Add to ORKGMachine learning algorithms detects patterns, regularities, and rules from the training data and adjust program actions accordingly. For example, when a learner (a computer program) sees a set of patient cases (patient records) with corresponding diagnoses, it can predict the presence of a disease for future patients. A somewhat unrealistic assumption in typical machine learning applications is that data is freely available. In my dissertation, I will present our research efforts to mitigate this assumption in the areas of active machine learning and budgeted machine learning
People may be surprised by noticing certain regularities that hold in existing knowledge they have h...
Student Thesis (NPS NRP Project Related)The rise of accessible real-world data creates a growing int...
Wide-ranging digitalization has made it possible to capture increasingly larger amounts of data. In ...
Machine learning algorithms detects patterns, regularities, and rules from the training data and adj...
Machine learning algorithms detects patterns, regularities, and rules from the training data and adj...
A sometimes unrealistic assumption in typical machine learning applications is that data is freely a...
In this article, we present a collection of fifteen novel contributions on machine learning methods ...
Training datasets for machine learning often have some form of missingness. For example, to learn a ...
We are surrounded by data in our daily lives. The rent of our houses, the amount of electricity unit...
Real-world learning tasks often involve high-dimensional data sets with complex patterns of missing...
The focus of this thesis is on understanding machine learning algorithms from an information-theoret...
Learning from data that contain missing values represents a common phenomenon in many domains. Relat...
abstract: Recently, a well-designed and well-trained neural network can yield state-of-the-art resul...
M.Sc. (Computer Science)Abstract: It is a well-known fact that the quality of the dataset plays a ce...
Because of the increasing popularity of machine learning methods, it is becoming important to unders...
People may be surprised by noticing certain regularities that hold in existing knowledge they have h...
Student Thesis (NPS NRP Project Related)The rise of accessible real-world data creates a growing int...
Wide-ranging digitalization has made it possible to capture increasingly larger amounts of data. In ...
Machine learning algorithms detects patterns, regularities, and rules from the training data and adj...
Machine learning algorithms detects patterns, regularities, and rules from the training data and adj...
A sometimes unrealistic assumption in typical machine learning applications is that data is freely a...
In this article, we present a collection of fifteen novel contributions on machine learning methods ...
Training datasets for machine learning often have some form of missingness. For example, to learn a ...
We are surrounded by data in our daily lives. The rent of our houses, the amount of electricity unit...
Real-world learning tasks often involve high-dimensional data sets with complex patterns of missing...
The focus of this thesis is on understanding machine learning algorithms from an information-theoret...
Learning from data that contain missing values represents a common phenomenon in many domains. Relat...
abstract: Recently, a well-designed and well-trained neural network can yield state-of-the-art resul...
M.Sc. (Computer Science)Abstract: It is a well-known fact that the quality of the dataset plays a ce...
Because of the increasing popularity of machine learning methods, it is becoming important to unders...
People may be surprised by noticing certain regularities that hold in existing knowledge they have h...
Student Thesis (NPS NRP Project Related)The rise of accessible real-world data creates a growing int...
Wide-ranging digitalization has made it possible to capture increasingly larger amounts of data. In ...