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In this paper we develop proximal methods for statistical learning. Proximal point algorithms are useful in statistics and machine learning for obtaining optimization solutions for composite functions. Our approach exploits closed-form…

Machine Learning · Statistics 2015-06-02 Nicholas G. Polson , James G. Scott , Brandon T. Willard

We study a posterior sampling approach to efficient exploration in constrained reinforcement learning. Alternatively to existing algorithms, we propose two simple algorithms that are more efficient statistically, simpler to implement and…

Machine Learning · Computer Science 2022-09-09 Danil Provodin , Pratik Gajane , Mykola Pechenizkiy , Maurits Kaptein

We give a new algorithm to simplify a given triangulation with respect to a given curve. The simplification uses flips together with powers of Dehn twists in order to complete in polynomial time in the bit-size of the curve.

Geometric Topology · Mathematics 2016-04-25 Mark C. Bell

Many multi-loop calculations make use of integration by parts relations to reduce the large number of complicated Feynman integrals that arise in such calculations to a simpler basis of master integrals. Recently, Gluza, Kajda, and Kosower…

High Energy Physics - Phenomenology · Physics 2015-06-03 Robert M. Schabinger

We present, in a pedagogical style, many instances of reduction procedures appearing in a variety of physical situations, both classical and quantum. We concentrate on the essential aspects of any reduction procedure, both in the algebraic…

Mathematical Physics · Physics 2009-05-29 J. F. Carinena , J. Clemente-Gallardo , G. Marmo

Submodular functions are a special class of set functions which naturally model the notion of representativeness, diversity, coverage etc. and have been shown to be computationally very efficient. A lot of past work has applied submodular…

Machine Learning · Computer Science 2022-02-24 Vishal Kaushal , Ganesh Ramakrishnan , Rishabh Iyer

Abstraction and realization are bilateral processes that are key in deriving intelligence and creativity. In many domains, the two processes are approached through rules: high-level principles that reveal invariances within similar yet…

Machine Learning · Computer Science 2018-03-13 Haizi Yu , Tianxi Li , Lav R. Varshney

Current approaches for text summarization are predominantly automatic, with rather limited space for human intervention and control over the process. In this paper, we introduce SummHelper, a 2-phase summarization assistant designed to…

Computation and Language · Computer Science 2023-10-17 Aviv Slobodkin , Niv Nachum , Shmuel Amar , Ori Shapira , Ido Dagan

Abduction is a fundamental and important form of non-monotonic reasoning. Given a knowledge base explaining how the world behaves it aims at finding an explanation for some observed manifestation. In this paper we focus on propositional…

Computational Complexity · Computer Science 2010-06-29 Nadia Creignou , Johannes Schmidt , Michael Thomas

We develop the technique of reduced word manipulation to give a range of results concerning reduced words and permutations more generally. We prove a broad connection between pattern containment and reduced words, which specializes to our…

Combinatorics · Mathematics 2017-03-24 Bridget Eileen Tenner

One of the major problems with text simplification is the lack of high-quality data. The sources of simplification datasets are limited to Wikipedia and Newsela, restricting further development of this field. In this paper, we analyzed the…

Computation and Language · Computer Science 2023-02-15 Renliang Sun , Zhixian Yang , Xiaojun Wan

A fully adaptive methodology is developed for reducing the complexity of large dissipative systems. This represents a significant step towards extracting essential physical knowledge from complex systems, by addressing the challenging…

Statistical Mechanics · Physics 2025-10-01 Eliodoro Chiavazzo , Ilya Karlin

General purpose correct-by-construction synthesis methods are limited to systems with low dimensionality or simple specifications. In this work we consider highly symmetrical counting problems and exploit the symmetry to synthesize provably…

Systems and Control · Computer Science 2018-07-11 Petter Nilsson , Necmiye Ozay

A notion of probabilistic lambda-calculus usually comes with a prescribed reduction strategy, typically call-by-name or call-by-value, as the calculus is non-confluent and these strategies yield different results. This is a break with one…

Logic in Computer Science · Computer Science 2020-02-21 Ugo Dal Lago , Giulio Guerrieri , Willem Heijltjes

Convex polyhedral abstractions of logic programs have been found very useful in deriving numeric relationships between program arguments in order to prove program properties and in other areas such as termination and complexity analysis. We…

Programming Languages · Computer Science 2007-12-18 Kim Henriksen , Gourinath Banda , John Gallagher

Detectability of failures of linear programming (LP) decoding and its potential for improvement by adding new constraints motivate the use of an adaptive approach in selecting the constraints for the LP problem. In this paper, we make a…

Information Theory · Computer Science 2007-07-13 Mohammad H. Taghavi N. , Paul H. Siegel

We address the problem of counting the number of strings in a collection where a given pattern appears, which has applications in information retrieval and data mining. Existing solutions are in a theoretical stage. We implement these…

Data Structures and Algorithms · Computer Science 2015-10-02 Travis Gagie , Aleksi Hartikainen , Juha Kärkkäinen , Gonzalo Navarro , Simon J. Puglisi , Jouni Sirén

The paper investigates the problem of performing correlation analysis when the number of observations is very large. In such a case, it is often necessary to combine the random observations to achieve dimensionality reduction of the…

Information Theory · Computer Science 2020-10-19 Pavel Loskot

Submodular set-functions have many applications in combinatorial optimization, as they can be minimized and approximately maximized in polynomial time. A key element in many of the algorithms and analyses is the possibility of extending the…

Machine Learning · Computer Science 2016-02-24 Francis Bach

Selective rationalization has become a common mechanism to ensure that predictive models reveal how they use any available features. The selection may be soft or hard, and identifies a subset of input features relevant for prediction. The…

Computation and Language · Computer Science 2019-12-17 Mo Yu , Shiyu Chang , Yang Zhang , Tommi S. Jaakkola