See: Description
Interface  Description 

DiffFloatFunction 
An interface for oncedifferentiable doublevalued functions over
double arrays.

DiffFunction 
An interface for oncedifferentiable doublevalued functions over
double arrays.

Evaluator  
FloatFunction 
An interface for doublevalued functions over double arrays.

Function 
An interface for doublevalued functions over double arrays.

HasEvaluators 
Indicates that an minimizer supports evaluation periodically

HasFeatureGrouping 
Indicates that an minimizer supports grouping features for glasso or aelasso

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.

HasRegularizerParamRange 
Indicates that a Function should only be regularized on a subset
of its parameters.

LineSearcher 
The interface for one variable function minimizers.

Minimizer<T extends Function> 
The interface for unconstrained function minimizers.

SparseMinimizer<K,T extends SparseOnlineFunction<K>> 
The interface for unconstrained function minimizers with sparse parameters
like Minimizer, except with sparse parameters

SparseOnlineFunction<K> 
An interface for functions over sparse parameters.

StochasticMinimizer.PropertySetter<T1> 
Class  Description 

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 
Conjugategradient 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.

InefficientSGDMinimizer<T extends Function> 
Stochastic Gradient Descent Minimizer.

MemoryEvaluator 
Evaluate current memory usage

QNMinimizer 
An implementation of LBFGS for Quasi Newton unconstrained minimization.

ResultStoringFloatMonitor  
ResultStoringMonitor  
ScaledSGDMinimizer<Q extends AbstractStochasticCachingDiffFunction> 
Stochastic Gradient Descent To Quasi Newton Minimizer.

ScaledSGDMinimizer.Weights  
SGDMinimizer<T extends Function> 
In place 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.

SGDWithAdaGradAndFOBOS<T extends DiffFunction> 
Stochastic Gradient Descent With AdaGrad and FOBOS in batch mode.

SMDMinimizer<T extends Function> 
Stochastic Meta Descent Minimizer based on Accelerated training of conditional random fields with stochastic gradient methods S. 
SparseAdaGradMinimizer<K,F extends SparseOnlineFunction<K>> 
AdaGrad optimizer that works online, and use sparse gradients, need a
function that takes a Counter<K> as argument and returns a
Counter<K> as gradient

SQNMinimizer<T extends Function> 
Online LimitedMemory QuasiNewton BFGS implementation based on the algorithms in
Nocedal, Jorge, and Stephen J. 
StochasticDiffFunctionTester  
StochasticMinimizer<T extends Function> 
Stochastic Gradient Descent Minimizer.

Enum  Description 

AbstractStochasticCachingDiffFunction.SamplingMethod  
SGDWithAdaGradAndFOBOS.Prior  
StochasticCalculateMethods 
This enumeratin was created to organize the selection of different methods for stochastic
calculations.

Exception  Description 

QNMinimizer.SurpriseConvergence 