LBFGSB

class LBFGSB(lowerBounds: DenseVector[Double], upperBounds: DenseVector[Double], maxIter: Int, m: Int, tolerance: Double, maxZoomIter: Int, maxLineSearchIter: Int) extends FirstOrderMinimizer[DenseVector[Double], DiffFunction[DenseVector[Double]]] with SerializableLogging

This algorithm is refered the paper "A LIMITED MEMOR Y ALGORITHM F OR BOUND CONSTRAINED OPTIMIZA TION" written by Richard H.Byrd   Peihuang Lu   Jorge Nocedal  and Ciyou Zhu Created by fanming.chen on 2015/3/7 0007. If StrongWolfeLineSearch(maxZoomIter,maxLineSearchIter) is small, the wolfeRuleSearch.minimize may throw FirstOrderException, it should increase the two variables to appropriate value

Companion
object
trait Serializable
class Object
trait Matchable
class Any

Type members

Classlikes

case class History(theta: Double, W: DenseMatrix[Double], M: DenseMatrix[Double], yHistory: DenseMatrix[Double], sHistory: DenseMatrix[Double])
Value Params
W

[Yk theta * Sk]

Inherited types

type State = State[T, Info, History]
Inherited from
FirstOrderMinimizer

Value members

Concrete methods

def adjustWithinBound(point: DenseVector[Double]): Unit

Inherited methods

def infiniteIterations(f: DiffFunction[DenseVector[Double]], state: State): Iterator[State]
Inherited from
FirstOrderMinimizer
def iterations(f: DiffFunction[DenseVector[Double]], init: DenseVector[Double]): Iterator[State]
Inherited from
FirstOrderMinimizer
protected def logger: LazyLogger
Inherited from
SerializableLogging
def minimize(f: DiffFunction[DenseVector[Double]], init: DenseVector[Double]): DenseVector[Double]
Inherited from
FirstOrderMinimizer

Inherited fields