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We derive upper bounds on the tail conditional expectation of binomial and Poisson random variables. Those upper bounds are subsequently employed to the problem of obtaining non-asymptotic lower bounds on the probability that the…

Probability · Mathematics 2017-12-07 Christos Pelekis

Anytime approximation algorithms that compute the probabilities of queries over probabilistic databases can be of great use to statistical learning tasks. Those approaches have been based so far on either (i) sampling or (ii)…

Databases · Computer Science 2018-07-04 Maarten Van den Heuvel , Floris Geerts , Wolfgang Gatterbauer , Martin Theobald

Since many real-world problems arising in the fields of compiler optimisation, automated software engineering, formal proof systems, and so forth are equivalent to the Halting Problem--the most notorious undecidable problem--there is a…

Information Theory · Computer Science 2007-07-13 Cristian S. Calude , Michael A. Stay

Termination is one of the basic liveness properties, and we study the termination problem for probabilistic programs with real-valued variables. Previous works focused on the qualitative problem that asks whether an input program terminates…

Programming Languages · Computer Science 2016-11-17 Krishnendu Chatterjee , Petr Novotný , Đorđe Žikelić

Evaluating joint probabilities of potential outcomes and observed variables, and their linear combinations, is a fundamental challenge in causal inference. This paper addresses the bounding and identification of these probabilities in…

Machine Learning · Statistics 2026-02-24 Naoya Hashimoto , Yuta Kawakami , Jin Tian

We propose upper and lower bounds on the maximum success probability for discriminating given quantum states. The proposed upper bound is obtained from a suboptimal solution to the dual problem of the corresponding optimal state…

Quantum Physics · Physics 2018-01-12 Kenji Nakahira , Tsuyoshi Sasaki Usuda , Kentaro Kato

Probabilistic separation logic offers an approach to reasoning about imperative probabilistic programs in which a separating conjunction is used as a mechanism for expressing independence properties. Crucial to the effectiveness of the…

Logic in Computer Science · Computer Science 2026-03-03 Janez Ignacij Jereb , Alex Simpson

The DUCK-calculus presented here is a recent approach to cope with probabilistic uncertainty in a sound and efficient way. Uncertain rules with bounds for probabilities and explicit conditional independences can be maintained incrementally.…

Artificial Intelligence · Computer Science 2013-03-25 Helmut Thone , Ulrich Guntzer , Werner Kiessling

Bounds on quantum probabilities and expectation values are derived for experimental setups associated with Bell-type inequalities. In analogy to the classical bounds, the quantum limits are experimentally testable and therefore serve as…

Quantum Physics · Physics 2007-05-23 Stefan Filipp , Karl Svozil

Existing complexity bounds for point-based POMDP value iteration algorithms focus either on the curse of dimensionality or the curse of history. We derive a new bound that relies on both and uses the concept of discounted reachability; our…

Artificial Intelligence · Computer Science 2012-07-09 Trey Smith , Reid Simmons

We prove an elementary yet useful inequality bounding the maximal value of certain linear programs. This leads directly to a bound on the martingale difference for arbitrarily dependent random variables, providing a generalization of some…

Functional Analysis · Mathematics 2007-05-23 Leonid Kontorovich

We consider the biased random walk on a tree constructed from the set of finite self-avoiding walks on a lattice, and use it to construct probability measures on infinite self-avoiding walks. The limit measure (if it exists) obtained when…

Probability · Mathematics 2019-12-25 Vincent Beffara , Cong Bang Huynh

We show that universal positive almost sure termination (UPAST) is decidable for a class of simple randomized programs, i.e., it is decidable whether the expected runtime of such a program is finite for all inputs. Our class contains all…

Logic in Computer Science · Computer Science 2025-07-02 Éléanore Meyer , Jürgen Giesl

Computing reachability probabilities is a fundamental problem in the analysis of probabilistic programs. This paper aims at a comprehensive and comparative account on various martingale-based methods for over- and under-approximating…

Programming Languages · Computer Science 2018-11-16 Toru Takisaka , Yuichiro Oyabu , Natsuki Urabe , Ichiro Hasuo

Information divergence functions play a critical role in statistics and information theory. In this paper we show that a non-parametric f-divergence measure can be used to provide improved bounds on the minimum binary classification…

Information Theory · Computer Science 2015-02-11 Visar Berisha , Alan Wisler , Alfred O. Hero , Andreas Spanias

We consider a Branching Random Walk on $\R$ whose step size decreases by a fixed factor, $0<b<1$, with each turn. This process generates a random probability measure on $\R$, that is, the limit of uniform distribution among the $2^n$…

Probability · Mathematics 2011-07-20 Itai Benjamini , Ori Gurel-Gurevich , Boris Solomyak

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

Bounded model checking of pointer programs is a debugging technique for programs that manipulate dynamically allocated pointer structures on the heap. It is based on the following four observations. First, error conditions like dereference…

Logic in Computer Science · Computer Science 2016-03-02 Witold Charatonik , Piotr Witkowski

The question of what can be computed, and how efficiently, are at the core of computer science. Not surprisingly, in distributed systems and networking research, an equally fundamental question is what can be computed in a…

Distributed, Parallel, and Cluster Computing · Computer Science 2016-04-01 Fabian Kuhn , Thomas Moscibroda , Roger Wattenhofer

This work proposes a view of probability as a relative measure rather than an absolute one. To demonstrate this concept, we focus on finite outcome spaces and develop three fundamental axioms that establish requirements for relative…

Machine Learning · Statistics 2023-05-30 Max Sklar