Hybrid Variable Sets
The combination of different types of input features, such as fundamental and technical variables, to improve predictive modeling.
The combination of different types of input features, such as fundamental and technical variables, to improve predictive modeling.
A method that provides structured support to models during reasoning tasks to enhance their performance.
The process of teaching robots to perform tasks by learning from human demonstrations.
Policies that utilize 3D point data to inform the manipulation actions of a robot’s multi-fingered hands.
A customized reinforcement learning strategy tailored for the TwiG framework.
A decoding strategy that generates multiple potential outputs in parallel to improve efficiency and reduce latency in response generation.
A technique that generates outputs without any prior examples or training on specific tasks.
A family of black-box optimization methods that utilize evolutionary algorithms to optimize complex functions, particularly useful for non-differentiable or noisy objectives.
A method that approximates high-dimensional matrices using low-rank representations to reduce computational and memory costs.
The process of testing a trading strategy using historical data to evaluate its effectiveness and profitability.