IEEE

An Inner Approximation Algorithm for Dynamic Optimization with Strict Satisfaction of Path Constraints

Abstract: An inner approximation algorithm is proposed for path-constrained dynamic optimization (PCDO) by iteratively solving restrictions of PCDO (RPCDO). Firstly, an upper bound function of the ...
GitHub

Trust Region Preference Approximation: A simple and stable reinforcement learning algorithm for LLM reasoning

We propose the Trust Region Preference Approximation (TRPA) algorithm ⚙️, which integrates rule-based optimization with preference-based optimization for LLM reasoning tasks 🤖🧠. As a ...
C&EN

Machine Learning K-Means Clustering of Interpolative Separable Density Fitting Algorithm for Accurate and Efficient Cubic-Scaling Exact Exchange Plus Random Phase Approximation ...

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Scientific Research Publishing

M. X. Goemans and D. P. Williamson, “Improved Approximation Algorithms for Maximum Cut and Satisfiability Problems Using Semidefinite Programming,” Journal of the ACM, Vol ...

ABSTRACT: The purpose of reoptimization using approximation methods—application of knowledge about the solution of the initial instance I, provided to achieve a better quality of approximation ...
Scientific Research Publishing

Shmoys, D.B., Tardos, E. and Aardal, K. (1998) Approximation Algorithms for Facility Location Problems (Extended Abstract). Proceedings of the 29th Annual ACM Symposium on ...

ABSTRACT: Facility location problems are concerned with the location of one or more facilities in a way that optimizes a certain objective such as minimizing transportation cost, providing equitable ...