التفاصيل البيبلوغرافية
| العنوان: |
Improving Learning Performance Through Rational Resource Allocation |
| المؤلفون: |
Gratch, J., Chien, S., DeJong, G. |
| سنة النشر: |
2004 |
| المجموعة: |
BEACON eSpace at Jet Propulsion Laboratory (California Institute of Technology / NASA JPL) |
| مصطلحات موضوعية: |
machine learning rational analysis parametric hypothesis selection problems resource optimization |
| الوصف: |
This article shows how rational analysis can be used to minimize learning cost for a general class of statistical learning problems. We discuss the factors that influence learning cost and show that the problem of efficient learning can be cast as a resource optimization problem. Solutions found in this way can be significantly more efficient than the best solutions that do not account for these factors. We introduce a heuristic learning algorithm that approximately solves this optimization problem and document its performance improvements on synthetic and real-world problems. |
| نوع الوثيقة: |
other/unknown material |
| وصف الملف: |
438642 bytes; application/pdf |
| اللغة: |
English |
| العلاقة: |
Seattle, Washington, USA; 94-0733; http://hdl.handle.net/2014/34387Test |
| الإتاحة: |
http://hdl.handle.net/2014/34387Test |
| رقم الانضمام: |
edsbas.47EEFD2D |
| قاعدة البيانات: |
BASE |
