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ICML
2006
IEEE
14 years 10 months ago
An analytic solution to discrete Bayesian reinforcement learning
Reinforcement learning (RL) was originally proposed as a framework to allow agents to learn in an online fashion as they interact with their environment. Existing RL algorithms co...
Pascal Poupart, Nikos A. Vlassis, Jesse Hoey, Kevi...
KDD
2007
ACM
149views Data Mining» more  KDD 2007»
14 years 9 months ago
Partial example acquisition in cost-sensitive learning
It is often expensive to acquire data in real-world data mining applications. Most previous data mining and machine learning research, however, assumes that a fixed set of trainin...
Victor S. Sheng, Charles X. Ling
ICALT
2007
IEEE
14 years 3 months ago
Impact of Process Goal and Outcome Goal on Learning Performance for Web-based Learners
The purpose of this research is to develop a webbased learning environment where teachers can provide subject content using SCORM Simple Sequence Specification (SSS) mechanism wit...
Nian-Shing Chen, Kinshuk, Chun-Wang Wei, Feng-Hsie...
ICML
2004
IEEE
14 years 2 months ago
Active learning using pre-clustering
The paper is concerned with two-class active learning. While the common approach for collecting data in active learning is to select samples close to the classification boundary,...
Hieu Tat Nguyen, Arnold W. M. Smeulders
ECML
2004
Springer
14 years 2 months ago
SWITCH: A Novel Approach to Ensemble Learning for Heterogeneous Data
The standard framework of machine learning problems assumes that the available data is independent and identically distributed (i.i.d.). However, in some applications such as image...
Rong Jin, Huan Liu