Package edu.stanford.nlp.optimization

Interface Summary

DiffFloatFunction	An interface for once-differentiable double-valued functions over double arrays.
DiffFunction	An interface for once-differentiable double-valued functions over double arrays.
Evaluator
FloatFunction	An interface for double-valued functions over double arrays.
Function	An interface for double-valued functions over double arrays.
HasEvaluators	Indicates that an minimizer supports evaluation periodically
HasFloatInitial	Indicates that a function has a method for supplying an intitial value.
HasInitial	Indicates that a function has a method for supplying an intitial value.
LineSearcher	The interface for one variable function minimizers.
Minimizer<T extends Function>	The interface for unconstrained function minimizers.
StochasticMinimizer.PropertySetter<T1>

Class Summary

AbstractCachingDiffFloatFunction
AbstractCachingDiffFunction	A differentiable function that caches the last evaluation of its value and derivative.
AbstractStochasticCachingDiffFunction
AbstractStochasticCachingDiffUpdateFunction	Function for stochastic calculations that does update in place (instead of maintaining and returning the derivative).
CGMinimizer	Conjugate-gradient implementation based on the code in Numerical Recipes in C.
CmdEvaluator	Runs a cmdline to evaluate a dataset (assumes cmd takes input from stdin)
GoldenSectionLineSearch	A class to do golden section line search.
HybridMinimizer	Hybrid Minimizer is set up as a combination of two minimizers.
MemoryEvaluator	Evaluate current memory usage
QNMinimizer	An implementation of L-BFGS for Quasi Newton unconstrained minimization.
QNMinimizer.SurpriseConvergence
ResultStoringFloatMonitor
ResultStoringMonitor
ScaledSGDMinimizer	Stochastic Gradient Descent To Quasi Newton Minimizer An experimental minimizer which takes a stochastic function (one implementing AbstractStochasticCachingDiffFunction) and executes SGD for the first couple passes, During the final iterations a series of approximate hessian vector products are built up...
ScaledSGDMinimizer.weight
SGDMinimizer<T extends Function>	Stochastic Gradient Descent Minimizer.
SGDToQNMinimizer	Stochastic Gradient Descent To Quasi Newton Minimizer An experimental minimizer which takes a stochastic function (one implementing AbstractStochasticCachingDiffFunction) and executes SGD for the first couple passes.
SMDMinimizer<T extends Function>	Stochastic Meta Descent Minimizer based on
SQNMinimizer<T extends Function>	Online Limited-Memory Quasi-Newton BFGS implementation based on the algorithms in
StochasticDiffFunctionTester
StochasticInPlaceMinimizer<T extends Function>	In place Stochastic Gradient Descent Minimizer.
StochasticMinimizer<T extends Function>	Stochastic Gradient Descent Minimizer.

Enum Summary

AbstractStochasticCachingDiffFunction.SamplingMethod
QNMinimizer.eLineSearch
QNMinimizer.eScaling
QNMinimizer.eState
StochasticCalculateMethods	This enumeratin was created to organize the selection of different methods for stochastic calculations.