arXiv research

Paper defines Farey Recursive Functions and explores their properties.

Topological recursion recovers a specific partition function for colored knots.

Harer and Zagier proved a recursion to enumerate gluings of a $2d$-gon that result in an orientable genus $g$ surface, in their work on Euler characteristics of moduli spaces of curves. Analogous results have been discovered for other enumerative problems, so it is natural to pose the following question: how large is t…

We propose a general theory for constructing functorial assignments $Σ\longmapsto Ω_Σ \in E(Σ)$ for a large class of functors $E$ from a certain category of bordered surfaces to a suitable target category of topological vector spaces. The construction proceeds by successive excisions of homotopy classes of embedded pai…

The paper uses LSM to solve complex monetary utility functions.

Solves a recursion for Gromov-Witten invariants of the unknot.

In this paper, we study and analyze the mini-batch version of StochAstic Recursive grAdient algoritHm (SARAH), a method employing the stochastic recursive gradient, for solving empirical loss minimization for the case of nonconvex losses. We provide a sublinear convergence rate (to stationary points) for general noncon…

Deep learning solves dynamic programming with recursive utility.

The paper uses tensor decompositions to improve neural network models for tree data.

This research extends topological recursion to hyperbolic surfaces with tight boundaries and conical defects.

Novel method recursively partitions sample space for density estimation.

We produce examples of codimension one foliations of the Euclidean and hyperbolic planes with bounded geometry which are topologically products, but for which leaves are non-recursively distorted. That is, the function which compares intrinsic distances in leaves with extrinsic distances in the ambient space grows fast…

Recurrent neural networks (RNNs) process input text sequentially and model the conditional transition between word tokens. In contrast, the advantages of recursive networks include that they explicitly model the compositionality and the recursive structure of natural language. However, the current recursive architectur…

CEFOL uses deep learning for dynamic programming with recursive utility.

Greedy training of recursive partitioning estimators faces a computational barrier when the true function doesn't satisfy a specific property.

R2-B2 optimizes game interactions with recursive reasoning.

New recursive algorithm estimates conditional kernel mean embeddings in Hilbert space.

The paper studies risk-sensitive MDPs with recursive risk measures.

ERM uses energy-based selection to improve recursive reasoning.

This study presents a rapid multiple incremental and decremental mechanism based on Weight-Error Curves (WECs) for support-vector analysis. Recursion-free computation is proposed for predicting the Lagrangian multipliers of new samples. This study examines Ridge Support Vector Models, subsequently devising a recursion-…

The topological recursion of Eynard and Orantin governs a variety of problems in enumerative geometry and mathematical physics. The recursion uses the data of a spectral curve to define an infinite family of multidifferentials. It has been conjectured that, under certain conditions, the spectral curve possesses a non-c…

Paper presents novel online MTL methods using WRLS and OSLSSVR.

New algorithm speeds up online mapping of unknown terrains.

Solves optimal stopping problem with Poisson constraints using jumps.

New Riemannian geometry for Compound Gaussian distributions applied to efficient change detection.

Study Nash equilibrium in non-zero-sum game with Bermudan strategies.

In quantitative finance, it is often necessary to analyze the distribution of the sum of specific functions of observed values at discrete points of an underlying process. Examples include the probability density function, the hedging error, the Asian option, and statistical hypothesis testing. We propose a method to c…

Dimensionality reduction is one of the key issues in the design of effective machine learning methods for automatic induction. In this work, we introduce recursive maxima hunting (RMH) for variable selection in classification problems with functional data. In this context, variable selection techniques are especially a…

We introduce a recursive adaptive group lasso algorithm for real-time penalized least squares prediction that produces a time sequence of optimal sparse predictor coefficient vectors. At each time index the proposed algorithm computes an exact update of the optimal $\ell_{1,\infty}$-penalized recursive least squares (R…

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…

Worldsheet skein D-module for Hopf link conormal uniquely determines partition functions.

New spin on Hurwitz theory connects to Gromov-Witten theory and topological recursion.

The paper analyzes distances and volumes in lens spaces using recursion and formulas.

Majority bit estimation in noisy random recursive DAGs.

Continuous optimization is an important problem in many areas of AI, including vision, robotics, probabilistic inference, and machine learning. Unfortunately, most real-world optimization problems are nonconvex, causing standard convex techniques to find only local optima, even with extensions like random restarts and …

A new Bayesian method optimizes time-dependent expensive functions with lookahead.

The paper explores generalizations of Mirzakhani's recursion and computes volumes for physical gravity models.

A weight system is defined from the (multivariable) Conway potential function. We also show that it can be calculated recursively by using five axioms.

Stochastic discount factor (SDF) processes in dynamic economies admit a permanent-transitory decomposition in which the permanent component characterizes pricing over long investment horizons. This paper introduces an empirical framework to analyze the permanent-transitory decomposition of SDF processes. Specifically, …

New approach solves utility maximization problems using Delta family.

In this paper, we propose the discrete time Compound Beta-Binomial Risk Model with by-claims, delayed by-claims and randomized dividends. We then analyze the Gerber-Shiu function for the cases where the dividend threshold $d=0$ and $d>0$ under the assumption that the constant discount rate $ν\in (0,1)$. More specifical…

Using methods of math.DG/0304245 and [I.S.Krasil'shchik and P.H.M.Kersten, Symmetries and recursion operators for classical and supersymmetric differential equations, Kluwer, 2000], we accomplish an extensive study of the N=1 supersymmetric Korteweg-de Vries equation. The results include: a description of local and non…

Tab-TRM uses recursive model for insurance pricing on tabular data.

This paper simplifies complex game dynamics by using a recursive representation.

In this paper we introduce and solve a class of optimal stopping problems of recursive type. In particular, the stopping payoff depends directly on the value function of the problem itself. In a multi-dimensional Markovian setting we show that the problem is well posed, in the sense that the value is indeed the unique …

New recursion formula for non-orientable surfaces resolves divergences.

Study risk-sensitive reinforcement learning with entropic risk measures and generative models.

New method for estimating treatment effects without complex propensity models.