3 citations · 6 across the 9 of their papers we have counts for
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stat.CO2017
Sequential Inverse Approximation of a Regularized Sample Covariance Matrix
Tomer Lancewicki
One of the goals in scaling sequential machine learning methods pertains to dealing with high-dimensional data spaces. A key related challenge is that many methods heavily depend o…
stat.CO2017★ 3 cited
Regularization of the Kernel Matrix via Covariance Matrix Shrinkage Estimation
Tomer Lancewicki
The kernel trick concept, formulated as an inner product in a feature space, facilitates powerful extensions to many well-known algorithms. While the kernel matrix involves inner p…