class ProjectedQuasiNewton extends FirstOrderMinimizer[DenseVector[Double], DiffFunction[DenseVector[Double]]] with Projecting[DenseVector[Double]] with SerializableLogging
Linear Supertypes
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Inherited
- ProjectedQuasiNewton
- Projecting
- FirstOrderMinimizer
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- Serializable
- Minimizer
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Instance Constructors
- new ProjectedQuasiNewton(tolerance: Double = 1e-6, m: Int = 10, initFeas: Boolean = false, testOpt: Boolean = true, maxIter: Int = -1, maxSrchIt: Int = 50, gamma: Double = 1e-4, projection: (DenseVector[Double]) => DenseVector[Double] = identity, relativeTolerance: Boolean = true)(implicit space: MutableInnerProductModule[DenseVector[Double], Double])
- new ProjectedQuasiNewton(convergenceCheck: ConvergenceCheck[DenseVector[Double]], innerOptimizer: SpectralProjectedGradient[DenseVector[Double]], m: Int, initFeas: Boolean, testOpt: Boolean, maxSrchIt: Int, gamma: Double, projection: (DenseVector[Double]) => DenseVector[Double])(implicit space: MutableInnerProductModule[DenseVector[Double], Double])
Type Members
- type BDV = DenseVector[Double]
- 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
- type State = FirstOrderMinimizer.State[DenseVector[Double], Info, History]
- Definition Classes
- FirstOrderMinimizer
Value Members
- final def !=(arg0: Any): Boolean
- Definition Classes
- AnyRef → Any
- final def ##: Int
- Definition Classes
- AnyRef → Any
- final def ==(arg0: Any): Boolean
- Definition Classes
- AnyRef → Any
- def adjust(newX: DenseVector[Double], newGrad: DenseVector[Double], newVal: Double): (Double, DenseVector[Double])
- Attributes
- protected
- Definition Classes
- ProjectedQuasiNewton → FirstOrderMinimizer
- def adjustFunction(f: DiffFunction[DenseVector[Double]]): DiffFunction[DenseVector[Double]]
- Attributes
- protected
- Definition Classes
- FirstOrderMinimizer
- final def asInstanceOf[T0]: T0
- Definition Classes
- Any
- def calculateObjective(f: DiffFunction[DenseVector[Double]], x: DenseVector[Double], history: History): (Double, DenseVector[Double])
- Attributes
- protected
- Definition Classes
- FirstOrderMinimizer
- def chooseDescentDirection(state: State, fn: DiffFunction[DenseVector[Double]]): DenseVector[Double]
- Attributes
- protected
- Definition Classes
- ProjectedQuasiNewton → FirstOrderMinimizer
- def clone(): AnyRef
- Attributes
- protected[lang]
- Definition Classes
- AnyRef
- Annotations
- @throws(classOf[java.lang.CloneNotSupportedException]) @native() @IntrinsicCandidate()
- val convergenceCheck: ConvergenceCheck[DenseVector[Double]]
- Definition Classes
- FirstOrderMinimizer
- 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
- final def eq(arg0: AnyRef): Boolean
- Definition Classes
- AnyRef
- def equals(arg0: AnyRef): Boolean
- Definition Classes
- AnyRef → Any
- val gamma: Double
- final def getClass(): Class[_ <: AnyRef]
- Definition Classes
- AnyRef → Any
- Annotations
- @native() @IntrinsicCandidate()
- def hashCode(): Int
- Definition Classes
- AnyRef → Any
- Annotations
- @native() @IntrinsicCandidate()
- def infiniteIterations(f: DiffFunction[DenseVector[Double]], state: State): Iterator[State]
- Definition Classes
- FirstOrderMinimizer
- val initFeas: Boolean
- def initialHistory(f: DiffFunction[DenseVector[Double]], init: DenseVector[Double]): History
- Attributes
- protected
- Definition Classes
- ProjectedQuasiNewton → FirstOrderMinimizer
- def initialState(f: DiffFunction[DenseVector[Double]], init: DenseVector[Double]): State
- Attributes
- protected
- Definition Classes
- FirstOrderMinimizer
- val innerOptimizer: SpectralProjectedGradient[DenseVector[Double]]
- final def isInstanceOf[T0]: Boolean
- Definition Classes
- Any
- def iterations(f: DiffFunction[DenseVector[Double]], init: DenseVector[Double]): Iterator[State]
- Definition Classes
- FirstOrderMinimizer
- def logger: LazyLogger
- Attributes
- protected
- Definition Classes
- SerializableLogging
- val m: Int
- val maxSrchIt: Int
- def minimize(f: DiffFunction[DenseVector[Double]], init: DenseVector[Double]): DenseVector[Double]
- Definition Classes
- FirstOrderMinimizer → Minimizer
- def minimizeAndReturnState(f: DiffFunction[DenseVector[Double]], init: DenseVector[Double]): State
- Definition Classes
- FirstOrderMinimizer
- final def ne(arg0: AnyRef): Boolean
- Definition Classes
- AnyRef
- final def notify(): Unit
- Definition Classes
- AnyRef
- Annotations
- @native() @IntrinsicCandidate()
- final def notifyAll(): Unit
- Definition Classes
- AnyRef
- Annotations
- @native() @IntrinsicCandidate()
- def projectedVector(x: DenseVector[Double], g: DenseVector[Double])(implicit vspace: Module[DenseVector[Double], Double]): DenseVector[Double]
- Definition Classes
- Projecting
- val projection: (DenseVector[Double]) => DenseVector[Double]
- Definition Classes
- ProjectedQuasiNewton → Projecting
- final def synchronized[T0](arg0: => T0): T0
- Definition Classes
- AnyRef
- def takeStep(state: State, dir: DenseVector[Double], stepSize: Double): DenseVector[Double]
- Attributes
- protected
- Definition Classes
- ProjectedQuasiNewton → FirstOrderMinimizer
- val testOpt: Boolean
- def toString(): String
- Definition Classes
- AnyRef → Any
- def updateHistory(newX: DenseVector[Double], newGrad: DenseVector[Double], newVal: Double, f: DiffFunction[DenseVector[Double]], oldState: State): History
- Attributes
- protected
- Definition Classes
- ProjectedQuasiNewton → FirstOrderMinimizer
- final def wait(arg0: Long, arg1: Int): Unit
- Definition Classes
- AnyRef
- Annotations
- @throws(classOf[java.lang.InterruptedException])
- final def wait(arg0: Long): Unit
- Definition Classes
- AnyRef
- Annotations
- @throws(classOf[java.lang.InterruptedException]) @native()
- final def wait(): Unit
- Definition Classes
- AnyRef
- Annotations
- @throws(classOf[java.lang.InterruptedException])