Structured data including sets, sequences, trees and graphs, pose significant challenges to fundamental aspects of data management such as efficient storage, indexing, and simila...
CVPR
2010
IEEE
14 years 3 months ago
2010
IEEE
We present a method for detecting and parsing buildings from unorganized 3D point clouds into a compact, hierarchical representation that is useful for high-level tasks. The input...
FOCS
2005
IEEE
14 years 1 months ago
2005
IEEE
We prove the first non-trivial (super linear) lower bound in the noisy broadcast model, defined by El Gamal in [6]. In this model there are n + 1 processors P0, P1, . . . , Pn, ...
ICML
2001
IEEE
14 years 8 months ago
2001
IEEE
Hierarchical reinforcement learning (RL) is a general framework which studies how to exploit the structure of actions and tasks to accelerate policy learning in large domains. Pri...