Results 111 to 120 of about 1,101,519 (253)

Sparse Causal Dynamic Linear Regression

Journal of Time Series Analysis, EarlyView.
ABSTRACT We develop a sparse causal dynamic regression framework for long multivariate time series. With very long time series, the potentially large number of lags and leads in a dynamic regression model often makes time‐domain estimation numerically unstable or intractable.
Rui Huang, Kung‐Sik Chan
wiley   +1 more source

Optimal Portfolio Choice With Cross‐Impact Propagators

Mathematical Finance, EarlyView.
ABSTRACT We consider a class of optimal portfolio choice problems in continuous time where the agent's transactions create both transient cross‐impact driven by a matrix‐valued Volterra propagator, as well as temporary price impact. We formulate this problem as the maximization of a revenue‐risk functional, where the agent also exploits available ...
Eduardo Abi Jaber, Eyal Neuman, Sturmius Tuschmann   +2 more
wiley   +1 more source

Frobenius deep feature fusion architecture to detect diabetic retinopathy

Discover Applied Sciences
Purpose Diabetic retinopathy is a medical complication affecting the retina of patients prone to prolonged periods of Diabetes mellitus. Early detection and diagnosis are essential since the symptoms are subtle at the early stages.
C. Priyadharsini, Y. Asnath Victy Phamila   +1 more
doaj   +1 more source

FroSSL: Frobenius Norm Minimization for Self-Supervised Learning

arXiv.org, 2023
Oscar Skean, Aayush Dhakal, Nathan Jacobs, L. S. Giraldo   +3 more
semanticscholar   +1 more source

Reinforcement Learning for Jump‐Diffusions, With Financial Applications

Mathematical Finance, EarlyView.
ABSTRACT We study continuous‐time reinforcement learning (RL) for stochastic control in which system dynamics are governed by jump‐diffusion processes. We formulate an entropy‐regularized exploratory control problem with stochastic policies to capture the exploration–exploitation balance essential for RL.
Xuefeng Gao, Lingfei Li, Xun Yu Zhou
wiley   +1 more source

Relative Arbitrage Opportunities With Interactions Among N Investors

Mathematical Finance, EarlyView.
ABSTRACT The relative arbitrage portfolio outperforms a benchmark portfolio over a given time‐horizon with probability one. With market price of risk processes depending on the market portfolio and investors, this paper analyzes the multi‐agent optimization of relative arbitrage opportunities in the coupled system of market and wealth dynamics.
Tomoyuki Ichiba, Nicole Tianjiao Yang
wiley   +1 more source

Predicting Adaptively Chosen Observables in Quantum Systems

PRX Quantum
Recent advances have demonstrated that O(log⁡M) measurements suffice to predict M properties of arbitrarily large quantum many-body systems. However, these remarkable findings assume that the properties to be predicted are chosen independently of the ...
Jerry Huang, Laura Lewis, Hsin-Yuan Huang, John Preskill   +3 more
doaj   +1 more source

Panel Sequential Group Estimation of Interactive Effects Models

Oxford Bulletin of Economics and Statistics, EarlyView.
ABSTRACT This paper proposes a novel procedure to identify latent groups in the slopes of panel data models with interactive effects. The method is straightforward to apply and relies only on closed‐form estimators when evaluating the objective function.
Ignace De Vos, Joakim Westerlund
wiley   +1 more source

Threshold Regression for Fixed‐T$$ T $$ Panel Data with Interactive Fixed Effects

Oxford Bulletin of Economics and Statistics, EarlyView.
ABSTRACT This paper develops a new toolbox for estimation and inference in panel data threshold regression models with interactive fixed effects and a fixed number of time periods, T$$ T $$. The toolbox is designed to be simple, accurate, and computationally efficient.
Jan Ditzen, Yiannis Karavias, Joakim Westerlund   +2 more
wiley   +1 more source

Sparse Minimum Redundancy Maximum Relevance for Feature Selection

Scandinavian Journal of Statistics, EarlyView.
ABSTRACT We propose a feature screening method that integrates both feature–feature and feature–target relationships. Inactive features are identified via a penalized minimum Redundancy Maximum Relevance (mRMR) procedure, which is the continuous version of the classical mRMR penalized by a non‐convex regularizer, and where the parameters estimated as ...
Peter Naylor, Benjamin Poignard, Héctor Climente‐González, Makoto Yamada   +3 more
wiley   +1 more source