Approximation Vector Machines for Large-scale Online Learning

22 Apr 2016 Trung Le Tu Dinh Nguyen Vu Nguyen Dinh Phung

One of the most challenging problems in kernel online learning is to bound the model size and to promote the model sparsity. Sparse models not only improve computation and memory usage, but also enhance the generalization capacity, a principle that concurs with the law of parsimony... (read more)

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