The leading approach to the simplex method, a widely used technique for balancing complex logistical constraints, can’t get any better. In 1939, upon arriving late to his statistics course at the ...
Introduction: In unsupervised learning, data clustering is essential. However, many current algorithms have issues like early convergence, inadequate local search capabilities, and trouble processing ...
One of the most frustrating things about using a large language model is dealing with its tendency to confabulate information, hallucinating answers that are not supported by its training data. From a ...
Mr. Ferguson is a documentary filmmaker. As you scroll through the internet, you’ve probably noticed the same problem Kirby Ferguson has: “Everything looks the same, sounds the same, is the same.” In ...
Abstract: In this work, we extend the simplex algorithm of linear programming for finding a local minimum of a concave quadratic function subject to box constraints. In order to test the performance ...
ABSTRACT: The outbreak of COVID-19 in 2019 resulted in numerous infections and deaths. In order to better study the transmission of COVID-19, this article adopts an improved fractional-order SIR model ...
In order to compile it, just enter the src folder and execute make. The only dependency is g++. In order to execute it, no parameters are required. The seed for the random number generator is taken ...
Initially designed for continuous control tasks, Proximal Policy Optimization (PPO) has become widely used in reinforcement learning (RL) applications, including fine-tuning generative models. However ...
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