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In the context of online interactive machine learning with combinatorial objectives, we extend purely submodular prior work to more general non-submodular objectives. This includes: (1) those that are additively decomposable into a sum of…

Machine Learning · Computer Science 2024-05-14 Adhyyan Narang , Omid Sadeghi , Lillian J Ratliff , Maryam Fazel , Jeff Bilmes

Let $p$ be a prime number, $\Bbbk$ a field of characteristic $p$ and $G$ a finite $p$-group acting on a standard graded polynomial ring $S = \Bbbk[x_1, \ldots, x_n]$ as degree-preserving $\Bbbk$-algebra automorphisms. Assume that $G$ is…

Commutative Algebra · Mathematics 2025-02-25 Manoj Kummini , Mandira Mondal

Recent results of Kahle and Miller give a method of constructing primary decompositions of binomial ideals by first constructing "mesoprimary decompositions" determined by their underlying monoid congruences. These mesoprimary…

Commutative Algebra · Mathematics 2018-08-15 Christopher O'Neill

We study the problem of preconditioning in sequential prediction. From the theoretical lens of linear dynamical systems, we show that convolving the target sequence corresponds to applying a polynomial to the hidden transition matrix.…

Machine Learning · Computer Science 2026-01-29 Annie Marsden , Elad Hazan

We propose employing a high-dimensional generalized method of moments (GMM) estimator, regularized for dimension reduction and subsequently debiased to correct for shrinkage bias (referred to as a debiased-regularized estimator), for…

Econometrics · Economics 2025-07-03 Victor Chernozhukov , Chen Huang , Weining Wang

We give an elementary proof of the celebrated Bichteler-Dellacherie Theorem which states that the class of stochastic processes $S$ allowing for a useful integration theory consists precisely of those processes which can be written in the…

Probability · Mathematics 2015-03-17 Mathias Beiglböck , Walter Schachermayer , Bezirgen Veliyev

We investigate aspects of semimartingale decompositions, approximation and the martingale representation for multidimensional correlated Markov processes. A new interpretation of the dependence among processes is given using the martingale…

Statistics Theory · Mathematics 2015-02-24 Antonio Dalessandro , Gareth W. Peters

In this paper, we extend the G-expectation theory to infinite dimensions. Such notions as a covariation set of G-normal distributed random variables, viscosity solution, a stochastic integral driven by G-Brownian motion are introduced and…

Probability · Mathematics 2013-06-25 Anton Ibragimov

In this paper we study a family of nonlinear (conditional) expectations that can be understood as a continuous semimartingale with uncertain local characteristics. Here, the differential characteristics are prescribed by a set-valued…

Probability · Mathematics 2023-08-04 David Criens , Lars Niemann

In this paper, we study the discrete-time approximation schemes for a class of backward stochastic differential equations driven by $G$-Brownian motion ($G$-BSDEs) which corresponds to the hedging pricing of European contingent claims. By…

Numerical Analysis · Mathematics 2024-09-24 Lianzi Jiang , Mingshang Hu

Confidence sequences, anytime p-values (called p-processes in this paper), and e-processes all enable sequential inference for composite and nonparametric classes of distributions at arbitrary stopping times. Examining the literature, one…

Statistics Theory · Mathematics 2022-11-08 Aaditya Ramdas , Johannes Ruf , Martin Larsson , Wouter Koolen

We construct a class of discontinuous superprocesses with dependent spatial motion and general branching mechanism. The process arises as the weak limit of critical interacting-branching particle systems where the spatial motions of the…

Probability · Mathematics 2008-07-02 Hui He

In this paper we extend the definition of time conditional G-expectations $\mathbb{\hat{E}}_{t}[\cdot]$ to a larger domain on which the dynamical consistency still holds. In fact we can consistently define, by taking the limit, the time…

Probability · Mathematics 2013-09-17 Mingshang Hu , Shige Peng

The g-formula can be used to estimate causal effects of sustained treatment strategies using observational data under the identifying assumptions of consistency, positivity, and exchangeability. The non-iterative conditional expectation…

Machine Learning · Statistics 2024-10-30 Sophia M Rein , Jing Li , Miguel Hernan , Andrew Beam

A new general decomposition theory inspired from modular graph decomposition is presented. This helps unifying modular decomposition on different structures, including (but not restricted to) graphs. Moreover, even in the case of graphs,…

Data Structures and Algorithms · Computer Science 2007-11-20 Binh-Minh Bui-Xuan , Michel Habib , Vincent Limouzy , Fabien De Montgolfier

We propose an automated deduction method which allows us to produce proofs close to the human intuition and practice. This method is based on tableaux, which generate more natural proofs than similar methods relying on clausal forms, and…

Logic in Computer Science · Computer Science 2015-01-07 David Delahaye , Mélanie Jacquel

The computation of triangular decompositions are based on two fundamental operations: polynomial GCDs modulo regular chains and regularity test modulo saturated ideals. We propose new algorithms for these core operations relying on modular…

Symbolic Computation · Computer Science 2009-07-25 Xin Li , Marc Moreno Maza , Wei Pan

In a recent work \cite{BG}, given a collection of continuous semimartingales, authors derive a semimartingale decomposition from the corresponding ranked processes in the case that the ranked processes can meet more than two original…

Probability · Mathematics 2008-12-02 Raouf Ghomrasni , Olivier Menoukeu Pamen

We explicitly construct the supermartingale version of the Fr{\'e}chet-Hoeffding coupling in the setting with infinitely many marginal constraints. This extends the results of Henry-Labordere et al. obtained in the martingale setting. Our…

Probability · Mathematics 2023-01-02 Erhan Bayraktar , Shuoqing Deng , Dominykas Norgilas

Based on the classical probability, the stability criteria for stochastic differential delay equations (SDDEs) where their coefficients are either linear or nonlinear but bounded by linear functions have been investigated intensively.…

Optimization and Control · Mathematics 2020-04-29 Chen Fei , Weiyin Fei , Xuerong Mao , Litan Yan