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NIPS
2001
15 years 4 months ago
Unsupervised Learning of Human Motion Models
This paper presents an unsupervised learning algorithm that can derive the probabilistic dependence structure of parts of an object (a moving human body in our examples) automatic...
Yang Song, Luis Goncalves, Pietro Perona
ICCV
2011
IEEE
14 years 3 months ago
Adaptive Deconvolutional Networks for Mid and High Level Feature Learning
We present a hierarchical model that learns image decompositions via alternating layers of convolutional sparse coding and max pooling. When trained on natural images, the layers ...
Matthew D. Zeiler, Graham W. Taylor, Rob Fergus
TSE
2010
155views more  TSE 2010»
15 years 1 months ago
A Comparison of Six UML-Based Languages for Software Process Modeling
— Describing and managing activities, resources and constraints of software development processes is a challenging goal for many organizations. A first generation of Software Pro...
Reda Bendraou, Jean-Marc Jézéquel, M...
ECCV
2010
Springer
15 years 6 months ago
Modeling Temporal Structure of Decomposable Motion Segments for Activity Classification
Abstract. Much recent research in human activity recognition has focused on the problem of recognizing simple repetitive (walking, running, waving) and punctual actions (sitting up...
JMLR
2008
209views more  JMLR 2008»
15 years 3 months ago
Bayesian Inference and Optimal Design for the Sparse Linear Model
The linear model with sparsity-favouring prior on the coefficients has important applications in many different domains. In machine learning, most methods to date search for maxim...
Matthias W. Seeger