breeze.optimize

ProjectedQuasiNewton

class ProjectedQuasiNewton extends FirstOrderMinimizer[DenseVector[Double], DiffFunction[DenseVector[Double]]] with Projecting[DenseVector[Double]] with SerializableLogging

Linear Supertypes
Projecting[DenseVector[Double]], FirstOrderMinimizer[DenseVector[Double], DiffFunction[DenseVector[Double]]], SerializableLogging, Serializable, Serializable, Minimizer[DenseVector[Double], DiffFunction[DenseVector[Double]]], AnyRef, Any
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Inherited
  1. ProjectedQuasiNewton
  2. Projecting
  3. FirstOrderMinimizer
  4. SerializableLogging
  5. Serializable
  6. Serializable
  7. Minimizer
  8. AnyRef
  9. Any
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  1. Public
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Instance Constructors

  1. new ProjectedQuasiNewton(tolerance: Double = 1.0E-6, m: Int = 10, initFeas: Boolean = false, testOpt: Boolean = true, maxIter: Int = -1, maxSrchIt: Int = 50, gamma: Double = 1.0E-4, projection: (DenseVector[Double]) ⇒ DenseVector[Double] = ...)(implicit space: MutableInnerProductModule[DenseVector[Double], Double])

Type Members

  1. type BDV = DenseVector[Double]

  2. type History = CompactHessian

    Any history the derived minimization function needs to do its updates.

    Any history the derived minimization function needs to do its updates. typically an approximation to the second derivative/hessian matrix.

    Definition Classes
    ProjectedQuasiNewton → FirstOrderMinimizer

  3. case class State(x: T, value: Double, grad: T, adjustedValue: Double, adjustedGradient: T, iter: Int, initialAdjVal: Double, history: History, fVals: IndexedSeq[Double] = ..., numImprovementFailures: Int = 0, searchFailed: Boolean = false) extends Product with Serializable

    Tracks the information about the optimizer, including the current point, its value, gradient, and then any history.

Value Members

  1. final def !=(arg0: AnyRef): Boolean

    Definition Classes
    AnyRef

  2. final def !=(arg0: Any): Boolean

    Definition Classes
    Any

  3. final def ##(): Int

    Definition Classes
    AnyRef → Any

  4. final def ==(arg0: AnyRef): Boolean

    Definition Classes
    AnyRef

  5. final def ==(arg0: Any): Boolean

    Definition Classes
    Any

  6. def adjust(newX: DenseVector[Double], newGrad: DenseVector[Double], newVal: Double): (Double, DenseVector[Double])

    Attributes
    protected
    Definition Classes
    ProjectedQuasiNewton → FirstOrderMinimizer

  7. def adjustFunction(f: DiffFunction[DenseVector[Double]]): DiffFunction[DenseVector[Double]]

    Attributes
    protected
    Definition Classes
    FirstOrderMinimizer

  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, fn: DiffFunction[DenseVector[Double]]): DenseVector[Double]

    Attributes
    protected
    Definition Classes
    ProjectedQuasiNewton → FirstOrderMinimizer

  11. def clone(): AnyRef

    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

  12. def determineStepSize(state: State, f: DiffFunction[DenseVector[Double]], dir: DenseVector[Double]): Double

    Given a direction, perform a Strong Wolfe Line Search

    Given a direction, perform a Strong Wolfe Line Search

    TO DO: Compare performance with Cubic Interpolation based line search from Mark's PQN paper

    state

    the current state

    f

    The objective

    dir

    The step direction

    returns

    stepSize

    Attributes
    protected
    Definition Classes
    ProjectedQuasiNewton → FirstOrderMinimizer

  13. final def eq(arg0: AnyRef): Boolean

    Definition Classes
    AnyRef

  14. def equals(arg0: Any): Boolean

    Definition Classes
    AnyRef → Any

  15. def finalize(): Unit

    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( classOf[java.lang.Throwable] )

  16. val gamma: Double

  17. final def getClass(): Class[_]

    Definition Classes
    AnyRef → Any

  18. def hashCode(): Int

    Definition Classes
    AnyRef → Any

  19. def infiniteIterations(f: DiffFunction[DenseVector[Double]], state: State): Iterator[State]

    Definition Classes
    FirstOrderMinimizer

  20. val initFeas: Boolean

  21. def initialHistory(f: DiffFunction[DenseVector[Double]], init: DenseVector[Double]): History

    Attributes
    protected
    Definition Classes
    ProjectedQuasiNewton → FirstOrderMinimizer

  22. def initialState(f: DiffFunction[DenseVector[Double]], init: DenseVector[Double]): State

    Attributes
    protected
    Definition Classes
    FirstOrderMinimizer

  23. val innerOptimizer: SpectralProjectedGradient[BDV]

  24. final def isInstanceOf[T0]: Boolean

    Definition Classes
    Any

  25. def iterations(f: DiffFunction[DenseVector[Double]], init: DenseVector[Double]): Iterator[State]

    Definition Classes
    FirstOrderMinimizer

  26. def logger: LazyLogger

    Attributes
    protected
    Definition Classes
    SerializableLogging

  27. val m: Int

  28. val maxSrchIt: Int

  29. val minImprovementWindow: Int

    Definition Classes
    FirstOrderMinimizer

  30. def minimize(f: DiffFunction[DenseVector[Double]], init: DenseVector[Double]): DenseVector[Double]

    Definition Classes
    FirstOrderMinimizer → Minimizer

  31. def minimizeAndReturnState(f: DiffFunction[DenseVector[Double]], init: DenseVector[Double]): State

    Definition Classes
    FirstOrderMinimizer

  32. final def ne(arg0: AnyRef): Boolean

    Definition Classes
    AnyRef

  33. final def notify(): Unit

    Definition Classes
    AnyRef

  34. final def notifyAll(): Unit

    Definition Classes
    AnyRef

  35. val numberOfImprovementFailures: Int

    Definition Classes
    FirstOrderMinimizer

  36. def projectedVector(x: DenseVector[Double], g: DenseVector[Double])(implicit vspace: Module[DenseVector[Double], Double]): DenseVector[Double]

    Definition Classes
    Projecting

  37. val projection: (DenseVector[Double]) ⇒ DenseVector[Double]

    Definition Classes
    ProjectedQuasiNewton → Projecting

  38. final def synchronized[T0](arg0: ⇒ T0): T0

    Definition Classes
    AnyRef

  39. def takeStep(state: State, dir: DenseVector[Double], stepSize: Double): DenseVector[Double]

    Attributes
    protected
    Definition Classes
    ProjectedQuasiNewton → FirstOrderMinimizer

  40. val testOpt: Boolean

  41. def toString(): String

    Definition Classes
    AnyRef → Any

  42. def updateFValWindow(oldState: State, newAdjVal: Double): IndexedSeq[Double]

    Attributes
    protected
    Definition Classes
    FirstOrderMinimizer

  43. def updateHistory(newX: DenseVector[Double], newGrad: DenseVector[Double], newVal: Double, f: DiffFunction[DenseVector[Double]], oldState: State): History

    Attributes
    protected
    Definition Classes
    ProjectedQuasiNewton → FirstOrderMinimizer

  44. final def wait(): Unit

    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

  45. final def wait(arg0: Long, arg1: Int): Unit

    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

  46. final def wait(arg0: Long): Unit

    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

Inherited from Projecting[DenseVector[Double]]

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

Inherited from SerializableLogging

Inherited from Serializable

Inherited from Serializable

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

Inherited from AnyRef

Inherited from Any

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