Kernels are similarity functions, and play important roles in machine learning. Traditional kernels are built directly from the feature vectors of data ...
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Collective Kernel Construction in Noisy Environment. Miao Zhang ∗. Chris Ding †. Deguang Kong ‡. Abstract. Kernels are similarity functions, and play important ...
Publications · Collective Kernel Construction in Noisy Environment. Proc. 2013 SIAM Int. Conf. on Data Mining (SDM'13). Traditional kernels are built directly ...
Nov 18, 2022 · We determine how the performance of noisy kernel machines scales with the number of nodes (chain sites) as a function of decoherence and examine ...
Missing: Collective Construction Environment.
May 31, 2024 · In this paper, we propose a model based on multiple views and kernel-matrix tensor decomposition to predict the noise situation at different ...
To take care of noises greater comprehensively, in this paper, we suggest a singular Local and Global De-noising Multiple Kernel Learning technique. We examine ...
Either there is not enough data to ensure that the matrix X. X is invertible, or there may be noise in the data making it unwise to try to match the target ...
Via kernel-assisted memory copy, the collective algorithms offload copy tasks onto non-leader/not-root processes to evenly distribute copy workloads among ...
Collective Kernel Construction in Noisy Environment · Ratio-Based Multiple Kernel Clustering · Aristidis Likas. 2014, Lecture Notes in Computer Science.