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» Learning Overcomplete Representations
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AI
2004
Springer
14 years 2 months ago
Intrinsic Representation: Bootstrapping Symbols from Experience
If we are to understand human-level intelligence, we need to understand how meanings can be learned without explicit instruction. I take a step toward that understanding by showing...
Stephen David Larson
CICLING
2007
Springer
14 years 2 months ago
Learning for Semantic Parsing
Semantic parsing is the task of mapping a natural language sentence into a complete, formal meaning representation. Over the past decade, we have developed a number of machine lear...
Raymond J. Mooney
ACL
2006
13 years 10 months ago
Using String-Kernels for Learning Semantic Parsers
We present a new approach for mapping natural language sentences to their formal meaning representations using stringkernel-based classifiers. Our system learns these classifiers ...
Rohit J. Kate, Raymond J. Mooney
CVPR
2008
IEEE
14 years 10 months ago
Hybrid body representation for integrated pose recognition, localization and segmentation
We propose a hybrid body representation that represents each typical pose by both template-like view information and part-based structural information. Specifically, each body par...
Cheng Chen, Guoliang Fan
ICML
2010
IEEE
13 years 9 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