Class RobustFullModelAggregationStrategyBase<T, TInput, TOutput>

Namespace

AiDotNet.FederatedLearning.Aggregators

Assembly

AiDotNet.dll

Base class for robust aggregation strategies operating on IFullModel<T, TInput, TOutput> parameters.

public abstract class RobustFullModelAggregationStrategyBase<T, TInput, TOutput> : AggregationStrategyBase<IFullModel<T, TInput, TOutput>, T>, IAggregationStrategy<IFullModel<T, TInput, TOutput>>

Type Parameters

T

Numeric type.

TInput

Model input type.

TOutput

Model output type.

Inheritance

object

FederatedLearningComponentBase<T>

AggregationStrategyBase<IFullModel<T, TInput, TOutput>, T>

RobustFullModelAggregationStrategyBase<T, TInput, TOutput>

Implements

IAggregationStrategy<IFullModel<T, TInput, TOutput>>

Derived

BulyanFullModelAggregationStrategy<T, TInput, TOutput>

KrumFullModelAggregationStrategy<T, TInput, TOutput>

MedianFullModelAggregationStrategy<T, TInput, TOutput>

MultiKrumFullModelAggregationStrategy<T, TInput, TOutput>

RfaFullModelAggregationStrategy<T, TInput, TOutput>

TrimmedMeanFullModelAggregationStrategy<T, TInput, TOutput>

WinsorizedMeanFullModelAggregationStrategy<T, TInput, TOutput>

Inherited Members

AggregationStrategyBase<IFullModel<T, TInput, TOutput>, T>.Aggregate(Dictionary<int, IFullModel<T, TInput, TOutput>>, Dictionary<int, double>)

AggregationStrategyBase<IFullModel<T, TInput, TOutput>, T>.GetStrategyName()

AggregationStrategyBase<IFullModel<T, TInput, TOutput>, T>.GetTotalWeightOrThrow(Dictionary<int, double>, IEnumerable<int>, string)

FederatedLearningComponentBase<T>.NumOps

object.Equals(object)

object.Equals(object, object)

object.GetHashCode()

object.GetType()

object.MemberwiseClone()

object.ReferenceEquals(object, object)

object.ToString()

Methods

ComputeSquaredL2Distance(Vector<T>, Vector<T>)

protected double ComputeSquaredL2Distance(Vector<T> a, Vector<T> b)

Parameters

a Vector<T>

b Vector<T>

Returns

double

GetClientParametersOrThrow(Dictionary<int, IFullModel<T, TInput, TOutput>>, int)

protected static Dictionary<int, Vector<T>> GetClientParametersOrThrow(Dictionary<int, IFullModel<T, TInput, TOutput>> clientModels, int expectedParameterCount)

Parameters

clientModels Dictionary<int, IFullModel<T, TInput, TOutput>>

expectedParameterCount int

Returns

Dictionary<int, Vector<T>>

GetReferenceModelOrThrow(Dictionary<int, IFullModel<T, TInput, TOutput>>)

protected static (IFullModel<T, TInput, TOutput> ReferenceModel, int ParameterCount) GetReferenceModelOrThrow(Dictionary<int, IFullModel<T, TInput, TOutput>> clientModels)

Parameters

clientModels Dictionary<int, IFullModel<T, TInput, TOutput>>

Returns

(IFullModel<T, TInput, TOutput> ReferenceModel, int ParameterCount)

WeightedAverageOrUnweightedAverage(IReadOnlyList<int>, Dictionary<int, Vector<T>>, Dictionary<int, double>, bool)

protected Vector<T> WeightedAverageOrUnweightedAverage(IReadOnlyList<int> selectedClientIds, Dictionary<int, Vector<T>> clientParameters, Dictionary<int, double> clientWeights, bool useClientWeights)

Parameters

selectedClientIds IReadOnlyList<int>

clientParameters Dictionary<int, Vector<T>>

clientWeights Dictionary<int, double>

useClientWeights bool

Returns

Vector<T>