Abstract: This article proposes a novel low-complexity syndrome-based linear programming (SB-LP) decoding algorithm for decoding quantum low-density parity-check codes. Under the code-capacity model, ...
MPAX is a hardware-accelerated, differentiable, batchable, and distributable solver for mathematical programming in JAX, designed to integrate with modern computational and deep learning workflows: ...
摘要: This article examines some of the properties of quasi-Fejer sequences when used in quasi-gradiental techniques as an alternative to stochastic search techniques for optimizing unconstrained ...
OpenAI and Google DeepMind demonstrated that their foundation models could outperform human coders — and win — showing that large language models (LLMs) can solve complex, previously unsolved ...
Note that the optimal solution to Gonzaga’s problem denoted by (G) is [a, 0] T with an optimal value of the objective function equal to a, a ≥ 10. From the infeasible starting point e = [1, 1] T, the ...
Abstract: In this article, the data-driven optimal control problem is addressed for discrete-time linear periodic systems with unknown system dynamics. To reduce the number of iterations required by ...
Computer science involves much more than writing code. It blends technical knowledge —like programming, algorithms and data systems — with soft skills, such as communication and problem-solving.
This project solves a toy distribution optimization problem using linear programming. The goal is to maximize the number of toys distributed to children while respecting constraints related to factory ...
This paper deals with linear programming techniques and their application in optimizing lecture rooms in an institution. This linear programming formulated based on the available secondary data ...
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