Posts from this topic will be added to your daily email digest and your homepage feed. A new bill would hold social media platforms responsible for foreseeable algorithmic harms. A new bill would hold ...

Note: The CUDA version requires significant GPU memory for large problems. For a 64x64 gridworld (4096 states), approximately 1GB of GPU memory is needed. If you ...

BRUSSELS, Nov 4 (Reuters) - Meta Platforms (META.O), opens new tab on Tuesday rejected a ruling by the French rights watchdog against its algorithm after allegations of discriminatory job ...

Reinforcement learning (RL) plays a crucial role in scaling language models, enabling them to solve complex tasks such as competition-level mathematics and programming through deeper reasoning.

Surface waves have proven to be valuable instruments in subsurface investigation, finding applications in diverse fields such as hydrocarbon and mineral resource exploration. The computation of ...

ABSTRACT: This study introduces a novel simulation-based framework that integrates Agent-Based Modelling (ABM) with Reinforcement Learning (RL) to evaluate and optimize policies for mental health ...

We propose Q-Policy, a hybrid quantum-classical reinforcement learning (RL) framework that mathematically accelerates policy evaluation and optimization by exploiting quantum computing primitives.

Dr. James McCaffrey from Microsoft Research presents a complete end-to-end demonstration of computing a matrix inverse using the Newton iteration algorithm. Compared to other algorithms, Newton ...

Abstract: Though policy evaluation error profoundly affects the direction of policy optimization and the convergence property, it is usually ignored in policy ...

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 ...