Zobrazeno 1 - 10
of 90
pro vyhledávání: '"49q99"'
Autor:
Cheng, Andrew, Weber, Melanie
Matrix-valued optimization tasks, including those involving symmetric positive definite (SPD) matrices, arise in a wide range of applications in machine learning, data science and statistics. Classically, such problems are solved via constrained Eucl
Externí odkaz:
http://arxiv.org/abs/2410.09660
Autor:
Esposito, Flavia, Ang, Andersen
Nonnegative Matrix Factorization (NMF) is the problem of approximating a given nonnegative matrix M through the conic combination of two nonnegative low-rank matrices W and H. Traditionally NMF is tackled by optimizing a specific objective function e
Externí odkaz:
http://arxiv.org/abs/2405.12823
Autor:
Kupferman, Raz, Maor, Cy
Motivated by recent interest in elastic problems in which the target space is non-Euclidean, we study a limit where local rest distances within an elastic body are incompatible, yet close to, distances within the ambient space. Specifically, we obtai
Externí odkaz:
http://arxiv.org/abs/2402.08041
Autor:
Bayraktar, Erhan, Han, Bingyan
We develop a fitted value iteration (FVI) method to compute bicausal optimal transport (OT) where couplings have an adapted structure. Based on the dynamic programming formulation, FVI adopts a function class to approximate the value functions in bic
Externí odkaz:
http://arxiv.org/abs/2306.12658
When generalizing schemes for real-valued data approximation or decomposition to data living in Riemannian manifolds, tangent space-based schemes are very attractive for the simple reason that these spaces are linear. An open challenge is to do this
Externí odkaz:
http://arxiv.org/abs/2306.00507
Autor:
Weber, Melanie, Sra, Suvrit
This paper studies algorithms for efficiently computing Brascamp-Lieb constants, a task that has recently received much interest. In particular, we reduce the computation to a nonlinear matrix-valued iteration, whose convergence we analyze through th
Externí odkaz:
http://arxiv.org/abs/2208.05013
In this paper, we propose a Riemannian version of the difference of convex algorithm (DCA) to solve a minimization problem involving the difference of convex (DC) function. We establish the equivalence between the classical and simplified Riemannian
Externí odkaz:
http://arxiv.org/abs/2112.05250
For cost functions $c(x,y)=h(x-y)$ with $h\in C^2$ homogeneous of degree $p\geq 2$, we show $L^\infty$-estimates of $Tx-x$ on balls, where $T$ is an $h$-monotone map. Estimates for the interpolating mappings $T_t=t(T-I)+I$ are deduced from this.
Externí odkaz:
http://arxiv.org/abs/2106.02899
Autor:
Diepeveen, Willem, Lellmann, Jan
We propose a higher-order method for solving non-smooth optimization problems on manifolds. In order to obtain superlinear convergence, we apply a Riemannian Semi-smooth Newton method to a non-smooth non-linear primal-dual optimality system based on
Externí odkaz:
http://arxiv.org/abs/2102.10309
Autor:
Tyranowski, Tomasz M.
In this work we recast the collisional Vlasov-Maxwell and Vlasov-Poisson equations as systems of coupled stochastic and partial differential equations, and we derive stochastic variational principles which underlie such reformulations. We also propos
Externí odkaz:
http://arxiv.org/abs/2102.09611