EVOLVE, an agentic framework that autonomously optimizes AI training data, model architectures, and learning algorithms — ...

Battersea Arts Centre will present BLOOM 2026, featuring five productions spanning absurdist theatre, immersive performance, ...

Abstract: The Kleinman iteration is a policy iteration method for solving Riccati equations and forms the basis of many reinforcement learning (RL) algorithms. However, its direct application to ...

ABSTRACT: To overcome the problem of calculation errors in the Born approximation when the forward accumulation effect is strong in VTI media, this article combines the De Wolf approximation method ...

Abstract: We generalize the generalized Arimoto-Blahut algorithm to a general function defined over Bregman-divergence system. In existing methods, when linear constraints are imposed, each iteration ...

Dozens of machine learning algorithms require computing the inverse of a matrix. Computing a matrix inverse is conceptually easy, but implementation is one of the most difficult tasks in numerical ...

A modernized, interactive demo of value iteration in a 10×10 grid world, adapted from David Poole’s original demo. Visualizes how the value function and optimal policy evolve with each iteration.

Large language models have made remarkable strides in natural language processing, yet they still encounter difficulties when addressing complex planning and reasoning tasks. Traditional methods often ...