class LBFGSB 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

Linear Supertypes
FirstOrderMinimizer[DenseVector[Double], DiffFunction[DenseVector[Double]]], SerializableLogging, Serializable, Minimizer[DenseVector[Double], DiffFunction[DenseVector[Double]]], AnyRef, Any
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Inherited
  1. LBFGSB
  2. FirstOrderMinimizer
  3. SerializableLogging
  4. Serializable
  5. Minimizer
  6. AnyRef
  7. Any
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Visibility
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  2. Protected

Instance Constructors

  1. new LBFGSB(lowerBounds: DenseVector[Double], upperBounds: DenseVector[Double], maxIter: Int = 100, m: Int = 5, tolerance: Double = 1E-8, maxZoomIter: Int = 64, maxLineSearchIter: Int = 64)

Type Members

  1. case class History(theta: Double, W: DenseMatrix[Double], M: DenseMatrix[Double], yHistory: DenseMatrix[Double], sHistory: DenseMatrix[Double]) extends Product with Serializable

    W

    [Yk theta * Sk]

  2. type State = FirstOrderMinimizer.State[DenseVector[Double], Info, History]
    Definition Classes
    FirstOrderMinimizer

Value Members

  1. final def !=(arg0: Any): Boolean
    Definition Classes
    AnyRef → Any
  2. final def ##: Int
    Definition Classes
    AnyRef → Any
  3. final def ==(arg0: Any): Boolean
    Definition Classes
    AnyRef → Any
  4. val EPS: Double
    Attributes
    protected
  5. def adjust(newX: DenseVector[Double], newGrad: DenseVector[Double], newVal: Double): (Double, DenseVector[Double])
    Attributes
    protected
    Definition Classes
    FirstOrderMinimizer
  6. def adjustFunction(f: DiffFunction[DenseVector[Double]]): DiffFunction[DenseVector[Double]]
    Attributes
    protected
    Definition Classes
    FirstOrderMinimizer
  7. def adjustWithinBound(point: DenseVector[Double]): Unit
  8. final def asInstanceOf[T0]: T0
    Definition Classes
    Any
  9. def calculateObjective(f: DiffFunction[DenseVector[Double]], x: DenseVector[Double], history: History): (Double, DenseVector[Double])
    Attributes
    protected
    Definition Classes
    FirstOrderMinimizer
  10. def chooseDescentDirection(state: State, f: DiffFunction[DenseVector[Double]]): DenseVector[Double]
    Attributes
    protected
    Definition Classes
    LBFGSB → FirstOrderMinimizer
  11. def clone(): AnyRef
    Attributes
    protected[lang]
    Definition Classes
    AnyRef
    Annotations
    @throws(classOf[java.lang.CloneNotSupportedException]) @native() @IntrinsicCandidate()
  12. val convergenceCheck: ConvergenceCheck[DenseVector[Double]]
    Definition Classes
    FirstOrderMinimizer
  13. def determineStepSize(state: State, f: DiffFunction[DenseVector[Double]], direction: DenseVector[Double]): Double
    Attributes
    protected
    Definition Classes
    LBFGSB → FirstOrderMinimizer
  14. final def eq(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  15. def equals(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef → Any
  16. def findAlpha(xCauchy: DenseVector[Double], du: Vector[Double], freeVarIndex: Array[Int]): Double

    xCauchy

    generalize cauchy point

    du

    gradient directiong

    returns

    starAlpha = max{a : a <= 1 and l_i-xc_i <= a*d_i <= u_i-xc_i}

    Attributes
    protected
  17. final def getClass(): Class[_ <: AnyRef]
    Definition Classes
    AnyRef → Any
    Annotations
    @native() @IntrinsicCandidate()
  18. def getGeneralizedCauchyPoint(history: History, x: DenseVector[Double], g: DenseVector[Double]): (DenseVector[Double], DenseVector[Double])
    Attributes
    protected
  19. def hashCode(): Int
    Definition Classes
    AnyRef → Any
    Annotations
    @native() @IntrinsicCandidate()
  20. def infiniteIterations(f: DiffFunction[DenseVector[Double]], state: State): Iterator[State]
    Definition Classes
    FirstOrderMinimizer
  21. def initialHistory(f: DiffFunction[DenseVector[Double]], init: DenseVector[Double]): History
    Attributes
    protected
    Definition Classes
    LBFGSB → FirstOrderMinimizer
  22. def initialState(f: DiffFunction[DenseVector[Double]], init: DenseVector[Double]): State
    Attributes
    protected
    Definition Classes
    FirstOrderMinimizer
  23. final def isInstanceOf[T0]: Boolean
    Definition Classes
    Any
  24. def iterations(f: DiffFunction[DenseVector[Double]], init: DenseVector[Double]): Iterator[State]
    Definition Classes
    FirstOrderMinimizer
  25. def logger: LazyLogger
    Attributes
    protected
    Definition Classes
    SerializableLogging
  26. def minimize(f: DiffFunction[DenseVector[Double]], init: DenseVector[Double]): DenseVector[Double]
    Definition Classes
    FirstOrderMinimizer → Minimizer
  27. def minimizeAndReturnState(f: DiffFunction[DenseVector[Double]], init: DenseVector[Double]): State
    Definition Classes
    FirstOrderMinimizer
  28. final def ne(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  29. final def notify(): Unit
    Definition Classes
    AnyRef
    Annotations
    @native() @IntrinsicCandidate()
  30. final def notifyAll(): Unit
    Definition Classes
    AnyRef
    Annotations
    @native() @IntrinsicCandidate()
  31. def subspaceMinimization(history: History, xCauchy: DenseVector[Double], x: DenseVector[Double], c: DenseVector[Double], g: DenseVector[Double]): DenseVector[Double]
    Attributes
    protected
  32. final def synchronized[T0](arg0: => T0): T0
    Definition Classes
    AnyRef
  33. def takeStep(state: State, dir: DenseVector[Double], stepSize: Double): DenseVector[Double]
    Attributes
    protected
    Definition Classes
    LBFGSB → FirstOrderMinimizer
  34. def toString(): String
    Definition Classes
    AnyRef → Any
  35. def updateHistory(newX: DenseVector[Double], newGrad: DenseVector[Double], newVal: Double, f: DiffFunction[DenseVector[Double]], oldState: State): History
    Attributes
    protected
    Definition Classes
    LBFGSB → FirstOrderMinimizer
  36. def updateSkYkHessianApproxMat(history: History, newS: DenseVector[Double], newY: DenseVector[Double]): History
    Attributes
    protected
  37. final def wait(arg0: Long, arg1: Int): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws(classOf[java.lang.InterruptedException])
  38. final def wait(arg0: Long): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws(classOf[java.lang.InterruptedException]) @native()
  39. final def wait(): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws(classOf[java.lang.InterruptedException])

Deprecated Value Members

  1. def finalize(): Unit
    Attributes
    protected[lang]
    Definition Classes
    AnyRef
    Annotations
    @throws(classOf[java.lang.Throwable]) @Deprecated
    Deprecated

Inherited from FirstOrderMinimizer[DenseVector[Double], DiffFunction[DenseVector[Double]]]

Inherited from SerializableLogging

Inherited from Serializable

Inherited from Minimizer[DenseVector[Double], DiffFunction[DenseVector[Double]]]

Inherited from AnyRef

Inherited from Any

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