… apply the kernel non-second order loss function to the orthogonal matching pursuit algorithm
and … Then we obtain a new approximation xk by solving the kernel non-second order loss …

… Motivated by this, in this paper, we discuss a new kernel based method for the classification
… 4 and 5, we present kernel OMP and a new classification method based on it. We provide …

… We propose a new greedy and adaptive matching pursuit (AMP) algorithm to directly solve
this hard problem. Essentially, in each step of the algorithm, the set of active elements would …

… To solve the problems mentioned above, we proposed a new matching pursuit method that
… Since the ITL has a close relationship with the kernel methods, we will introduce a similarity …

… Relying on this new model, we propose a matching pursuit-based total variation … improves
the robustness to errors in blur kernel. Extensive experiments on different tasks demonstrate …

… Kernel Risk-Sensitive Loss Based Matching Pursuit Extreme Learning Machine … propose a
robust kernel risk-sensitive loss based orthogonal matching pursuit extreme learning machine …

… Based on an iterative greedy algorithm, called the orthogonal matching pursuit, the signal is
expanded in terms of trial functions which are picked from a large redundant set of functions, …

… constant weights, we use heat kernel weights for the SLPP, … we propose applying our fast
matching pursuit (FMP) algorithm [… Furthermore, we use a heat kernel for weights to improve the …

… To tackle these issues, we propose an efficient Matching Pursuit algorithm for Generalized
… for the first time, and propose a matching pursuit algorithm to solve it. Instead of handling all …

… pursuit algorithms (eg, OMP and Matching Pursuit). We do not require explicit estimates
of model order, and provide a stopping criterion based on CFAR (constant false alarm rate) …