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In comparative studies, such as in causal inference and clinical trials, balancing important covariates is often one of the most important concerns for both efficient and credible comparison. However, chance imbalance still exists in many…

Methodology · Statistics 2018-07-30 Yichen Qin , Yang Li , Wei Ma , Feifang Hu

Rejection sampling is a technique for sampling from difficult distributions. However, its use is limited due to a high rejection rate. Common adaptive rejection sampling methods either work only for very specific distributions or without…

Machine Learning · Statistics 2026-04-27 Akram Erraqabi , Michal Valko , Alexandra Carpentier , Odalric-Ambrym Maillard

We introduce Joint Probability Trees (JPT), a novel approach that makes learning of and reasoning about joint probability distributions tractable for practical applications. JPTs support both symbolic and subsymbolic variables in a single…

Machine Learning · Computer Science 2023-02-15 Daniel Nyga , Mareike Picklum , Tom Schierenbeck , Michael Beetz

The probabilistic serial (PS) rule is one of the most prominent randomized rules for the assignment problem. It is well-known for its superior fairness and welfare properties. However, PS is not immune to manipulative behaviour by the…

Computer Science and Game Theory · Computer Science 2015-01-28 Haris Aziz , Serge Gaspers , Simon Mackenzie , Nicholas Mattei , Nina Narodytska , Toby Walsh

Consider a randomized algorithm that draws samples exactly from a distribution using recursion. Such an algorithm is called a perfect simulation, and here a variety of methods for building this type of algorithm are shown to derive from the…

Data Structures and Algorithms · Computer Science 2019-07-17 Mark Huber

Social dilemmas concern a natural conflict between cooperation and self interests among individuals in large populations. The emergence of cooperation and its maintenance is the key for the understanding of fundamental concepts about the…

Physics and Society · Physics 2016-10-26 Pablo A. Valverde , Roberto da Silva , Eduardo V. Stock

We propose a permutation-invariant loss function designed for the neural networks reconstructing a set of elements without considering the order within its vector representation. Unlike popular approaches for encoding and decoding a set,…

Machine Learning · Computer Science 2018-12-06 Masataro Asai

Negation is an important perspective of knowledge representation. Existing negation methods are mainly applied in probability theory, evidence theory and complex evidence theory. As a generalization of evidence theory, random permutation…

Artificial Intelligence · Computer Science 2024-03-14 Yongchuan Tang , Rongfei Li

Permutation is the different arrangements that can be made with a given number of things taking some or all of them at a time. The notation P(n,r) is used to denote the number of permutations of n things taken r at a time. Permutation is…

Data Structures and Algorithms · Computer Science 2012-05-15 Youssef Bassil

While machine-learning models are flourishing and transforming many aspects of everyday life, the inability of humans to understand complex models poses difficulties for these models to be fully trusted and embraced. Thus, interpretability…

Artificial Intelligence · Computer Science 2020-06-18 Guangyi Zhang , Aristides Gionis

The study of pinnacle sets has been a recent area of interest in combinatorics. Given a permutation, its pinnacle set is the set of all values larger than the values on either side of it. Largely inspired by conjectures posed by Davis,…

Combinatorics · Mathematics 2021-11-17 Quinn Minnich

Mixture models have received considerable attention recently and Newton [Sankhy\={a} Ser. A 64 (2002) 306--322] proposed a fast recursive algorithm for estimating a mixing distribution. We prove almost sure consistency of this recursive…

Statistics Theory · Mathematics 2009-08-25 Surya T. Tokdar , Ryan Martin , Jayanta K. Ghosh

Repetitive Scenario Design (RSD) is a randomized approach to robust design based on iterating two phases: a standard scenario design phase that uses $N$ scenarios (design samples), followed by randomized feasibility phase that uses $N_o$…

Systems and Control · Computer Science 2016-02-12 Giuseppe C. Calafiore

Probabilistic sampling methods have become very popular to solve single-shot path planning problems. Rapidly-exploring Random Trees (RRTs) in particular have been shown to be very efficient in solving high dimensional problems. Even though…

Artificial Intelligence · Computer Science 2009-12-03 Nicolas A. Barriga , Mauricio Araya-López , Mauricio Solar

Resampling techniques are widely used in statistical inference and ensemble learning, in which estimators' statistical properties are essential. However, existing methods are computationally demanding, because repetitions of…

Machine Learning · Statistics 2019-05-24 Takashi Takahashi , Yoshiyuki Kabashima

In finite probability theory, events are subsets of the outcome set. Subsets can be represented by 1-dimensional column vectors. By extending the representation of events to two dimensional matrices, we can introduce "superposition events."…

Quantum Physics · Physics 2020-06-18 David Ellerman

Sign-Perturbed Sum (SPS) is a powerful finite-sample system identification algorithm which can construct confidence regions for the true data generating system with exact coverage probabilities, for any finite sample size. SPS was developed…

Machine Learning · Statistics 2024-01-30 Szabolcs Szentpéteri , Balázs Csanád Csáji

Permutation tests are a distribution free way of performing hypothesis tests. These tests rely on the condition that the observed data are exchangeable among the groups being tested under the null hypothesis. This assumption is easily…

Methodology · Statistics 2017-12-14 Daniell Toth

Binary search trees (BST) are a popular type of data structure when dealing with ordered data. Indeed, they enable one to access and modify data efficiently, with their height corresponding to the worst retrieval time. From a probabilistic…

Probability · Mathematics 2025-01-28 Benoît Corsini , Victor Dubach , Valentin Féray

Motion planning problems have been studied by both the robotics and the controls research communities for a long time, and many algorithms have been developed for their solution. Among them, incremental sampling-based motion planning…

Robotics · Computer Science 2012-05-01 Oktay Arslan , Panagiotis Tsiotras