OpenAI's internal reasoning model outperformed all competitors, successfully solving all 12 algorithm problems with a perfect ...

The Cursor R&D team has breakthrough adopted a reinforcement learning framework, allowing the model to directly learn user behavior patterns through a policy gradient algorithm. When suggestions are ...

Probabilistic programming has emerged as a powerful paradigm that integrates uncertainty directly into computational models. By embedding probabilistic constructs into conventional programming ...

This is an advanced undergraduate course on algorithms. This course examines such topics as greedy algorithms, dynamic programming, graph algorithms, string processing, and algorithms for ...

Successive Linear Programming (SLP) algorithms solve nonlinear optimization problems via a sequence of linear programs. They have been widely used, particularly in the oil and chemical industries, ...

Algorithm design and analysis is fundamental to all areas of computer science and gives a rigorous framework for the study optimization. This course provides an introduction to algorithm design ...

Dinkelbach's algorithm [2] solving the parametric equivalent of a fractional program is investigated. It is shown that the algorithm converges superlinearly and often ...

Valdosta State University recently announced the launch of a new degree program — the Bachelor of Science in Data Science.