Sökning: "Statistical Learning Techniques"

Visar resultat 1 - 5 av 57 avhandlingar innehållade orden Statistical Learning Techniques.

1. 1. Statistical Feature Selection : With Applications in Life Science

   Författare :Roland Nilsson; Jesper Tegnér; Johan Björkegren; Sepp Hochreiter; Linköpings universitet; []
   Nyckelord :NATURVETENSKAP; NATURAL SCIENCES; Machine learning; supervised learning; classification; dimemsionality reduction; multiple testing; gene expression; microarray; cancer; Bioinformatics; Bioinformatik;

   Sammanfattning : The sequencing of the human genome has changed life science research in many ways. Novel measurement technologies such as microarray expression analysis, genome-wide SNP typing and mass spectrometry are now producing experimental data of extremely high dimensions. LÄS MER

3. 2. Information-Theoretic Generalization Bounds: Tightness and Expressiveness

   Författare :Fredrik Hellström; Chalmers tekniska högskola; []
   Nyckelord :NATURVETENSKAP; NATURAL SCIENCES; TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; NATURVETENSKAP; NATURAL SCIENCES; NATURVETENSKAP; NATURAL SCIENCES; information theory; neural networks; generalization; statistical learning; meta learning; PAC-Bayes; Machine learning;

   Sammanfattning : Machine learning has achieved impressive feats in numerous domains, largely driven by the emergence of deep neural networks. Due to the high complexity of these models, classical bounds on the generalization error---that is, the difference between training and test performance---fail to explain this success. LÄS MER

4. 3. Bayesian learning of structured dynamical systems

   Författare :Riccardo Sven Risuleo; Håkan Hjalmarsson; Johan Schoukens; KTH; []
   Nyckelord :TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; system identification; bayesian learning; machine learning; Gaussian processes; Electrical Engineering; Elektro- och systemteknik;

   Sammanfattning : In this thesis, we propose some Bayesian approaches to the identificationof structured dynamical systems. In particular, we consider block-orientedmodels in which a complex system is built starting from simple linear andnonlinear building blocks. LÄS MER

5. 4. A Multi-Dimensional Approach to Human Mobility and Transportation Mode Detection Using GPS Data

   Författare :Paria Sadeghian; Johan Håkansson; Xiaoyun Zhao; Mengjie Han; Kevin Heaslip; Högskolan Dalarna; []
   Nyckelord :TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; NATURVETENSKAP; NATURAL SCIENCES; Transport mode detection; Machine learning; Statistical learning; Rule-based method; Data labelling;

   Sammanfattning : GPS tracking data is an essential resource for analyzing human travel patterns and evaluating the effects on transportation systems. The primary challenge, however, is to accurately identify the modes of transportation within unlabeled GPS data. These approaches range from simple rule-based systems to advanced machine-learning techniques. LÄS MER

7. 5. Guaranteeing Generalization via Measures of Information

   Författare :Fredrik Hellström; Chalmers tekniska högskola; []
   Nyckelord :NATURVETENSKAP; NATURAL SCIENCES; NATURVETENSKAP; NATURAL SCIENCES; NATURVETENSKAP; NATURAL SCIENCES; PAC-Bayes; statistical learning; information theory; Machine learning; neural networks.; generalization;

   Sammanfattning : During the past decade, machine learning techniques have achieved impressive results in a number of domains. Many of the success stories have made use of deep neural networks, a class of functions that boasts high complexity. Classical results that mathematically guarantee that a learning algorithm generalizes, i.e. LÄS MER