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Evaluating higher-order functional programs through abstract machines inspired by the geometry of the interaction is known to induce $\textit{space}$ efficiencies, the price being $\textit{time}$ performances often poorer than those…

Programming Languages · Computer Science 2020-10-27 Beniamino Accattoli , Ugo Dal Lago , Gabriele Vanoni

It is well-known that proper scaling can increase the efficiency of computational problems. In this paper we define and show that a balancing technique can substantially improve the computational efficiency of optimal control algorithms. We…

Optimization and Control · Mathematics 2018-10-29 I. M. Ross , Q. Gong , M. Karpenko , R. J. Proulx

Improperly efficient solutions in the sense of Geoffrion in linear fractional vector optimization problems with unbounded constraint sets are studied in this paper. We give two sets of conditions which assure that all the efficient…

Optimization and Control · Mathematics 2020-08-04 N. T. T. Huong , N. D. Yen

Machine learning assumes a pivotal role in our data-driven world. The increasing scale of models and datasets necessitates quick and reliable algorithms for model training. This dissertation investigates adaptivity in machine learning…

Machine Learning · Computer Science 2023-11-20 Slavomír Hanzely

In this paper, we consider distributed optimization problems over a multi-agent network, where each agent can only partially evaluate the objective function, and it is allowed to exchange messages with its immediate neighbors. Differently…

Optimization and Control · Mathematics 2019-02-22 Davood Hajinezhad , Mingyi Hong , Alfredo Garcia

A simple procedure to estimate O(alpha_s^3) and O(alpha_s^4) corrections to mass-dependent observables is conjectured. The method is tested in a number of cases where the O(alpha_s^3) contribution is exactly known, and reasonable agreement…

High Energy Physics - Phenomenology · Physics 2009-10-30 K. G. Chetyrkin , B. A. Kniehl , A. Sirlin

In this paper we analyze several new methods for solving nonconvex optimization problems with the objective function formed as a sum of two terms: one is nonconvex and smooth, and another is convex but simple and its structure is known.…

Optimization and Control · Mathematics 2014-06-25 A. Patrascu , I. Necoara

We show that when time-reversible symplectic algorithms are used to solve periodic motions, the energy error after one period is generally two orders higher than that of the algorithm. By use of correctable algorithms, we show that the…

Mathematical Physics · Physics 2009-11-10 S. R. Scuro , S. A. Chin

Division algorithms have been developed to reduce latency and to improve the efficiency of the processors. Floating point division is considered as a high latency operation. This papers looks into one such division algorithm, examines the…

Hardware Architecture · Computer Science 2019-09-24 Taposh Dutta Roy

In this paper we theoretically show that interior-point methods based on self-concordant barriers possess favorable global complexity beyond their standard application area of convex optimization. To do that we propose first- and…

Optimization and Control · Mathematics 2024-04-30 Pavel Dvurechensky , Mathias Staudigl

The exponential ordering is exploited in the context of non-auto\-no\-mous delay systems, inducing monotone skew-product semiflows under less restrictive conditions than usual. Some dynamical concepts linked to the order, such as…

Dynamical Systems · Mathematics 2022-12-09 Sylvia Novo , Rafael Obaya , Ana M. Sanz , Victor M. Villarragut

In distributional or average-case analysis, the goal is to design an algorithm with good-on-average performance with respect to a specific probability distribution. Distributional analysis can be useful for the study of general-purpose…

Data Structures and Algorithms · Computer Science 2020-07-28 Tim Roughgarden

In this paper, we examine the concept of the predict and optimise problem with specific reference to the third Technical Challenge of the IEEE Computational Intelligence Society. In this competition, entrants were asked to forecast building…

Machine Learning · Computer Science 2022-11-28 Mahdi Abolghasemi , Richard Bean

This paper introduces the first theoretical framework for quantifying the efficiency and performance gain opportunity size of adaptive inference algorithms. We provide new approximate and exact bounds for the achievable efficiency and…

Machine Learning · Computer Science 2024-02-08 Soheil Hor , Ying Qian , Mert Pilanci , Amin Arbabian

State-of-the-art methods in convex and non-convex optimization employ higher-order derivative information, either implicitly or explicitly. We explore the limitations of higher-order optimization and prove that even for convex optimization,…

Optimization and Control · Mathematics 2017-10-31 Naman Agarwal , Elad Hazan

Operator-splitting methods are widely used to solve differential equations, especially those that arise from multi-scale or multi-physics models, because a monolithic (single-method) approach may be inefficient or even infeasible. The most…

Numerical Analysis · Mathematics 2025-01-07 Siqi Wei , Victoria Guenter , Raymond J. Spiteri

In order to improve precision and efficiency sharing analysis should track both freeness and linearity. The abstract unification algorithms for these combined domains are suboptimal, hence there is scope for improving precision. This paper…

Programming Languages · Computer Science 2007-05-23 Jacob M. Howe , Andy King

In this paper, we resolve the ever-present confusion over the QUICK scheme: it is a second-order scheme or a third-order scheme. The QUICK scheme, as proposed in the original reference [B. P. Leonard, Comput. Methods. Appl. Mech. Eng., 19,…

Numerical Analysis · Mathematics 2021-04-06 Hiroaki Nishikawa

Using (a,b)-trees as an example, we show how to perform a parallel split with logarithmic latency and parallel join, bulk updates, intersection, union (or merge), and (symmetric) set difference with logarithmic latency and with information…

Data Structures and Algorithms · Computer Science 2016-05-12 Yaroslav Akhremtsev , Peter Sanders

Scientific studies often require the precise calculation of derivatives. In many cases an analytical calculation is not feasible and one resorts to evaluating derivatives numerically. These are error-prone, especially for higher-order…

High Energy Physics - Phenomenology · Physics 2010-05-28 Mathias Wagner , Andrea Walther , Bernd-Jochen Schaefer
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