Results for "energy function"

Learns the score (∇ log p(x)) for generative sampling.

Matrix of first-order derivatives for vector-valued functions.

Matrix of curvature information.

Describes likelihoods of random variable outcomes.

Visualization of optimization landscape.

Choosing step size along gradient direction.

Modifying reward to accelerate learning.

A learning paradigm where an agent interacts with an environment and learns to choose actions to maximize cumulative reward.

Activation max(0, x); improves gradient flow and training speed in deep nets.

Raw model outputs before converting to probabilities; manipulated during decoding and calibration.

Estimating parameters by maximizing likelihood of observed data.

Optimization problems where any local minimum is global.

A narrow minimum often associated with poorer generalization.

Average value under a distribution.

Formal framework for sequential decision-making under uncertainty.

Minimum relative to nearby points.

Optimizing policies directly via gradient ascent on expected reward.

Optimization under equality/inequality constraints.

Converts constrained problem to unconstrained form.

Alternative formulation providing bounds.

Optimization under uncertainty.

Finding control policies minimizing cumulative cost.

Optimizes future actions using a model of dynamics.

Optimal control for linear systems with quadratic cost.

Learning policies from expert demonstrations.

Fast approximation of costly simulations.

Reusing knowledge from a source task/domain to improve learning on a target task/domain, typically via pretrained models.

Training one model on multiple tasks simultaneously to improve generalization through shared structure.

Learning where data arrives sequentially and the model updates continuously, often under changing distributions.

A continuous vector encoding of an item (word, image, user) such that semantic similarity corresponds to geometric closeness.