Conjugate gradient methods form a class of iterative algorithms that are highly effective for solving large‐scale unconstrained optimisation problems. They achieve efficiency by constructing search ...
ABSTRACT: Three PRP-type direct search methods for unconstrained optimization are presented. The methods adopt three kinds of recently developed descent conjugate gradient methods and the idea of ...
Abstract: Backpropagation neural networks are commonly utilized to solve complicated issues in various disciplines. However, optimizing their settings remains a significant task. Traditional ...
Abstract: With the evolution toward 6G wireless networks, new technologies such as reconfigurable intelligent surfaces (RIS) and non-orthogonal multiple access (NOMA) are considered to meet increasing ...
There are several optimization techniques available in PROC NLMIXED. You can choose a particular optimizer with the TECH=name option in the PROC NLMIXED statement. No algorithm for optimizing general ...
GPU-accelerated linear solvers based on the conjugate gradient (CG) method, supporting NVIDIA and AMD GPUs with GPU-aware MPI, NCCL, RCCL or NVSHMEM ...
Rust + WASM sublinear-time solver for asymmetric diagonally dominant systems. Exposes Neumann series, push, and hybrid random-walk algorithms with npm/npx CLI and Flow-Nexus HTTP streaming for swarm ...
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