Abstract: In this paper, we investigate the problem of prescribed-time optimal control using reinforcement learning technology. Unlike finite/fixed-time control methods that only achieve stability ...

The area of approximation algorithms is aimed at giving provable guarantees on the performance of heuristics for hard problems. The course will present general techniques (such as convex ...

Dynamic Programming (DP) is a powerful technique for solving complex problems by breaking them into smaller, overlapping subproblems and avoiding redundant calculations. It’s a must-know skill for ...

The goal of the course is to improve programming and problem-solving skills of the students by facing them with difficult problems and by presenting the techniques that help their reasoning in the ...

In recent years, the prospect of real-world quantum computing has raised hopes for solving hard combinatorial optimisation problems, leading to tremendous theoretical work on developing and analysing ...

I invested 6+ hours to create this cheatsheet of 53 DSA problem-solving patterns & 265 problems of the 6 most commonly asked important data structures in interviews. (Problems are at the end) 1.

Mojo-V (pronounced “mojo-five”) is a new RISC-V extension that introduces privacy-oriented programming capabilities for RISC-V. Mojo-V implements secret computation, enabling secure, efficient, and ...

Great advances have been made in mass spectrometric data interpretation for intact glycopeptide analysis. However, accurate identification of intact glycopeptides and modified saccharide units at the ...

Yash is an aspiring computer science student who loves to build things and write about all things tech. In his free time, he likes to play Squash, read a copy of the latest Murakami, and hunt dragons ...

Uncertainties are widespread in the optimization of process systems, such as uncertainties in process technologies, prices, and customer demands. In this paper, we review the basic concepts and recent ...