Systematic review of financial distress identification using artificial intelligence methods
The study presents a systematic review of 232 studies on various aspects of the use of
artificial intelligence methods for identification of financial distress (such as bankruptcy or …
artificial intelligence methods for identification of financial distress (such as bankruptcy or …
Clustering high dimensional data
I Assent - Wiley Interdisciplinary Reviews: Data Mining and …, 2012 - Wiley Online Library
High‐dimensional data, ie, data described by a large number of attributes, pose specific
challenges to clustering. The so‐called 'curse of dimensionality', coined originally to …
challenges to clustering. The so‐called 'curse of dimensionality', coined originally to …
Multilevel monte carlo path simulation
MB Giles - Operations research, 2008 - pubsonline.informs.org
We show that multigrid ideas can be used to reduce the computational complexity of
estimating an expected value arising from a stochastic differential equation using Monte …
estimating an expected value arising from a stochastic differential equation using Monte …
High-dimensional integration: the quasi-Monte Carlo way
This paper is a contemporary review of QMC ('quasi-Monte Carlo') methods, that is, equal-
weight rules for the approximate evaluation of high-dimensional integrals over the unit cube …
weight rules for the approximate evaluation of high-dimensional integrals over the unit cube …
The Bayesian approach to inverse problems
M Dashti, AM Stuart - arxiv preprint arxiv:1302.6989, 2013 - arxiv.org
These lecture notes highlight the mathematical and computational structure relating to the
formulation of, and development of algorithms for, the Bayesian approach to inverse …
formulation of, and development of algorithms for, the Bayesian approach to inverse …
[BOOK][B] Lecture notes in computational science and engineering
TJ Barth, M Griebel, DE Keyes, RM Nieminen, D Roose… - 2005 - Springer
The FEniCS Project set out in 2003 with an idea to automate the solution of mathematical
models based on differential equations. Initially, the FEniCS Project consisted of two …
models based on differential equations. Initially, the FEniCS Project consisted of two …
Super-samples from kernel herding
We extend the herding algorithm to continuous spaces by using the kernel trick. The
resulting" kernel herding" algorithm is an infinite memory deterministic process that learns to …
resulting" kernel herding" algorithm is an infinite memory deterministic process that learns to …
Text-video retrieval with disentangled conceptualization and set-to-set alignment
Text-video retrieval is a challenging cross-modal task, which aims to align visual entities with
natural language descriptions. Current methods either fail to leverage the local details or are …
natural language descriptions. Current methods either fail to leverage the local details or are …
Importance sampling: Intrinsic dimension and computational cost
The basic idea of importance sampling is to use independent samples from a proposal
measure in order to approximate expectations with respect to a target measure. It is key to …
measure in order to approximate expectations with respect to a target measure. It is key to …
The low-rank hypothesis of complex systems
Complex systems are high-dimensional nonlinear dynamical systems with heterogeneous
interactions among their constituents. To make interpretable predictions about their large …
interactions among their constituents. To make interpretable predictions about their large …