Show/Hide Menu
Hide/Show Apps
Logout
Türkçe
Türkçe
Search
Search
Login
Login
OpenMETU
OpenMETU
About
About
Open Science Policy
Open Science Policy
Open Access Guideline
Open Access Guideline
Postgraduate Thesis Guideline
Postgraduate Thesis Guideline
Communities & Collections
Communities & Collections
Help
Help
Frequently Asked Questions
Frequently Asked Questions
Guides
Guides
Thesis submission
Thesis submission
MS without thesis term project submission
MS without thesis term project submission
Publication submission with DOI
Publication submission with DOI
Publication submission
Publication submission
Supporting Information
Supporting Information
General Information
General Information
Copyright, Embargo and License
Copyright, Embargo and License
Contact us
Contact us
The Cauchy-Schwarz divergence and entropy-based density-weighted active learning
Download
METU_Thesis_Mehmet_Enes_Sen_.pdf
Date
2022-9
Author
Şen, Mehmet Enes
Metadata
Show full item record
This work is licensed under a
Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License
.
Item Usage Stats
193
views
134
downloads
Cite This
The general framework for active learning is explained. The existing active learning strategies are surveyed. The information-theoretic measures such as the entropy and the mutual information are analyzed as active learning objectives. The use of divergence measures in density-weighted active learning is discussed. A novel density-weighted active learning algorithm, based on Cauchy-Schwarz divergence and entropy, is introduced and compared with the state-of-the-art active learning strategies.
Subject Keywords
Active learning
,
Cauchy-Schwarz divergence
,
Entropy
,
Mutual information
,
Information-theory
,
Machine learning
URI
https://hdl.handle.net/11511/99757
Collections
Graduate School of Natural and Applied Sciences, Thesis
Suggestions
OpenMETU
Core
Recursive Compositional Reinforcement Learning for Continuous Control Sürekli Kontrol Uygulamalari için Özyinelemeli Bileşimsel Pekiştirmeli Öǧrenme
Tanik, Guven Orkun; Ertekin Bolelli, Şeyda (2022-01-01)
Compositional and temporal abstraction is the key to improving learning and planning in reinforcement learning. Modern real-world control problems call for continuous control domains and robust, sample efficient and explainable control frameworks. We are presenting a framework for recursively composing control skills to solve compositional and progressively complex tasks. The framework promotes reuse of skills, and as a result quickly adaptable to new tasks. The decision-tree can be observed, providing insi...
The effects of cognitive load in learning from goal based scenario designed multimedia learning environment for learners having different working memory capacities
Kılıç, Eylem; Yıldırım, Zahide; Department of Computer Education and Instructional Technology (2009)
The purpose of this study is to investigate the effects of principles aiming to reduce extraneous cognitive load in learning from goal based scenario designed multimedia learning environment for learners having different working memory capacities. In addition, the effects of goal based scenario and the principles of cognitive load theory on students’ perception, motivation and satisfaction has been explored. Two versions of the multimedia were developed for this study. In the first version (+CLT), the princ...
A Counting-Based Heuristic for ILP-Based Concept Discovery Systems
Mutlu, Alev; Karagöz, Pınar; Kavurucu, Yusuf (2013-09-13)
Concept discovery systems are concerned with learning definitions of a specific relation in terms of other relations provided as background knowledge. Although such systems have a history of more than 20 years and successful applications in various domains, they are still vulnerable to scalability and efficiency issues - mainly due to large search spaces they build. In this study we propose a heuristic to select a target instance that will lead to smaller search space without sacrificing the accuracy. The p...
The Investigation of Process of Teaching Function Concept in an Adidactic Learning Environment
Dikkartin Ovez, Filiz Tuba; Akar, Nazlı (2018-09-01)
This study investigates the learning of the concept of functions in an adidactic learning environment, explains the five phases of the adidactic learning environments defined in the Didactic Situation Theory and their interactions with the milieu generated within the given problem state of the students. It was carried out with 33 ninth grade students from an Anatolian high school in Balikesir. This qualitative study was designed as a case study. Descriptive analysis was used to analyze the data from student...
The Role of schemata in responsibility among people with traumatic event history
Topçu, Merve; Köroğlu, Deniz; Gençöz, Faruk (null; 2018-05-05)
Schemata can be thought of as an abstract cognitive plan that serves as a guide for solving problems and interpreting knowledge. Schemata rooted in the early childhood. Trauma can be defined as events which disrupt the daily routine, develop suddenly and unexpectedly, create horror, anxiety and panic, and disturb the process of making sense of the world. Trauma have an important role in development of early maladaptive schemata. However, after traumatic event exposure it is possible to show psychological im...
Citation Formats
IEEE
ACM
APA
CHICAGO
MLA
BibTeX
M. E. Şen, “The Cauchy-Schwarz divergence and entropy-based density-weighted active learning,” M.S. - Master of Science, Middle East Technical University, 2022.