The technique of randomizing an algorithm to improve its efficiency was first introduced in 1976 independently by Rabin, and Solovay and Strassen. Since then, this idea has been used to solve a myriad of comput
It is still not convincing from the general discussion in the previous subsection that quantum parallelism and interference can actually help us to solve some interesting computational problems. However, the power of combining quantum parallelism and interference can be clearly seen in the Deutsch-Jozsa...
The study, published in Nature Machine Intelligence, shows that DeepCubeA, their deep reinforcement learning algorithm, was able to solve 100 percent of all test configuraitons, finding the shortest path to the goal 60.3 percent of the time. "The solution to the Rubik's Cube involves more sy...
tensor-product B-spline — Simple and runs well on a GPU — Spline space size controls blurring versus detail 100x100x100 200x200x200 — A quasi-interpolant builds the spline Contribution equals basis at position — Scatter contributions using atomic adds — No need to solve a linear ...
To solve this problem, LightGBM42, as an efficient and scalable implementation of GBDT, significantly improves the training speed and maintains high accuracy by adopting a strategy called “leaf-by-leaf growth”. This strategy avoids the computational complexity of XGBoost in the tree building ...
10061: How to solve the cryptarithm? 10062: Tell me the frequencies! 10066: The Twin Towers 10067: Playing with Wheels 10070: Leap Year or Not Leap Year and ... 10071: Back to High School Physics 10074: Take the Land 10077: The Stern-Brocot Number System 10079: Pizza Cutting 10082: WE...
Zhang et al.5 developed a Q-learning based evolutionary algorithm to solve the DFJSP. For the DFJSP with order cancellation, an effective reformative memetic algorithm is designed6. For the dynamic DFJSP with job arrivals, Huang et al.7 proposed deep reinforcement learning method. Most ...
enhanced the pelican optimization algorithm by modifying three movement strategies and a predefined knowledge sharing factor to solve load scheduling problems, thereby increasing the algorithm's solution precision and efficiency35. Pan et al. developed an improved artificial bee colony algorithm based...
In this study, a non-uniform cellular automata framework was proposed to solve this problem. This proposed scheme included confusion and diffusion steps. In the confusion step, the positions of the original image pixels were replaced by chaos mapping. The key image was created using non-uniform ...
In a modern mathematics view, the old Babylonian algorithm can be easily extended to solve a cube root: 𝑥3=𝑎.x3=a. (6) Similar to Equation (6), we have 𝑥𝑛+1=𝛽𝑥𝑛+(1−𝛽)𝑎𝑥2𝑛.xn+1=βxn+(1−β)axn2. (7) We recommend β = 2/3 for the ...