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» Learning with Continuous Experts Using Drifting Games
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IDA
2002
Springer
15 years 2 days ago
Online classification of nonstationary data streams
Most classification methods are based on the assumption that the data conforms to a stationary distribution. However, the real-world data is usually collected over certain periods...
Mark Last
GECCO
2007
Springer
214views Optimization» more  GECCO 2007»
15 years 6 months ago
Portfolio allocation using XCS experts in technical analysis, market conditions and options market
Schulenburg [15] first proposed the idea to model different trader types by supplying different input information sets to a group of homogenous LCS agent. Gershoff [12] investigat...
Sor Ying (Byron) Wong, Sonia Schulenburg
CHI
2009
ACM
16 years 27 days ago
Longitudinal study of people learning to use continuous voice-based cursor control
We conducted a 2.5 week longitudinal study with five motor impaired (MI) and four non-impaired (NMI) participants, in which they learned to use the Vocal Joystick, a voice-based u...
Susumu Harada, Jacob O. Wobbrock, Jonathan Malkin,...
FLAIRS
2003
15 years 1 months ago
Learning Opening Strategy in the Game of Go
In this paper, we present an experimental methodology and results for a machine learning approach to learning opening strategy in the game of Go, a game for which the best compute...
Timothy Huang, Graeme Connell, Bryan McQuade
CVPR
2009
IEEE
16 years 7 months ago
Learning Optimized MAP Estimates in Continuously-Valued MRF Models
We present a new approach for the discriminative training of continuous-valued Markov Random Field (MRF) model parameters. In our approach we train the MRF model by optimizing t...
Kegan G. G. Samuel, Marshall F. Tappen