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» On Kernel Methods for Relational Learning
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146
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CVPR
2004
IEEE
16 years 5 months ago
Model-Based Motion Clustering Using Boosted Mixture Modeling
Model-based clustering of motion trajectories can be posed as the problem of learning an underlying mixture density function whose components correspond to motion classes with dif...
Vladimir Pavlovic
116
Voted
EMNLP
2006
15 years 5 months ago
Inducing Temporal Graphs
We consider the problem of constructing a directed acyclic graph that encodes temporal relations found in a text. The unit of our analysis is a temporal segment, a fragment of tex...
Philip Bramsen, Pawan Deshpande, Yoong Keok Lee, R...
125
Voted
MLDM
2005
Springer
15 years 9 months ago
Unsupervised Learning of Visual Feature Hierarchies
We propose an unsupervised, probabilistic method for learning visual feature hierarchies. Starting from local, low-level features computed at interest point locations, the method c...
Fabien Scalzo, Justus H. Piater
157
Voted
MIR
2005
ACM
129views Multimedia» more  MIR 2005»
15 years 9 months ago
Tracking concept drifting with an online-optimized incremental learning framework
Concept drifting is an important and challenging research issue in the field of machine learning. This paper mainly addresses the issue of semantic concept drifting in time series...
Jun Wu, Dayong Ding, Xian-Sheng Hua, Bo Zhang
160
Voted
WEBI
2010
Springer
15 years 1 months ago
DSP: Robust Semi-supervised Dimensionality Reduction Using Dual Subspace Projections
High-dimensional data usually incur learning deficiencies and computational difficulties. We present a novel semi-supervised dimensionality reduction technique that embeds high-dim...
Su Yan, Sofien Bouaziz, Dongwon Lee