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There has been a great deal of recent interest in methods for performing lifted inference; however, most of this work assumes that the first-order model is given as input to the system. Here, we describe lifted inference algorithms that…

Artificial Intelligence · Computer Science 2012-05-14 Prithviraj Sen , Amol Deshpande , Lise Getoor

Computing the probability of a formula given the probabilities or weights associated with other formulas is a natural extension of logical inference to the probabilistic setting. Surprisingly, this problem has received little attention in…

Artificial Intelligence · Computer Science 2012-03-19 Vibhav Gogate , Pedro Domingos

Computer Algebra systems are widely spread because of some of their remarkable features such as their ease of use and performance. Nonetheless, this focus on performance sometimes leads to unwanted consequences: algorithms and computations…

Logic in Computer Science · Computer Science 2014-01-27 Jesús Aransay , Jose Divasón

This piece of work presents a meaningful example for the advantages of using bitwise operations for creating effective algorithms in programming. A task connected with mathematical modeling in weaving industry is examined and computed.

Other Computer Science · Computer Science 2012-01-09 Krasimir Yankov Yordzhev

Computer Algebra Systems (e.g. Maple) are used in research, education, and industrial settings. One of their key functionalities is symbolic integration, where there are many sub-algorithms to choose from that can affect the form of the…

Machine Learning · Computer Science 2024-04-24 Rashid Barket , Matthew England , Jürgen Gerhard

One challenge in fact checking is the ability to improve the transparency of the decision. We present a fact checking method that uses reference information in knowledge graphs (KGs) to assess claims and explain its decisions. KGs contain a…

Databases · Computer Science 2019-06-24 Naser Ahmadi , Joohyung Lee , Paolo Papotti , Mohammed Saeed

Discrete mixture models provide a well-known basis for effective clustering algorithms, although technical challenges have limited their scope. In the context of gene-expression data analysis, a model is presented that mixes over a finite…

Methodology · Statistics 2012-11-12 Michael A. Newton , Lisa M. Chung

Ensembling methods are well known for improving prediction accuracy. However, they are limited in the sense that they cannot discriminate among component models effectively. In this paper, we propose stacking with auxiliary features that…

Computation and Language · Computer Science 2016-05-30 Nazneen Fatema Rajani , Raymond J. Mooney

We deliver a call to arms for probabilistic numerical methods: algorithms for numerical tasks, including linear algebra, integration, optimization and solving differential equations, that return uncertainties in their calculations. Such…

Numerical Analysis · Mathematics 2016-02-17 Philipp Hennig , Michael A Osborne , Mark Girolami

Metacognitive knowledge refers to humans' intuitive knowledge of their own thinking and reasoning processes. Today's best LLMs clearly possess some reasoning processes. The paper gives evidence that they also have metacognitive knowledge,…

Many algorithms and applications involve repeatedly solving variations of the same inference problem; for example we may want to introduce new evidence to the model or perform updates to conditional dependencies. The goal of adaptive…

Data Structures and Algorithms · Computer Science 2012-06-18 Umut A. Acar , Alexander T. Ihler , Ramgopal Mettu , Ozgur Sumer

This article describes the implementation in the software package NumGfun of classical algorithms that operate on solutions of linear differential equations or recurrence relations with polynomial coefficients, including what seems to be…

Symbolic Computation · Computer Science 2010-06-01 Marc Mezzarobba

Probabilistic programming makes it easy to represent a probabilistic model as a program. Building an individual model, however, is only one step of probabilistic modeling. The broader challenge of probabilistic modeling is in understanding…

Programming Languages · Computer Science 2022-08-15 Ryan Bernstein

The gradient scheme framework is based on a small number of properties and encompasses a large number of numerical methods for diffusion models. We recall these properties and develop some new generic tools associated with the gradient…

Numerical Analysis · Mathematics 2015-11-10 Jerome Droniou , Robert Eymard , Raphaele Herbin

We describe various errors in the mathematical literature, and consider how some of them might have been avoided, or at least detected at an earlier stage, using tools such as Maple or Sage. Our examples are drawn from three broad…

Number Theory · Mathematics 2021-10-14 Richard P. Brent

Geospatial sciences include a wide range of applications, from environmental monitoring transportation to infrastructure planning, as well as location-based analysis and services. Graph theory algorithms in mathematics have emerged as…

Machine Learning · Computer Science 2023-10-10 Surajit Ghosh , Archita Mallick , Anuva Chowdhury , Kounik De Sarkar

An autonomous variational inference algorithm for arbitrary graphical models requires the ability to optimize variational approximations over the space of model parameters as well as over the choice of tractable families used for the…

Machine Learning · Computer Science 2012-07-19 Eric P. Xing , Michael I. Jordan , Stuart Russell

Analogy is one of the core capacities of human cognition; when faced with new situations, we often transfer prior experience from other domains. Most work on computational analogy relies heavily on complex, manually crafted input. In this…

Computation and Language · Computer Science 2023-11-06 Shahar Jacob , Chen Shani , Dafna Shahaf

The Hastings algorithm is a key tool in computational science. While mathematically justified by detailed balance, it can be conceptually difficult to grasp. Here, we present two complementary and intuitive ways to derive and understand the…

Computation · Statistics 2019-08-07 David D. L. Minh , Do Le , Minh

In the spirit of "multi-culturalism", we use four kinds of computations: simulation, numeric, symbolic, and "conceptual" to explore some "games of pure chance" inspired by children board games like "Snakes and Ladders" (aka as "Chutes and…

Combinatorics · Mathematics 2019-09-26 Thotsaporn "Aek" Thanatipanonda , Doron Zeilberger