Implements asynchronous max-product (min-sum) inference. More...

Inheritance diagram for drwnAsyncMaxProdInference:

Public Member Functions
	drwnAsyncMaxProdInference (const drwnFactorGraph &graph)

Public Member Functions inherited from drwnMessagePassingMAPInference
	drwnMessagePassingMAPInference (const drwnFactorGraph &graph)

void	clear ()
	Clear internally cached data (e.g., computation graph)

std::pair< double, double >	inference (drwnFullAssignment &mapAssignment)
	Run inference (or resume for iterative algorithms). Algorithms may initialize from `mapAssignment` if not empty. Returns an upper and lower bound (if available) of the minimum energy. The upper bound is the same as the energy of the best solution found (i.e., same as `graph.getEnergy(mapAssignment)`).

Public Member Functions inherited from drwnMAPInference
	drwnMAPInference (const drwnFactorGraph &graph)

	drwnMAPInference (const drwnMAPInference &inf)

Protected Member Functions
void	buildComputationGraph ()

void	decodeBeliefs (drwnFullAssignment &mapAssignment)

Protected Member Functions inherited from drwnMessagePassingMAPInference
virtual void	initializeMessages ()

Additional Inherited Members
Static Public Attributes inherited from drwnMessagePassingMAPInference
static unsigned	MAX_ITERATIONS = 1000
	maximum number of iterations

static double	DAMPING_FACTOR = 0.0
	damping factor for updating messages

Protected Attributes inherited from drwnMessagePassingMAPInference
std::vector< drwnTableFactor * >	_forwardMessages

std::vector< drwnTableFactor * >	_backwardMessages

std::vector< drwnTableFactor * >	_oldForwardMessages

std::vector< drwnTableFactor * >	_oldBackwardMessages

std::vector< drwnTableFactor * >	_intermediateFactors

std::vector < drwnFactorOperation * >	_computations

std::vector < drwnTableFactorStorage * >	_sharedStorage

Protected Attributes inherited from drwnMAPInference
const drwnFactorGraph &	_graph
	reference to initial clique potentials

Detailed Description

Implements asynchronous max-product (min-sum) inference.

Note: Since the factor graph is expected to be in energy form (i.e., negative log-probability), this algorithm is equivalent to min-sum.

Member Function Documentation

void drwnAsyncMaxProdInference::decodeBeliefs ( drwnFullAssignment & mapAssignment )

protectedvirtual

The documentation for this class was generated from the following files: