Discrete logarithm problemGeneralized multiple discrete logarithm problemLower boundFast multipoint evaluationDiscrete logarithm problem (DLP) is one of the fundamental hard problems used in cryptography. For 1
Faster approximation algorithms for generalized flow. In Proceedings of the Tenth Annual ACM-SIAM Symposium on Discrete Algorithms, January 1999. http://www.cs.princeton.edu/ wayne/packing.ps. 16]]>generalized shortest pathsrestricted uncapacitated transshipment problemgeneralized maximum flow...
Summary: This paper aims at introducing generalized Jacobians as a new candidate for discrete logarithm (DL) based cryptography. The motivation for this work came from the observation that several practical DL-based cryptosystems, such as ElGamal, the Elliptic and Hyperelliptic Curve Cryptosystems, XT...
Although setting \(w_{j \ell } = 1\) is usual, this may cause a problem of over-shrinkage because all pairs of parameters are shrunk uniformly by the common \(\lambda \). As one option to avoid this problem, we can use the following weight based on adaptive-Lasso (Zou 2006):...
2.ON REDUCING FACTORIZATION TO THE DISCRETE LOGARITHM PROBLEM MODULO A COMPOSITE and spring 机译:关于减少离散对数问题模量复合的分解 Jacek Pomykala ,Bartosz Zralek - Computational complexity - 2012 3.(t,n) threshold verifiable multisecret sharing scheme based on factorisation intractability and dis...
(Weak solution to the regularized system) We say that a pair \((u,w) \in {\mathbb {U}} \times {\mathbb {W}}\) is a weak solution to problem (4.1), if $$\begin{aligned} u,w \ge 0, \quad w \in L^\infty ((0,T) \times \varOmega ), \quad \nabla w \in L^p(0,...
Such measures stop short of the most natural way of interpreting the parameters in discrete probability models such as ordered response models, namely in terms of marginal probability effects. Indeed, the main concern of this paper is to determine how the change in 8 a covariate, such as ...
Consider the problem of learning a regression function M:R→R from observations of the form zi=(xi,yi)∈R2. More specifically, suppose that the observed outputs are imprecise and therefore modeled as intervals Yi⊆R (whereas the inputs xi are precise). Our learning algorithm ALG assumes a...
The idea in out-of-sample evaluations is to separate the estimation and evaluation stages so to avoid overfitting problems, and to mimic as close as possible a real time forecasting problem, in which a decision maker cannot estimate his/her preferred models with observations that are not availabl...
i=1 Ltgt (reproj. at target pose) Lpred (reproj. at predicted pose) (5) The only remaining problem is the integration in the second term, which is elaborated in Section 3.2. Propoer Loss g.t. g.t. Impropoer Loss g.t. ...