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NIPS
2003
15 years 8 months ago
Can We Learn to Beat the Best Stock
A novel algorithm for actively trading stocks is presented. While traditional universal algorithms (and technical trading heuristics) attempt to predict winners or trends, our app...
Allan Borodin, Ran El-Yaniv, Vincent Gogan
UAI
1998
15 years 8 months ago
A Multivariate Discretization Method for Learning Bayesian Networks from Mixed Data
In this paper we address the problem of discretization in the context of learning Bayesian networks (BNs) from data containing both continuous and discrete variables. We describe ...
Stefano Monti, Gregory F. Cooper
SODA
2000
ACM
85views Algorithms» more  SODA 2000»
15 years 8 months ago
Improved bounds on the sample complexity of learning
We present a new general upper bound on the number of examples required to estimate all of the expectations of a set of random variables uniformly well. The quality of the estimat...
Yi Li, Philip M. Long, Aravind Srinivasan
SLP
1989
105views more  SLP 1989»
15 years 7 months ago
Automatic Ordering of Subgoals - A Machine Learning Approach
This paper describes a learning system, LASSY1, which explores domains represented by Prolog databases, and use its acquired knowledge to increase the efficiency of a Prolog inter...
Shaul Markovitch, Paul D. Scott
BDA
2007
15 years 8 months ago
Hyperplane Queries in a Feature-Space M-tree for Speeding up Active Learning
In content-based retrieval, relevance feedback (RF) is a noticeable method for reducing the “semantic gap” between the low-level features describing the content and the usually...
Michel Crucianu, Daniel Estevez, Vincent Oria, Jea...