Lipschitz-based robustness estimation for hyperdimensional learning. [PDF]
Yeung C +5 more
europepmc +1 more source
Repelled Point Processes With Application to Numerical Integration
ABSTRACT We look at Monte Carlo numerical integration from a stochastic geometry point of view. While crude Monte Carlo estimators relate to linear statistics of a homogeneous Poisson point process (PPP), linear statistics of more regularly spread point processes can yield unbiased estimators with faster‐decaying variance, and thus lower integration ...
Diala Hawat +3 more
wiley +1 more source
On the ROF Model in Rectilinear Anisotropy: Piecewise Constant Approximation and Universal Minimality. [PDF]
Kirisits C, Setterqvist E.
europepmc +1 more source
Transfer Learning for Moderate-Dimensional Ridge-Regularized Robust Linear Regression. [PDF]
Lyu L, Guo X, Liu Z.
europepmc +1 more source
Safe and adaptive control of non-stationary stochastic systems via Lyapunov-constrained distributional reinforcement learning. [PDF]
Khaniki MAL, Mirzaee M, Moradi E.
europepmc +1 more source
Fractional-order analysis and optimal control of the NERA model: stability, sensitivity, and numerical validation. [PDF]
Pandey A, Ghosh S.
europepmc +1 more source
Entangled States are Typically Incomparable. [PDF]
Jain V, Kwan M, Michelen M.
europepmc +1 more source
DAFRL: a dynamic adaptive mean field game-based multi-agent cooperative decision-making method. [PDF]
Tang Y, Fan C, Yu D.
europepmc +1 more source
Real-valued Lipschitz functions and metric properties of functions
The purpose of this article is to explore the very general phenomenon that a function between metric spaces has a particular metric property if and only if whenever it is followed in a composition by an arbitrary realvalued Lipschitz function, the ...
Gerald Beer, M Isabel Garrido
exaly +2 more sources

