Results 51 to 60 of about 71,119 (185)
A minimax p-robust optimization approach for planning under uncertainty
Planning under uncertainty is one of the important issues in production planning. The development of mathematical models under uncertainty has long been studied in order to avoid the impact of uncertain factors and to maintain stable and excellent ...
Kwang-Kyu SEO, Jun KIM, Byung Do CHUNG
doaj +1 more source
Sion's mini-max theorem and Nash equilibrium in a multi-players game with two groups which is zero-sum and symmetric in each group [PDF]
We consider the relation between Sion's minimax theorem for a continuous function and a Nash equilibrium in a multi-players game with two groups which is zero-sum and symmetric in each group. We will show the following results. 1. The existence of Nash
Satoh, Atsuhiro, Tanaka, Yasuhito
core +2 more sources
Computing Skinning Weights via Convex Duality
We present an alternate optimization method to compute bounded biharmonic skinning weights. Our method relies on a dual formulation, which can be optimized with a nonnegative linear least squares setup. Abstract We study the problem of optimising for skinning weights through the lens of convex duality.
J. Solomon, O. Stein
wiley +1 more source
Minimax Estimation of Nonregular Parameters and Discontinuity in Minimax Risk
When a parameter of interest is nondifferentiable in the probability, the existing theory of semiparametric efficient estimation is not applicable, as it does not have an influence function.
Bickel P. J. +7 more
core +1 more source
Miners' Reward Elasticity and Stability of Competing Proof‐of‐Work Cryptocurrencies
ABSTRACT Proof‐of‐Work cryptocurrencies employ miners to sustain the system through algorithmic reward adjustments. We develop a stochastic model of the multicurrency mining and identify conditions for stable transaction speeds. Bitcoin's algorithm requires hash supply elasticity <$<$1 for stability, while ASERT remains stable for any elasticity and ...
Kohei Kawaguchi +2 more
wiley +1 more source
Minimax Linear Smoothers [PDF]
We consider the problem of estimating the mean of a multivariate distribution. As a general alternative to penalized least squares estimators, we consider minimax estimators for squared error over a restricted parameter space where the restriction is determined by the penalization term.
openaire +1 more source
A Non‐Parametric Framework for Correlation Functions on Product Metric Spaces
Summary We propose a non‐parametric framework for analysing data defined over products of metric spaces, a versatile class encountered in various fields. This framework accommodates non‐stationarity and seasonality and is applicable to both local and global domains, such as the Earth's surface, as well as domains evolving over linear time or time ...
Pier Giovanni Bissiri +3 more
wiley +1 more source
In many sports contests, the equilibrium requires players to randomize across repeated rounds, i.e., exhibit no temporal predictability. Such sports data present a window into the (in)efficiency of random sequence generation in a natural competitive ...
Leonidas Spiliopoulos
doaj +1 more source
Minimax Structured Normal Means Inference
We provide a unified treatment of a broad class of noisy structure recovery problems, known as structured normal means problems. In this setting, the goal is to identify, from a finite collection of Gaussian distributions with different means, the ...
Krishnamurthy, Akshay
core +1 more source
Adaptive Estimation for Weakly Dependent Functional Times Series
ABSTRACT We propose adaptive mean and autocovariance function estimators for stationary functional time series under 𝕃p−m‐approximability assumptions. These estimators are designed to adapt to the regularity of the curves and to accommodate both sparse and dense data designs.
Hassan Maissoro +2 more
wiley +1 more source

