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ICPR
2006
IEEE
16 years 7 months ago
Weakly Supervised Learning on Pre-image Problem in Kernel Methods
This paper presents a novel alternative approach, namely weakly supervised learning (WSL), to learn the pre-image of a feature vector in the feature space induced by a kernel. It ...
Weishi Zheng, Jian-Huang Lai, Pong Chi Yuen
FOCM
2008
140views more  FOCM 2008»
15 years 6 months ago
Online Gradient Descent Learning Algorithms
This paper considers the least-square online gradient descent algorithm in a reproducing kernel Hilbert space (RKHS) without explicit regularization. We present a novel capacity i...
Yiming Ying, Massimiliano Pontil
ML
2010
ACM
151views Machine Learning» more  ML 2010»
15 years 5 months ago
Inductive transfer for learning Bayesian networks
In several domains it is common to have data from different, but closely related problems. For instance, in manufacturing, many products follow the same industrial process but with...
Roger Luis, Luis Enrique Sucar, Eduardo F. Morales
DAGM
2011
Springer
14 years 6 months ago
Relaxed Exponential Kernels for Unsupervised Learning
Many unsupervised learning algorithms make use of kernels that rely on the Euclidean distance between two samples. However, the Euclidean distance is optimal for Gaussian distribut...
Karim T. Abou-Moustafa, Mohak Shah, Fernando De la...
AAAI
2006
15 years 8 months ago
From Pigeons to Humans: Grounding Relational Learning in Concrete Examples
We present a cognitive model that bridges work in analogy and category learning. The model, Building Relations through Instance Driven Gradient Error Shifting (BRIDGES), extends A...
Marc T. Tomlinson, Bradley C. Love