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» The Inefficiency of Batch Training for Large Training Sets
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MM
2005
ACM
143views Multimedia» more  MM 2005»
14 years 2 months ago
Hierarchical voting classification scheme for improving visual sign language recognition
As one of the important research areas of multimodal interaction, sign language recognition (SLR) has attracted increasing interest. In SLR, especially on medium or large vocabula...
Liang-Guo Zhang, Xilin Chen, Chunli Wang, Wen Gao
ACL
2001
13 years 10 months ago
Scaling to Very Very Large Corpora for Natural Language Disambiguation
The amount of readily available on-line text has reached hundreds of billions of words and continues to grow. Yet for most core natural language tasks, algorithms continue to be o...
Michele Banko, Eric Brill
TSP
2010
13 years 3 months ago
Recursive least squares dictionary learning algorithm
We present the Recursive Least Squares Dictionary Learning Algorithm, RLSDLA, which can be used for learning overcomplete dictionaries for sparse signal representation. Most Dicti...
Karl Skretting, Kjersti Engan
CVPR
2008
IEEE
14 years 10 months ago
Incremental learning of nonparametric Bayesian mixture models
Clustering is a fundamental task in many vision applications. To date, most clustering algorithms work in a batch setting and training examples must be gathered in a large group b...
Ryan Gomes, Max Welling, Pietro Perona
ML
2008
ACM
152views Machine Learning» more  ML 2008»
13 years 8 months ago
Learning near-optimal policies with Bellman-residual minimization based fitted policy iteration and a single sample path
Abstract. We consider batch reinforcement learning problems in continuous space, expected total discounted-reward Markovian Decision Problems. As opposed to previous theoretical wo...
András Antos, Csaba Szepesvári, R&ea...