A locally-built, LLM-digested index of recent arXiv papers in quant finance, geometry/topology, and statistical ML — keyword search served straight from SQLite on this machine.
Paper estimates the order of vertices in random recursive trees.
AdaVol adapts QML for real-time GARCH volatility prediction.
We prove that desingularizations of non degenerate Poincaré-Einstein metrics with A1 singularities remain non degenerate. In principle this enables a recursive procedure to desingularize the other Fuchsian singularities. We illustrate this procedure by the A2 case.
The article improves prediction by aggregating Kalman recursions online.
MREC efficiently matches and aligns point clouds, useful for single cell molecular data.
In this paper, the method of approximate transformation groups which was proposed by Baikov, Gazizov and Ibragimov, is extended on Hamiltonian and bi-Hamiltonian systems of evolution equations. Indeed, as a main consequence, this extended procedure is applied in order to compute the approximate conservation laws and ap…
We consider a structural model where the survival/default state is observed together with a noisy version of the firm value process. This assumption makes the model more realistic than most of the existing alternatives, but triggers important challenges related to the computation of conditional default probabilities. I…
Bayesian method for multivariate autoregressive models with exogenous inputs.
This paper describes a recursive estimation procedure for multivariate binary densities (probability distributions of vectors of Bernoulli random variables) using orthogonal expansions. For covariates, there are basis coefficients to estimate, which renders conventional approaches computationally prohibitive …
Paper presents novel online MTL methods using WRLS and OSLSSVR.
We introduce a recursive algorithm for performing compressed sensing on streaming data. The approach consists of a) recursive encoding, where we sample the input stream via overlapping windowing and make use of the previous measurement in obtaining the next one, and b) recursive decoding, where the signal estimate from…
Study volumes of Klein surfaces, extending Mirzakhani's recursion.
Introduces a new theoretical framework for exponential smoothing.
Paper proposes online learning for estimating AC network admittance matrix.
This study proposes the segmentation procedure of univariate time series based on Fisher's exact test. We show that an adequate change point can be detected as the minimum value of p-value. It is shown that the proposed procedure can detect change points for an artificial time series. We apply the proposed method to fi…
XR-Transformer accelerates XMC by recursively fine-tuning on multi-resolution objectives.
Optimizes Gaussian process hyperparameters using Bayesian autoregression.
This study considers the multivariate segmentation procedure under the assumption of the multivariate Gaussian mixture. Jensen-Shannon divergence between two multivariate Gaussian distributions is employed as a discriminator and a recursive segmentation procedure is proposed. The daily log-return time series for 30 cur…
This paper refines the Gaussian Sinkhorn algorithm for general multivariate models.
We study the problem of learning a latent tree graphical model where samples are available only from a subset of variables. We propose two consistent and computationally efficient algorithms for learning minimal latent trees, that is, trees without any redundant hidden nodes. Unlike many existing methods, the observed …
New algorithm reduces rank constrained optimization problems.
Study on friction forces for nonholonomic systems using affine connections.
This paper presents a general iterative bias correction procedure for regression smoothers. This bias reduction schema is shown to correspond operationally to the Boosting algorithm and provides a new statistical interpretation for Boosting. We analyze the behavior of the Boosting algorithm applied to commo…
The paper investigates model collapse in language models from a probabilistic perspective.
Bayesian method improves online NARMAX model identification.
A new recursive mixture estimation algorithm improves VAE inference efficiency and accuracy.
Value-at-Risk (VaR) and Conditional Value-at-Risk (CVaR) are two risk measures which are widely used in the practice of risk management. This paper deals with the problem of computing both VaR and CVaR using stochastic approximation (with decreasing steps): we propose a first Robbins-Monro procedure based on Rockaffela…
We introduce the notion of weak reduciblity for Dupin submanifolds with arbitrary codimension. We give a complete characterization of all weakly reducible Dupin submanifolds, as a consequence of a general result on a broader class of Euclidean submanifolds. As a main application, we derive an explicit recursive procedu…
The paper challenges the use of decision trees for pointwise inference due to slow convergence rates.
Quantization algorithms have been successfully adopted to option pricing in finance thanks to the high convergence rate of the numerical approximation. In particular, very recently, recursive marginal quantization has been proven to be a flexible and versatile tool when applied to stochastic volatility processes. In th…
We introduce a new recursive aggregation procedure called Bernstein Online Aggregation (BOA). The exponential weights include an accuracy term and a second order term that is a proxy of the quadratic variation as in Hazan and Kale (2010). This second term stabilizes the procedure that is optimal in different senses. We…
GADGET framework decomposes global feature effects using recursive partitioning.
Clustering with fast algorithms large samples of high dimensional data is an important challenge in computational statistics. Borrowing ideas from MacQueen (1967) who introduced a sequential version of the -means algorithm, a new class of recursive stochastic gradient algorithms designed for the -medians loss cri…
A method for calculating multi-portfolio time consistent multivariate risk measures in discrete time is presented. Market models for assets with transaction costs or illiquidity and possible trading constraints are considered on a finite probability space. The set of capital requirements at each time and state is c…
Recursive neural networks have widely been used by researchers to handle applications with recursively or hierarchically structured data. However, embedded control flow deep learning frameworks such as TensorFlow, Theano, Caffe2, and MXNet fail to efficiently represent and execute such neural networks, due to lack of s…
Optimizes investment under uncertain time horizons with non-concave utility.
This work presents an explicit-implicit procedure to compute a model predictive control (MPC) law with guarantees on recursive feasibility and asymptotic stability. The approach combines an offline-trained fully-connected neural network with an online primal active set solver. The neural network provides a control inpu…
New PAC-Bayes method updates priors without losing confidence information.
Paper defines Farey Recursive Functions and explores their properties.
A new feature selection method using random forest and Kolmogorov filter.
The paper explores generalizations of Mirzakhani's recursion and computes volumes for physical gravity models.
We study an open problem of risk-sensitive portfolio allocation in a regime-switching credit market with default contagion. The state space of the Markovian regime-switching process is assumed to be a countably infinite set. To characterize the value function, we investigate the corresponding recursive infinite-dimensi…
Method minimizes total cost of classification by acquiring covariates efficiently.
Efficient online kernel CUSUM detects changes quickly and accurately.
A new method for robust product Markovian quantization overcomes numerical instabilities.
Tab-TRM uses recursive model for insurance pricing on tabular data.
A new scheme for FBSDEs simplifies computation without Monte Carlo.
Gradient-free deep learning for large datasets.