Results for "game theory"

A measure of a model class’s expressive capacity based on its ability to shatter datasets.

A measure of randomness or uncertainty in a probability distribution.

Measures how much information an observable random variable carries about unknown parameters.

Updating beliefs about parameters using observed evidence and prior distributions.

Estimating parameters by maximizing likelihood of observed data.

Optimization problems where any local minimum is global.

Optimization with multiple local minima/saddle points; typical in neural networks.

Neural networks can approximate any continuous function under certain conditions.

Fundamental recursive relationship defining optimal value functions.

Coordination arising without explicit programming.

Required human review for high-risk decisions.

Recovering training data from gradients.

Embedding signals to prove model ownership.

Neural networks that operate on graph-structured data by propagating information along edges.

Predicting future values from past observations.

Models time evolution via hidden states.

Distributed agents producing emergent intelligence.

Agents communicate via shared state.

Increasing performance via more data.

Describes likelihoods of random variable outcomes.

Variable whose values depend on chance.

Average value under a distribution.

Measure of spread around the mean.

Sample mean converges to expected value.

Sum of independent variables converges to normal distribution.

Eliminating variables by integrating over them.

Probability of data given parameters.

Flat high-dimensional regions slowing training.

Lowest possible loss.

Restricting updates to safe regions.