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📚TheoryIntermediate

Metric Learning

Metric learning is about automatically learning a distance function so that similar items are close and dissimilar items are far in a feature space.

#metric learning#mahalanobis distance#contrastive loss+12
∑MathIntermediate

Maximum Likelihood Estimation (MLE)

Maximum Likelihood Estimation (MLE) chooses parameters that make the observed data most probable under a chosen model.

#maximum likelihood
Advanced
Filtering by:
#fisher information
#log-likelihood
#bernoulli mle
+12
∑MathIntermediate

Exponential Family Distributions

Exponential family distributions express many common probability models in a single template p(x|η) = h(x) exp(η^T T(x) − A(η)).

#exponential family#natural parameter#sufficient statistics+12