This new, dead simple prompt technique boosts accuracy on LLMs by up to 76% on non-reasoning tasks

Most modern LLMs are trained as "causal" language models. This means they process text strictly from left to right. When the ...
AlphaGalileo

Multi-Constraint Reinforcement Learning in Complex Robot Environments

FPMCO decomposes multi-constraint RL into KL-projection sub-problems, achieving higher reward with lower computing than second-order rivals on the ...
EurekAlert!

Deterministic streaming algorithms for non-monotone submodular maximization

Research team debuts the first deterministic streaming algorithms for non-monotone submodular maximization, delivering superior approximation ratios with minimal memory and real-time throughput on ...
IEEE

Constrained Multiobjective Evolutionary Optimization With Population Image Convolution

Abstract: Various constrained multiobjective evolutionary optimization algorithms (CMOEAs) have been proposed for constrained multiobjective optimization problems (CMOPs). However, their reproduction ...
IEEE

An Adaptive Auxiliary Phase Switching Multi-Task Collaborative Constrained Multi-Objective Optimization Algorithm

Abstract: To address the critical challenges of premature convergence, insufficient diversity, and constrained boundary search difficulties in constrained multi-objective optimization problems (CMOPs) ...
Lycoming College

Actuarial Science Learning Goals

Compute a derivative Compute an integral Establish the convergence of an infinite series, and find its sum in certain common cases Be able to solve a variety of kinds of equations, as well as ...