SwePub
Tyck till om SwePub Sök här!
Sök i SwePub databas

  Utökad sökning

Träfflista för sökning "WFRF:(Borga Magnus) ;conttype:(scientificother)"

Sökning: WFRF:(Borga Magnus) > Övrigt vetenskapligt/konstnärligt

  • Resultat 1-10 av 70
Sortera/gruppera träfflistan
   
NumreringReferensOmslagsbildHitta
1.
  •  
2.
  •  
3.
  • Artificial Neural Networks in Medicine and Biology
  • 2000
  • Samlingsverk (redaktörskap) (övrigt vetenskapligt/konstnärligt)abstract
    • This book contains the proceedings of ANNIMAB-1, the first international conference on artificial neural networks in medicine and biology. Comprising a selection of papers from leading researchers in the field, it summarises the state-of-the-art, analyses the relationship between ANN techniques and other available methods and points to possible future biomedical and medical uses of ANNs.
  •  
4.
  • Borga, Magnus, et al. (författare)
  • A Binary Competition Tree for Reinforcement Learning
  • 1994
  • Rapport (övrigt vetenskapligt/konstnärligt)abstract
    • A robust, general and computationally simple reinforcement learning system is presented. It uses a channel representation which is robust and continuous. The accumulated knowledge is represented as a reward prediction function in the outer product space of the input- and output channel vectors. Each computational unit generates an output simply by a vector-matrix multiplication and the response can therefore be calculated fast. The response and a prediction of the reward are calculated simultaneously by the same system, which makes TD-methods easy to implement if needed. Several units can cooperate to solve more complicated problems. A dynamic tree structure of linear units is grown in order to divide the knowledge space into a sufficiently number of regions in which the reward function can be properly described. The tree continuously tests split- and prune criteria in order to adapt its size to the complexity of the problem.
  •  
5.
  •  
6.
  • Borga, Magnus, 1965-, et al. (författare)
  • A canonical correlation approach to exploratory data analysis in fMRI
  • 2002
  • Konferensbidrag (övrigt vetenskapligt/konstnärligt)abstract
    • A computationally efficient data-driven method for exploratory analysis of functional MRI data is presented. The basic idea is to reveal underlying components in the fMRI data that have maximum autocorrelation. The tool for accomplishing this task is Canonical Correlation Analysis. The proposed method is more robust and much more computationally efficient than independent component analysis, which previously has been applied in fMRI.
  •  
7.
  • Borga, Magnus, et al. (författare)
  • A Survey of Current Techniques for Reinforcement Learning
  • 1992
  • Rapport (övrigt vetenskapligt/konstnärligt)abstract
    • This survey considers response generating systems that improve their behaviour using reinforcement learning. The difference between unsupervised learning, supervised learning, and reinforcement learning is described. Two general problems concerning learning systems are presented; the credit assignment problem and the problem of perceptual aliasing. Notations and some general issues concerning reinforcement learning systems are presented. Reinforcement learning systems are further divided into two main classes; memory mapping and projective mapping systems. Each of these classes is described and some examples are presented. Some other approaches are mentioned that do not fit into the two main classes. Finally some issues not covered by the surveyed articles are discussed, and some comments on the subject are made.
  •  
8.
  • Borga, Magnus, et al. (författare)
  • A Unified Approach to PCA, PLS, MLR and CCA
  • 1997
  • Rapport (övrigt vetenskapligt/konstnärligt)abstract
    • This paper presents a novel algorithm for analysis of stochastic processes. The algorithm can be used to find the required solutions in the cases of principal component analysis (PCA), partial least squares (PLS), canonical correlation analysis (CCA) or multiple linear regression (MLR). The algorithm is iterative and sequential in its structure and uses on-line stochastic approximation to reach an equilibrium point. A quotient between two quadratic forms is used as an energy function and it is shown that the equilibrium points constitute solutions to the generalized eigenproblem.
  •  
9.
  •  
10.
  •  
Skapa referenser, mejla, bekava och länka
  • Resultat 1-10 av 70
Typ av publikation
konferensbidrag (49)
rapport (10)
doktorsavhandling (6)
licentiatavhandling (3)
samlingsverk (redaktörskap) (1)
annan publikation (1)
visa fler...
visa färre...
Typ av innehåll
övrigt vetenskapligt/konstnärligt  (70)Ta bort avgränsningen
Författare/redaktör
Borga, Magnus (43)
Borga, Magnus, 1965- (22)
Dahlqvist Leinhard, ... (19)
Knutsson, Hans, 1950 ... (16)
Knutsson, Hans (16)
Romu, Thobias (15)
visa fler...
Lundberg, Peter (8)
Dahlqvist Leinhard, ... (7)
Karlsson, Anette (7)
Smedby, Örjan (5)
Bell, Jimmy (4)
Linge, Jennifer (4)
Lundberg, Peter, 195 ... (3)
Johansson, Andreas (3)
Kihlberg, Johan (2)
Rydell, Joakim (2)
Sirlin, Claude B. (2)
Malmgren, Helge, 194 ... (2)
Hammar, Mats (2)
Lindh-Åstrand, Lotta (2)
Moreno, Rodrigo, 197 ... (2)
Lindblom, Hanna (2)
Spetz, Anna-Clara (2)
Nyström, Fredrik (2)
Smedby, Örjan, 1956- (1)
Andersson, Mats (1)
Ekholm, S (1)
Nyström, Fredrik H. (1)
Starck, Göran (1)
Loomba, Rohit (1)
Olsson, E (1)
Farnebäck, Gunnar (1)
Wigström, Lars (1)
Almer, Sven (1)
Thomas, E. Louise (1)
Lenz, Reiner (1)
Ekholm, Sven (1)
Malmgren, H (1)
Andersson, Mats, 196 ... (1)
Andersson, Thord (1)
Läthén, Gunnar (1)
Norén, Bengt (1)
Forsgren, Mikael (1)
Andersson, Thord, 19 ... (1)
Carlsson, Tomas (1)
Niklasson, Lars, 196 ... (1)
Pettersson, Johanna (1)
Lansner, Anders (1)
Friberg, M. (1)
Elander, Louise (1)
visa färre...
Lärosäte
Linköpings universitet (67)
Göteborgs universitet (2)
Kungliga Tekniska Högskolan (1)
Språk
Engelska (70)
Forskningsämne (UKÄ/SCB)
Medicin och hälsovetenskap (30)
Teknik (29)
Naturvetenskap (6)
Humaniora (1)

År

Kungliga biblioteket hanterar dina personuppgifter i enlighet med EU:s dataskyddsförordning (2018), GDPR. Läs mer om hur det funkar här.
Så här hanterar KB dina uppgifter vid användning av denna tjänst.

 
pil uppåt Stäng

Kopiera och spara länken för att återkomma till aktuell vy