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Mm algorithmMinimax theoremApproximation theoryMaximum likelihood estimationMinimum mean square errorEllipsoid methodLinear programmingGradient descentMirror descentLeast absolute deviationsGlobal optimizationEmpirical risk minimizationLagrange multiplierMinimax estimatorOdds algorithmTernary searchMaximum theoremLocal optimumLogsumexpBayes estimatorIterative methodOptimization problemPerturbation theoryLow-rank approximationOptimizationLinear approximationInverse quadratic interpolationRecursive least squares filterCoordinate descentGolden-section searchLeast-squares adjustmentMean shiftBiconjugate gradient methodSemidefinite programmingTrajectory optimizationAdjoint state methodCompact convergenceLagrangian relaxationRegularized least squaresRoot-finding algorithmsMinimaxInverse iterationSequential minimal optimizationCombinatorial optimizationTruncated newton methodLaplace's methodConjugate gradient methodApproximation algorithmNon-negative least squaresDesign optimizationAlgorithmProbability mass functionMilstein methodLine searchLimitConvex analysisRemez algorithmOptimal controlFinite volume methodMidpoint methodLinearizationEuler methodInfinite element methodArg maxLeast mean squares filterBacktracking line searchConvex conjugateDelta methodSum-of-squares optimizationMultiple-scale analysisBasic feasible solutionLimit comparison testCutting-plane methodLinear least squaresChebyshev distanceConstrained optimizationExtended finite element methodQuantum phase estimation algorithmGeneralized assignment problemLeast-upper-bound propertyIndex calculus algorithmSubgradient methodLearning rateTotal derivativeMatrix differential equationQ-gaussian distributionQuadratic programmingFloating-point error mitigationMaximum principleLinear differential equationGradient methodHyperloglogConvex optimizationFloor and ceiling functionsNonlinear programmingTheory of computationEstimation lemmaStein's methodPowell's methodLeast fixed point