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A two-step learning approach for solving full and almost full cold start
  problems in dyadic prediction

A two-step learning approach for solving full and almost full cold start problems in dyadic prediction

17 May 2014
T. Pahikkala
Michiel Stock
A. Airola
T. Aittokallio
B. De Baets
Willem Waegeman
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Papers citing "A two-step learning approach for solving full and almost full cold start problems in dyadic prediction"

5 / 5 papers shown
Title
Incorporating Side Information in Probabilistic Matrix Factorization
  with Gaussian Processes
Incorporating Side Information in Probabilistic Matrix Factorization with Gaussian Processes
Ryan P. Adams
George E. Dahl
Iain Murray
106
88
0
09 Aug 2014
Classifying pairs with trees for supervised biological network inference
Classifying pairs with trees for supervised biological network inference
Marie Schrynemackers
L. Wehenkel
M. Babu
Pierre Geurts
39
19
0
24 Apr 2014
Efficient Regularized Least-Squares Algorithms for Conditional Ranking
  on Relational Data
Efficient Regularized Least-Squares Algorithms for Conditional Ranking on Relational Data
T. Pahikkala
A. Airola
Michiel Stock
B. De Baets
Willem Waegeman
41
38
0
21 Sep 2012
A kernel-based framework for learning graded relations from data
A kernel-based framework for learning graded relations from data
Willem Waegeman
T. Pahikkala
A. Airola
T. Salakoski
Michiel Stock
B. De Baets
59
30
0
28 Nov 2011
Kernels for Vector-Valued Functions: a Review
Kernels for Vector-Valued Functions: a Review
Mauricio A. Alvarez
Lorenzo Rosasco
Neil D. Lawrence
GP
207
925
0
30 Jun 2011
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