package collapsedgibbs
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abstract
class
CollapsedProbQueryGibbs
extends ProbQueryGibbs with CollapsedProbabilisticGibbs
CollapsedProbQueryGibbs only uses graph information and the list of targets to collapse some variables.
CollapsedProbQueryGibbs only uses graph information and the list of targets to collapse some variables. extend with HeuristicCollapser or RecurringCollapser to implement other features described in Gogate et. al.
 trait CollapsedProbabilisticGibbs extends BaseUnweightedSampler with ProbabilisticGibbs

trait
DeterministicCollapseStrategy
extends BaseUnweightedSampler with CollapsedProbabilisticGibbs
Experimental collapser that doesn't need to calculate marginal probabilities.
Experimental collapser that doesn't need to calculate marginal probabilities. The original paper doesn't distinguish between model variables, or use any metainformation about the variables. Since Figaro knows which variables are deterministic, we can use this as a proxy for the correlation heuristic.

trait
FactorSizeCollapseStrategy
extends BaseUnweightedSampler with CollapsedProbabilisticGibbs
This trait causes variables to collapsed until the total summed size of all of the factors collapsed thus far exceeds a threshold.

trait
HeuristicCollapseStrategy
extends BaseUnweightedSampler with CollapsedProbabilisticGibbs
HeuristicCollapsedGibbs adds the Hellingerdistancebased term to the elimination heuristic.
HeuristicCollapsedGibbs adds the Hellingerdistancebased term to the elimination heuristic. So the heuristic is now based on the marginal probabilities and pairwise marginals. These have to be estimated by some number of saved samples.

trait
RecurringCollapseStrategy
extends BaseUnweightedSampler with HeuristicCollapseStrategy
In the paper, the authors recommend updating the marginals every N samples and recollapsing every few iterations.
In the paper, the authors recommend updating the marginals every N samples and recollapsing every few iterations. In practice, this is pretty slow. This trait will keep a running tally of samples of each of the used variables and recollapse the factor graph (starting from the initial graph) periodically.
Value Members
 object CollapsedGibbs