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» Learning the Common Structure of Data
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TIP
2010
145views more  TIP 2010»
14 years 11 months ago
Joint Manifolds for Data Fusion
The emergence of low-cost sensing architectures for diverse modalities has made it possible to deploy sensor networks that capture a single event from a large number of vantage po...
Mark A. Davenport, Chinmay Hegde, Marco F. Duarte,...
CAMP
2005
IEEE
15 years 10 months ago
Virtual Astronomy, Information Technology, and the New Scientific Methodology
—All sciences, including astronomy, are now entering the era of information abundance. The exponentially increasing volume and complexity of modern data sets promises to transfor...
S. George Djorgovski
ATAL
2007
Springer
15 years 11 months ago
Batch reinforcement learning in a complex domain
Temporal difference reinforcement learning algorithms are perfectly suited to autonomous agents because they learn directly from an agent’s experience based on sequential actio...
Shivaram Kalyanakrishnan, Peter Stone
ICML
2010
IEEE
15 years 6 months ago
Robust Subspace Segmentation by Low-Rank Representation
We propose low-rank representation (LRR) to segment data drawn from a union of multiple linear (or affine) subspaces. Given a set of data vectors, LRR seeks the lowestrank represe...
Guangcan Liu, Zhouchen Lin, Yong Yu
PRIB
2009
Springer
135views Bioinformatics» more  PRIB 2009»
15 years 11 months ago
Sequential Hierarchical Pattern Clustering
Abstract. Clustering is a widely used unsupervised data analysis technique in machine learning. However, a common requirement amongst many existing clustering methods is that all p...
Bassam Farran, Amirthalingam Ramanan, Mahesan Nira...