An Information-Theoretic Analysis of Thompson Sampling

We provide an information-theoretic analysis of Thompson sampling that applies across a broad range of online optimization problems in which a decision-maker must learn from partial feedback. This analysis inherits the simplicity and elegance of information theory and leads to regret bounds that scale with the entropy of the optimal-action distribution. This strengthens preexisting results and yields new insight into how information improves performance

Sub-Jordan Operator Tuples

In this talk we will discuss tuples of 3-isometric and 3-symmetric operators. These operators have connections with Sturm-Liouville theory and are natural generalizations of self-adjoint and isometric operators. We call an operator $J$ a Jordan operator of order $2$ if $J=A+N$, where $A$ is either unitary or self-adjoint, $N$ is nilpotent of order $2$, and $A$ commutes with $N$. As shown in the work of Agler, Ball and Helton, and joint work with McCullough, 3-symmetric and 3-isometric operators are the restriction of a Jordan operator to an invariant subspace. In this talk we discuss the extension of these theorems to the multi-variable case and an application to disconjugacy for Sch{\ o}dinger operators

Detección fenotípica de cultivos con datos relevados a campo

La presente línea de investigación busca realizar un análisis de los datos fenotípicos de cultivos agronómicos que las tecnologías generan y poder, a partir de ello, obtener información. Esto mediante el uso plataformas robóticas de sensado a campo y el uso de imágenes digitales capturadas con cámaras de luz visible o multiespectrales, más la utilización de técnicas de procesamiento digital.Área: TICs, Electrónica e Informática

Convergence of weak-SINDy Surrogate Models

In this paper, we give an in-depth error analysis for surrogate models generated by a variant of the Sparse Identification of Nonlinear Dynamics (SINDy) method. We start with an overview of a variety of non-linear system identification techniques, namely, SINDy, weak-SINDy, and the occupation kernel method. Under the assumption that the dynamics are a finite linear combination of a set of basis functions, these methods establish a matrix equation to recover coefficients. We illuminate the structural similarities between these techniques and establish a projection property for the weak-SINDy technique. Following the overview, we analyze the error of surrogate models generated by a simplified version of weak-SINDy. In particular, under the assumption of boundedness of a composition operator given by the solution, we show that (i) the surrogate dynamics converges towards the true dynamics and (ii) the solution of the surrogate model is reasonably close to the true solution. Finally, as an application, we discuss the use of a combination of weak-SINDy surrogate modeling and proper orthogonal decomposition (POD) to build a surrogate model for partial differential equations (PDEs)