We introduce a novel approach to solving dynamic programming problems, such as those in many economic models, on a quantum annealer, a specialized device that performs combinatorial optimization ...

This course covers reinforcement learning aka dynamic programming, which is a modeling principle capturing dynamic environments and stochastic nature of events. The main goal is to learn dynamic ...

An error correction model is derived from a stochastic dynamic programming problem incorporating rational expectations. A parametric restriction is derived that ...

Some possible reasons for these results are explored. In cases where the hypothesis holds, a dynamic programming approach to the sequential decision problem may be used to provide optimal decision ...

After analyzing the DeepSeek-R1 architecture, unsloth performed 'dynamic quantization,' which quantizes each part of the model at a different compression rate.