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This paper presents a sharp approximation of the density of long runs of a random walk conditioned on its end value or by an average of a functions of its summands as their number tends to infinity. The conditioning event is of moderate or…

Probability · Mathematics 2011-06-14 Michel Broniatowski , Virgile Caron

The undecidability of basic decision problems for general FIFO machines such as reachability and unboundedness is well-known. In this paper, we provide an underapproximation for the general model by considering only runs that are…

Logic in Computer Science · Computer Science 2023-06-22 Benedikt Bollig , Alain Finkel , Amrita Suresh

The aim of this paper is first to give necessary and sufficient condition of existence (of free boundaries) for both Laplacian and bi-Laplacian operators in the case where the overdetermined condition is not constant. second, by using some…

Analysis of PDEs · Mathematics 2023-04-11 Mohammed Barkatou

Off-policy evaluation of sequential decision policies from observational data is necessary in applications of batch reinforcement learning such as education and healthcare. In such settings, however, unobserved variables confound observed…

Machine Learning · Computer Science 2020-07-14 Nathan Kallus , Angela Zhou

Randomized higher-order computation can be seen as being captured by a lambda calculus endowed with a single algebraic operation, namely a construct for binary probabilistic choice. What matters about such computations is the probability of…

Logic in Computer Science · Computer Science 2020-12-24 Ugo Dal Lago , Claudia Faggian , Simona Ronchi Della Rocca

The overarching goal of this paper is to derive excess risk bounds for learning from exp-concave loss functions in passive and sequential learning settings. Exp-concave loss functions encompass several fundamental problems in machine…

Machine Learning · Computer Science 2014-02-11 Mehrdad Mahdavi , Rong Jin

We develop a new technique for studying the boundary limiting behavior of a holomorphic function on a domain $\Omega$ -- both in one and several complex variables. The approach involves two new localized maximal functions. As a result of…

Complex Variables · Mathematics 2007-05-23 Steven G. Krantz

Logics closed under classes of substitutions broader than class of uniform substitutions are known as hyperformal logics. This paper extends known results about hyperformal logics in two ways. First: we examine a very powerful form of…

Logic · Mathematics 2026-04-28 Shay Allen Logan , Blane Worley

We describe an algorithm that takes as input a complex sequence $(u_n)$ given by a linear recurrence relation with polynomial coefficients along with initial values, and outputs a simple explicit upper bound $(v_n)$ such that $|u_n| \leq…

Symbolic Computation · Computer Science 2013-06-19 Marc Mezzarobba , Bruno Salvy

We study first-order logic (FO) over the structure consisting of finite words over some alphabet $A$, together with the (non-contiguous) subword ordering. In terms of decidability of quantifier alternation fragments, this logic is…

Logic in Computer Science · Computer Science 2024-02-14 Pascal Baumann , Moses Ganardi , Ramanathan S. Thinniyam , Georg Zetzsche

The need for an ontological layer on top of data, associated with advanced reasoning mechanisms able to exploit the semantics encoded in ontologies, has been acknowledged both in the database and knowledge representation communities. We…

Artificial Intelligence · Computer Science 2014-12-16 Sebastian Rudolph , Michaël Thomazo , Jean-François Baget , Marie-Laure Mugnier

We investigate a subclass of well-structured transition systems (WSTS), the bounded---in the sense of Ginsburg and Spanier (Trans. AMS 1964)---complete deterministic ones, which we claim provide an adequate basis for the study of forward…

Logic in Computer Science · Computer Science 2016-03-07 Pierre Chambart , Alain Finkel , Sylvain Schmitz

A run of all failures, a run of all successes, or complete separation in a logistic regression each tempts the analyst to declare a probability of exactly zero or one. The central message of this paper is that all three phenomena share a…

Methodology · Statistics 2026-05-05 Yuan-chin Ivan Chang

We establish empirical risk minimization principles for active learning by deriving a family of upper bounds on the generalization error. Aligning with empirical observations, the bounds suggest that superior query algorithms can be…

Machine Learning · Statistics 2024-09-17 Vincent Menden , Yahya Saleh , Armin Iske

When does society eventually learn the truth, or take the correct action, via observational learning? In a general model of sequential learning over social networks, we identify a simple condition for learning dubbed excludability.…

Theoretical Economics · Economics 2024-04-05 Navin Kartik , SangMok Lee , Tianhao Liu , Daniel Rappoport

There are many types of automata and grammar models that have been studied in the literature, and for these models, it is common to determine whether certain problems are decidable. One problem that has been difficult to answer throughout…

Formal Languages and Automata Theory · Computer Science 2024-05-20 Oscar H. Ibarra , Ian McQuillan

For two causal structures with the same set of visible variables, one is said to observationally dominate the other if the set of distributions over the visible variables realizable by the first contains the set of distributions over the…

Machine Learning · Statistics 2025-02-24 Marina Maciel Ansanelli , Elie Wolfe , Robert W. Spekkens

In this note, we provide complexity characterizations of model checking multi-pushdown systems. Multi-pushdown systems model recursive concurrent programs in which any sequential process has a finite control. We consider three standard…

Logic in Computer Science · Computer Science 2012-12-10 Kshitij Bansal , Stéphane Demri

We consider the semiconjugate factorization and reduction of order for non-autonomous, nonlinear, higher order difference equations containing linear arguments. These equations have appeared in several mathematical models in biology and…

Dynamical Systems · Mathematics 2014-01-16 H. Sedaghat

We introduce a class of learning problems where the agent is presented with a series of tasks. Intuitively, if there is relation among those tasks, then the information gained during execution of one task has value for the execution of…

Machine Learning · Computer Science 2012-09-06 Christos Dimitrakakis
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