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Mathematical relation assigning a probability event to a cost
optimization and decision theory, a loss function or cost function (sometimes also called an error function) is a function that maps an event or values of
Loss_function
Loss function used in robust regression
statistics, the Huber loss is a loss function used in robust regression, that is less sensitive to outliers in data than the squared error loss. A variant for
Huber_loss
Concept in machine learning
learning and mathematical optimization, loss functions for classification are computationally feasible loss functions representing the price paid for inaccuracy
Loss functions for classification
Loss_functions_for_classification
Optimization algorithm for artificial neural networks
in weight space of a feedforward neural network, with respect to a loss function. Denote: x {\displaystyle x} : input (vector of features) y {\displaystyle
Backpropagation
Alteration in the nucleotide sequence of a genome
mutations, are a form of loss-of-function mutations that completely prohibit the gene's function. The mutation leads to a complete loss of operation at the
Mutation
Function for machine learning algorithms
Triplet loss is a machine learning loss function widely used in one-shot learning, a setting where models are trained to generalize effectively from limited
Triplet_loss
Information-theoretic measure
"Logistic loss refers to the loss function commonly used to optimize a logistic regression model. It may also be referred to as logarithmic loss (which is
Cross-entropy
Technique to make a model more generalizable and transferable
regularization. This includes, for example, early stopping, using a robust loss function, and discarding outliers. Implicit regularization is essentially ubiquitous
Regularization_(mathematics)
Statistical modeling technique
\tau \right\},} where 0 < τ < 1 {\displaystyle 0<\tau <1} . Define the loss function as ρ τ ( u ) = u ( τ − I ( u < 0 ) ) = { ( τ − 1 ) u , if u < 0 , τ
Quantile_regression
Loss function in machine learning
In machine learning, the hinge loss is a loss function used for training classifiers. The hinge loss is used for "maximum-margin" classification, most
Hinge_loss
Graphical depicture of loss
The Taguchi loss function is graphical depiction of loss developed by the Japanese business statistician Genichi Taguchi to describe a phenomenon affecting
Taguchi_loss_function
Technique for the generative modeling of a continuous probability distribution
observed data. This allows us to perform variational inference. Define the loss function L ( θ ) := − E x 0 : T ∼ q [ ln p θ ( x 0 : T ) − ln q ( x 1 : T
Diffusion_model
Statistical methods to improve the quality of manufactured goods
comparisons of treatment means. However, loss functions were avoided by Ronald A. Fisher[clarification needed - loss functions weren't explicitly mentioned yet]
Taguchi_methods
Statistical property
central tendency; because a biased estimator gives a lower value of some loss function (particularly mean squared error) compared with unbiased estimators
Bias_of_an_estimator
Technique to solve partial differential equations
{\displaystyle f(t,x)} can be then learned by minimizing the following loss function L tot {\displaystyle L_{\text{tot}}} : L tot = L u + L f {\displaystyle
Physics-informed neural networks
Physics-informed_neural_networks
Gradient boosting machine learning library
in function space unlike gradient boosting that works as gradient descent in function space, a second order Taylor approximation is used in the loss function
XGBoost
Machine learning technique
other methods by allowing optimization of an arbitrary differentiable loss function. The idea of gradient boosting originated in the observation by Leo
Gradient_boosting
Topics referred to by the same term
fiber Dielectric loss, a dielectric material's inherent dissipation of electromagnetic energy Loss function, in statistics, a function representing the
Loss
Middle quantile of a data set or probability distribution
risk with respect to the absolute-deviation loss function, as observed by Laplace. Other loss functions are used in statistical theory, particularly
Median
Distance from a point to the boundary of a set
[non-primary source needed] A modified version of SDF was introduced as a loss function to minimise the error in interpenetration of pixels while rendering
Signed_distance_function
Statistical model for a binary dependent variable
surprising". Since the value of the logistic function is always strictly between zero and one, the log loss is always greater than zero and less than infinity
Logistic_regression
Machine learning technique
_{i}w(x)_{i}f_{i}(x)} . Both the experts and the weighting function are trained by minimizing some loss function, generally via gradient descent. There is much freedom
Mixture_of_experts
Process of finding the optimal set of variables for a machine learning algorithm
minimizes a predefined loss function on a given data set. The objective function takes a set of hyperparameters and returns the associated loss. Cross-validation
Hyperparameter_optimization
Mathematical decision rule
value of a loss function (i.e., the posterior expected loss). Equivalently, it maximizes the posterior expectation of a utility function. An alternative
Bayes_estimator
Measure of the error of an estimator
values and the true value. MSE is a risk function, corresponding to the expected value of the squared error loss. The fact that MSE is almost always strictly
Mean_squared_error
Computational model used in machine learning
long as the value of the loss function (its cost) continues to decline, the network is continuing to improve. The function typically produces a statistic
Neural network (machine learning)
Neural_network_(machine_learning)
Set of statistical processes for estimating the relationships among variables
regression models propose that Y i {\displaystyle Y_{i}} is a function (regression function) of X i {\displaystyle X_{i}} and β {\displaystyle \beta }
Regression_analysis
Principle in statistical learning theory
{E} [L(h(x),y)]=\int L(h(x),y)\,dP(x,y).} A loss function commonly used in theory is the 0-1 loss function: L ( y ^ , y ) = { 1 if y ^ ≠ y 0 if y ^
Empirical_risk_minimization
Use of machine learning to rank items
goal is to minimize a loss function L ( h ; x u , x v , y u , v ) {\displaystyle L(h;x_{u},x_{v},y_{u,v})} . The loss function typically reflects the
Learning_to_rank
Function related to statistics and probability theory
A likelihood function (often simply called the likelihood) measures how well a statistical model explains observed data by calculating the probability
Likelihood_function
Framework for machine learning
The most common loss function for regression is the square loss function (also known as the L2-norm). This familiar loss function is used in Ordinary
Statistical_learning_theory
Smoothed ramp function
softplus function is f ( x ) = ln ( 1 + e x ) . {\displaystyle f(x)=\ln(1+e^{x}).} It is a smooth approximation (in fact, an analytic function) to the
Softplus
Set of methods for supervised statistical learning
between the hinge loss and these other loss functions is best stated in terms of target functions - the function that minimizes expected risk for a given
Support_vector_machine
Statistical model validation technique
{\displaystyle i^{th}} candidate configuration that might be selected, then the loss function that is to be minimized can be defined as L λ i = ( 1 − γ ) Relative
Cross-validation_(statistics)
Method of machine learning
example, with other convex loss functions. Consider the setting of supervised learning with f {\displaystyle f} being a linear function to be learned: f ( x
Online_machine_learning
Method of estimating the parameters of a statistical model
linear-error loss respectively—which are more representative of typical loss functions—and for a continuous posterior distribution there is no loss function which
Maximum a posteriori estimation
Maximum_a_posteriori_estimation
Class of statistical models
response variable via a link function and by allowing the magnitude of the variance of each measurement to be a function of its predicted value. Generalized
Generalized_linear_model
Parameter controlling the machine learning process
a predefined loss function on given test data. The objective function takes a tuple of hyperparameters and returns the associated loss. Typically these
Hyperparameter (machine learning)
Hyperparameter_(machine_learning)
Measure of variation in statistics
{erf} } is the error function. The proportion that is less than or equal to a number, x, is given by the cumulative distribution function: Proportion ≤ x =
Standard_deviation
Covariance and correlation
processing, cross-correlation is a measure of similarity of two series as a function of the displacement of one relative to the other. This is also known as
Cross-correlation
Machine learning paradigm
(x_{i},\;y_{i})} . In order to measure how well a function fits the training data, a loss function L : Y × Y → R ≥ 0 {\displaystyle L:Y\times Y\to \mathbb
Supervised_learning
Adaptive boosting based classification algorithm
minimization of a convex loss function over a convex set of functions. Specifically, the loss being minimized by AdaBoost is the exponential loss ∑ i ϕ ( i , y
AdaBoost
Algorithm for modelling sequential data
based on the context. The loss function for the task is typically sum of log-perplexities for the masked-out tokens: Loss = − ∑ t ∈ masked tokens ln
Transformer_(deep_learning)
Distribution function associated with the empirical measure of a sample
an empirical distribution function (a.k.a. an empirical cumulative distribution function, eCDF) is the distribution function associated with the empirical
Empirical distribution function
Empirical_distribution_function
Process of using data analysis for predicting population data from sample data
most powerful testing) make use of loss functions, which play the role of (negative) utility functions. Loss functions need not be explicitly stated for
Statistical_inference
Measure of statistical dispersion
calculated by integrating the probability density function (which yields the cumulative distribution function—any other means of calculating the CDF will also
Interquartile_range
Study of mathematical algorithms for optimization problems
solutions. The function f is variously called an objective function, criterion function, loss function, cost function (minimization), utility function or fitness
Mathematical_optimization
Deep learning generative model to encode data representation
loss function to squeeze q ϕ ( z | x ) {\displaystyle q_{\phi }({z|x})} under p θ ( z | x ) {\displaystyle p_{\theta }(z|x)} . This divergence loss expands
Variational_autoencoder
Machine learning model training problem
weights are updated proportional to their partial derivative of the loss function. As the number of forward propagation steps in a network increases,
Vanishing_gradient_problem
Paralysis of all four limbs and torso
as the dysfunction or loss of motor and/or sensory function in the cervical area of the spinal cord. A loss of motor function can present as either weakness
Tetraplegia
Statistical modeling method
}}\end{aligned}}} As the loss function is convex, the optimum solution lies at gradient zero. The gradient of the loss function is (using Denominator layout
Linear_regression
Aspect of decision and prospect theories
behavioral economics, loss aversion is a cognitive bias in which the same situation is perceived as worse if it is framed as a loss, rather than a gain
Loss_aversion
Calculation of financial risk
understanding and mitigation of systemic risk. Systemic risk Loss function Loss function § Expected loss Potential future exposure Sandra Thompson/Voon Hoe Chen
Expected_loss
Optimality condition in optimal control theory
conditions for optimality of a control with respect to a loss function. Its solution is the value function of the optimal control problem which, once known,
Hamilton–Jacobi–Bellman equation
Hamilton–Jacobi–Bellman_equation
Conditional probability used in Bayesian statistics
| X ) {\displaystyle p(\theta |X)} . It contrasts with the likelihood function, which is the probability of the evidence given the parameters: p ( X |
Posterior_probability
Measure of linear correlation
cross-product of standardized variables Function of the angle between two standardized regression lines Function of the angle between two variable vectors
Pearson correlation coefficient
Pearson_correlation_coefficient
Fundamental theorem in probability theory and statistics
characteristic functions of a number of density functions becomes close to the characteristic function of the normal density as the number of density functions increases
Central_limit_theorem
In mathematics, a quantitative measure of the shape of a set of points
Moments of a function in mathematics are certain quantitative measures related to the shape of the function's graph. For example, if the function represents
Moment_(mathematics)
Machine learning method to transfer knowledge from a large model to a smaller one
training set or consist of new, possibly unlabeled data. A cross-entropy loss function is typically used, computed between the output of the distilled model
Knowledge_distillation
Measure for evaluating probabilistic forecasts
target variable. Scoring rules and scoring functions are often used as "cost functions" or "loss functions" of forecasting models. If a sample of forecasts
Scoring_rule
Probability distribution
instance of the hypergeometric function. For information on its inverse cumulative distribution function, see quantile function § Student's t-distribution
Student's_t-distribution
Statistical measure of variability
reciprocal of the quantile function Φ − 1 {\displaystyle \Phi ^{-1}} (also known as the inverse of the cumulative distribution function) for the standard normal
Median_absolute_deviation
Statistical measure of how far values spread from their average
random variable X {\displaystyle X} is discrete with probability mass function x 1 ↦ p 1 , x 2 ↦ p 2 , … , x n ↦ p n {\displaystyle x_{1}\mapsto p_{1}
Variance
Statistical theorem
{E} [L(\delta (X))]} where the "loss function" L {\displaystyle L} may be any convex function. If the loss function is twice-differentiable, as in the
Rao–Blackwell_theorem
Topics referred to by the same term
function In economics, the cost curve, expressing production costs in terms of the amount produced. In mathematical optimization, the loss function,
Cost_function
Type of statistics
known as the Huber loss function. Tukey's biweight (also known as bisquare) function behaves in a similar way to the squared error function at first, but for
Robust_statistics
Method of statistical inference
estimation that minimize the posterior risk (expected-posterior loss) with respect to a loss function, and these are of interest to statistical decision theory
Bayesian_inference
Measure of prediction accuracy of a forecast
section below). Mean absolute percentage error is commonly used as a loss function for regression problems and in model evaluation, because of its very
Mean absolute percentage error
Mean_absolute_percentage_error
Neural network working on two input vectors
(\cdot )} function implemented by the twin network The most common distance metric used is Euclidean distance, in case of which the loss function can be
Siamese_neural_network
Correlation of a signal with a time-shifted copy of itself, as a function of shift
Pearson correlation between values of the process at different times, as a function of the two times or of the time lag. Let { X t } {\displaystyle \left\{X_{t}\right\}}
Autocorrelation
Probability of survival beyond any specified time
certain time. The survival function is also known as the survivor function or reliability function. The term reliability function is common in engineering
Survival_function
Statistical method
median-unbiased estimators of minimum risk (with respect to an absolute loss function). Bias in the bootstrap distribution will lead to bias in the confidence
Bootstrapping_(statistics)
Nonparametric measure of rank correlation
relationship between two variables can be described using a monotonic function. The Spearman correlation between two variables is equal to the Pearson
Spearman's rank correlation coefficient
Spearman's_rank_correlation_coefficient
Partial correlation of a time series with its lagged values
In time series analysis, the partial autocorrelation function (PACF) gives the partial correlation of a stationary time series with its own lagged values
Partial autocorrelation function
Partial_autocorrelation_function
Mathematical function characterizing set membership
In mathematics, an indicator function or a characteristic function of a subset of a set is a function that maps elements of the subset to one, and all
Indicator_function
Machine learning paradigm
requiring it to reconstruct the same data as closely as possible. The loss function used during training typically penalizes the difference between the
Self-supervised_learning
Mathematical function for the probability a given outcome occurs in an experiment
often described by functions such as cumulative distribution functions, probability mass functions, or probability density functions. Which description
Probability_distribution
Optimization algorithm
machine learning and artificial intelligence for minimizing the cost or loss function. Gradient descent is generally attributed to Augustin-Louis Cauchy,
Gradient_descent
Measure of the asymmetry of random variables
} where Q is the quantile function (i.e., the inverse of the cumulative distribution function). The numerator is difference between the
Skewness
Type of kernel induced by artificial neural networks
equivalent to kernel gradient descent using the NTK as the kernel. If the loss function is mean-squared error, the final distribution over f ( x ; θ ) {\displaystyle
Neural_tangent_kernel
Numeric quantity representing the center of a collection of numbers
random variable and P ( x ) {\displaystyle P(x)} is the probability mass function. For a continuous distribution, the mean is ∫ − ∞ ∞ x f ( x ) d x {\displaystyle
Mean
Parameter estimation via sample statistics
Posterior mean, which minimizes the (posterior) risk (expected loss) for a squared-error loss function; in Bayesian estimation, the risk is defined in terms of
Point_estimation
Generalization of the one-dimensional normal distribution to higher dimensions
scalar-valued function of a normal vector, its probability density function, cumulative distribution function, and inverse cumulative distribution function can
Multivariate normal distribution
Multivariate_normal_distribution
Subset of evolutionary computation
individuals in a population, and the fitness function determines the quality of the solutions (see also loss function). Evolution of the population then takes
Evolutionary_algorithm
Diagnostic plot of binary classifier ability
The ROC can also be thought of as a plot of the statistical power as a function of the Type I Error of the decision rule (when the performance is calculated
Receiver operating characteristic
Receiver_operating_characteristic
Estimator for quality of a statistical model
of fit (as assessed by the likelihood function), but it also includes a penalty that is an increasing function of the number of estimated parameters.
Akaike_information_criterion
Smooth approximation of one-hot arg max
The softmax function, also known as softargmax or normalized exponential function, converts a tuple of K real numbers into a probability distribution
Softmax_function
Method of estimating the parameters of a statistical model, given observations
{\mathbb {P} } (x)}},} and if we further assume the zero-or-one loss function, which is a same loss for all errors, the Bayes Decision rule can be reformulated
Maximum_likelihood_estimation
Parametric model in survival analysis
censored observations one needs the survival function, which is the complement of the cumulative distribution function, i.e. one needs to be able to evaluate
Accelerated failure time model
Accelerated_failure_time_model
Tuning parameter (hyperparameter) in optimization
the step size at each iteration while moving toward a minimum of a loss function. Since it influences to what extent newly acquired information overrides
Learning_rate
Graphical representation of the distribution of numerical data
and often for density estimation: estimating the probability density function of the underlying variable. The total area of a histogram used for probability
Histogram
Statistics term
statistic has a smaller expected loss for any convex loss function; in many practical applications with the squared loss-function, it has a smaller mean squared
Completeness_(statistics)
Statistical distribution for dependence between random variables
theory and statistics, a copula is a multivariate cumulative distribution function for which the marginal probability distribution of each variable is uniform
Copula_(statistics)
Type of neural network output and associated scoring function
company Baidu used a bidirectional RNN (not an LSTM) trained on the CTC loss function to break the 2S09 Switchboard Hub5'00 speech recognition dataset benchmark
Connectionist temporal classification
Connectionist_temporal_classification
Line-breaking algorithm used in the TeX typesetting package
algorithm by using a discrete dynamic programming method to minimize a loss function that attempts to quantify the aesthetic qualities desired in the finished
Knuth–Plass line-breaking algorithm
Knuth–Plass_line-breaking_algorithm
Approximation method in statistics
Orthogonal projection Proximal gradient methods for learning Quadratic loss function Root mean square Squared deviations from the mean Charnes, A.; Frome
Least_squares
Type of statistical measure over subsets of a dataset
viewed as a low-pass finite impulse response filter. Because the boxcar function outlines its filter coefficients, it is called a boxcar filter. It is sometimes
Moving_average
Specialized form of regression analysis, in statistics
error loss, and therefore has more leverage over the regression estimates. The Huber loss function is a robust alternative to standard square error loss that
Robust_regression
Pattern of motion in a visual scene due to relative motion of the observer
{\displaystyle \alpha } is a constant, and Ψ ( ) {\displaystyle \Psi ()} is a loss function. This optimisation problem is difficult to solve owing to its non-linearity
Optical_flow
Statistic which divides a data set into 100 parts and analyzes it as a percentage
the percentile approximates the percentile function, the inverse of the cumulative distribution function. A related quantity is the percentile rank of
Percentile
LOSS FUNCTION
LOSS FUNCTION
Surname or Lastname
North German
North German : habitational name from any of several places called Loose or Loosey.North German : from a short form of Nikolaus, German form of Nicholas.Dutch : nickname from the adjective loos ‘cunning’, ‘artful’, ‘guileful’.English : variant spelling of Loose.
Male
English
Scottish surname transferred to forename use, derived from the Gaelic word ros, ROSS means "headland, promontory."
Surname or Lastname
English
English : variant of Close 1.German : variant of Kloss.
Boy/Male
German Hebrew
One of the Goths'. Introduced into Britam as a masculine name during the Norman Conquest,...
Surname or Lastname
English and Welsh
English and Welsh : from the personal name Moss, a Middle English vernacular form of the Biblical name Moses.English and Scottish : topographic name for someone who lived by a peat bog, Middle English, Old English mos, or a habitational name from a place named with this word. (It was not until later that the vocabulary word came to denote the class of plants characteristic of a peat-bog habitat, under the influence of the related Old Norse word mosi.)Americanized form of Moses or some other like-sounding Jewish surname.Irish (Ulster) : part translation of Gaelic Ó Maolmhóna ‘descendant of Maolmhóna’, a personal name composed of the elements maol ‘servant’, ‘tonsured one’, ‘devotee’ + a second element which was assumed to be móin (genitive móna) ‘moorland’, ‘peat bog’.
Surname or Lastname
North German variant of Laas 2.Jewish (Ashkenazic)
North German variant of Laas 2.Jewish (Ashkenazic) : unexplained.English : nickname from Middle English lesse, lasse ‘smaller’ (from Old English lǣssa ‘less’), perhaps also used in the sense ‘younger’.
Surname or Lastname
English
English : variant spelling of Fosse.Danish : from fos, vos ‘fox’; a nickname for a sly or cunning person or a habitational name for someone living at a house distinguished by the sign of a fox.Norwegian : habitational name from a farmstead so named from Old Norse fors ‘waterfall’, examples of which are found throughout Norway.Altered spelling of German Voss or the Dutch cognate Vos.
Male
Hebrew
 Medieval Jewish form of Hebrew Moshe, MOSS means "drawn out." Compare with another form of Moss.
Surname or Lastname
English
English : nickname for a hunchback, from Old French bossu ‘hunchbacked’ (a derivative of bosse ‘lump’, ‘hump’; compare Bossard 2).German : from a short form of the personal name Borkhardt, a variant of Burkhart.Possibly an altered spelling of South German Bös (see Bos).Danish : medieval variant of Buus, a surname of uncertain origin, perhaps from German būsemen ‘devil’, ‘ghost’.
Female
English
Pet form of English unisex Jocelyn, JOSS means "Gaut."Â Compare with strictly masculine Joss.
Surname or Lastname
Norwegian
Norwegian : habitational name from any of various farmsteads named Noss, from Old Norse nǫs ‘nose’, in reference to any natural feature, such as a crag or mountain peak, that is shaped like a nose.German (of Slavic origin) : see Nosek.German : variant of Notz.English : variant of Ness 1.
Surname or Lastname
German
German : variant of Klaus, a reduced form of the personal name Nikolaus, German form of Nicholas.English : nickname for a flatterer, from Old French glose ‘flattery’.
Girl/Female
Latin
The mythological Roman goddess of flowers. Diminutive of Florence: From 'florentius' or...
Surname or Lastname
Probably a shortened form of an unidentified Jewish surname.English
Probably a shortened form of an unidentified Jewish surname.English : variant of Lass 3.
Surname or Lastname
English (chiefly West Country)
English (chiefly West Country) : variant of Gosse.German : from the Germanic personal name Gozzo, a short form of the various compound names with the first element gÅd ‘good’ or god, got ‘god’.
Male
English
 English surname transferred to forename use, derived from medieval Jewish Moss (2), MOSS means "drawn out." Compare with another form of Moss.
Surname or Lastname
Scottish and English (of Norman origin)
Scottish and English (of Norman origin) : habitational name for someone from Rots near Caen in Normandy, probably named with the Germanic element rod ‘clearing’. Compare Rhodes. This was the original home of a family de Ros, who were established in Kent in 1130.Scottish and English : habitational name from any of various places called Ross or Roos(e), deriving the name from Welsh rhós ‘upland’ or moorland, or from a British ancestor of this word, which also had the sense ‘promontory’. This is the sense of the cognate Gaelic word ros. Known sources of the surname include Roos in Humberside (formerly in East Yorkshire) and the region of northern Scotland known as Ross. Other possible sources are Ross-on-Wye in Herefordshire, Ross in Northumbria (which is on a promontory), and Roose in LancashireEnglish and German : from the Germanic personal name Rozzo, a short form of the various compound names with the first element hrÅd ‘renown’, introduced into England by the Normans in the form Roce.German and Jewish (Ashkenazic) : metonymic occupational name for a breeder or keeper of horses, from Middle High German ros, German Ross ‘horse’; perhaps also a nickname for someone thought to resemble a horse or a habitational name for someone who lived at a house distinguished by the sign of a horse.Jewish : Americanized form of Rose 3.
Surname or Lastname
English and German
English and German : from the Breton personal name Iodoc (Latinized as Jodocus) (see Joyce).
Female
English
(Λωΐς) Greek name of uncertain origin, possibly LOIS means "agreeable." In the bible, this is the name of the grandmother of Timothy. Compare with masculine Lois.
Male
Portuguese
Galician-Portuguese form of French Louis, LOIS means "famous warrior."Â Compare with feminine Lois.
LOSS FUNCTION
LOSS FUNCTION
Male
English
English surname transferred to unisex forename use, derived from a Norman French byname for an unfortunate person, from Old French malheure, MALLORY means "unfortunate, unhappy, unlucky."
Female
Egyptian
, The Good Companion.
Surname or Lastname
English
English : variant of Folds.Scottish : habitational name from any of various places called Faulds, as for example in Ayrshire, Lanarkshire, and Perth.
Boy/Male
Biblical
Hardness; his gravity; his offense.
Surname or Lastname
English
English : topographic name from Middle English stocking ‘ground cleared of stumps’.South German : habitational name from any of several places in Bavaria and Styria named Stocking.
Boy/Male
Arabic
Treasurer; Cashier
Surname or Lastname
English
English : from Middle English lady ‘lady’, ‘female head of a household’, hence a nickname for a woman who was ladylike or the head of a household or for an effeminate man.Polish : variant of Lada.Hungarian (Ládi) : habitational name for someone from Lád in Borsod county or Lad in Somogy county.
Girl/Female
Arabic, Bengali, Gujarati, Hindu, Indian, Kannada, Malayalam, Marathi, Muslim, Sanskrit, Tamil, Telugu, Traditional
A Star; Morning Star
Girl/Female
Indian, Sanskrit
To Progress
Girl/Female
Arabic
Lotus
LOSS FUNCTION
LOSS FUNCTION
LOSS FUNCTION
LOSS FUNCTION
LOSS FUNCTION
v. t.
Not perceptible to the senses; no longer visible; as, an island lost in a fog; a person lost in a crowd.
v. t.
To give a superficial luster or gloss to; to make smooth and shining; as, to gloss cloth.
v. t.
Failure to use advantageously; as, loss of time.
v. t.
Ruined or destroyed, either physically or morally; past help or hope; as, a ship lost at sea; a woman lost to virtue; a lost soul.
v. t.
To divest of the ross, or rough, scaly surface; as, to ross bark.
a.
Smaller; not so large or great; not so much; shorter; inferior; as, a less quantity or number; a horse of less size or value; in less time than before.
v. t.
Not employed or enjoyed; thrown away; employed ineffectually; wasted; squandered; as, a lost day; a lost opportunity or benefit.
n.
Praise. See Loos.
v. t.
Having wandered from, or unable to find, the way; bewildered; perplexed; as, a child lost in the woods; a stranger lost in London.
v. t.
To cease to have; to possess no longer; to suffer diminution of; as, to lose one's relish for anything; to lose one's health.
v. t.
Parted with; no longer held or possessed; as, a lost limb; lost honor.
v. t.
That which is lost or from which one has parted; waste; -- opposed to gain or increase; as, the loss of liquor by leakage was considerable.
v. t.
To make less; to lessen.
v. t.
The state of being lost or destroyed; especially, the wreck or foundering of a ship or other vessel.
v. t.
Failure to gain or win; as, loss of a race or battle.
v. t.
To cover or overgrow with moss.
v. t.
The act of losing; failure; destruction; privation; as, the loss of property; loss of money by gaming; loss of health or reputation.
adv.
Not so much; in a smaller or lower degree; as, less bright or loud; less beautiful.
v. t.
The state of losing or having lost; the privation, defect, misfortune, harm, etc., which ensues from losing.
v. t.
Hardened beyond sensibility or recovery; alienated; insensible; as, lost to shame; lost to all sense of honor.