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In this paper, we develop fast algorithms for two stochastic submodular maximization problems. We start with the well-studied adaptive submodular maximization problem subject to a cardinality constraint. We develop the first linear-time…

Machine Learning · Computer Science 2020-07-09 Shaojie Tang

Current dynamical overlap fermion hybrid Monte Carlo simulations encounter large fermionic forces when there is mixing between near zero-eigenvectors of the kernel operator. This leads to low acceptance rates when there is a large density…

High Energy Physics - Lattice · Physics 2009-03-12 Nigel Cundy

We present a distributed proximal-gradient method for optimizing the average of convex functions, each of which is the private local objective of an agent in a network with time-varying topology. The local objectives have distinct…

Distributed, Parallel, and Cluster Computing · Computer Science 2012-10-09 Annie I. Chen , Asuman Ozdaglar

In this paper, we propose some accelerated methods for solving optimization problems under the condition of relatively smooth and relatively Lipschitz continuous functions with an inexact oracle. We consider the problem of minimizing the…

Optimization and Control · Mathematics 2024-11-27 O. S. Savchuk , M. S. Alkousa , A. S. Shushko , A. A. Vyguzov , F. S. Stonyakin , D. A. Pasechnyuk , A. V. Gasnikov

We discuss the usage and applicability of deflation methods for the overlap lattice Dirac operator, focussing on calculating the eigenvalues using a method similar to the eigCG algorithm used for other Dirac operators. The overlap operator,…

High Energy Physics - Lattice · Physics 2016-05-04 Nigel Cundy , Weonjong Lee

We present a new multigrid solver that is suitable for the Dirac operator in the presence of disordered gauge fields. The key behind the success of the algorithm is an adaptive projection onto the coarse grids that preserves the near null…

High Energy Physics - Lattice · Physics 2008-11-26 J. Brannick , R. C. Brower , M. A. Clark , J. C. Osborn , C. Rebbi

We achieve a quantum speed-up of fully polynomial randomized approximation schemes (FPRAS) for estimating partition functions that combine simulated annealing with the Monte-Carlo Markov Chain method and use non-adaptive cooling schedules.…

Quantum Physics · Physics 2013-06-12 Pawel Wocjan , Chen-Fu Chiang , Anura Abeyesinghe , Daniel Nagaj

We consider the speed planning problem for a robotic manipulator. In particular, we present an algorithm for finding the time-optimal speed law along an assigned path that satisfies velocity and acceleration constraints and respects the…

Robotics · Computer Science 2018-10-04 Luca Consolini , Marco Locatelli , Andrea Minari , Akos Nagy , Istvan Vajk

Chiral symmetry is a key to investigating quantum physics, from condensed matter to particle physics. We propose a novel way of realizing a chiral fermion, known as the overlap-Dirac operator, without explicitly calculating the low modes of…

High Energy Physics - Lattice · Physics 2022-04-05 Yuki Nagai , Akio Tomiya

Algorithms which compute locally optimal continuous designs often rely on a finite design space or on repeatedly solving a complex non-linear program. Both methods require extensive evaluations of the Jacobian Df of the underlying model.…

Methodology · Statistics 2021-01-18 Philipp Seufert , Jan Schwientek , Michael Bortz

We describe a suite of fast algorithms for evaluating Jacobi polynomials, applying the corresponding discrete Sturm-Liouville eigentransforms and calculating Gauss-Jacobi quadrature rules. Our approach is based on the well-known fact that…

Numerical Analysis · Mathematics 2018-03-13 James Bremer , Haizhao Yang

In this talk, we shall assess the finite ma errors from the overlap fermion. We shall present results on the speed of light from the dispersion relation and hyperfine splitting between the vector and pseudoscalar mesons as a function to ma…

High Energy Physics - Lattice · Physics 2009-04-14 S. J. Dong , K. F. Liu

Submodular optimization generalizes many classic problems in combinatorial optimization and has recently found a wide range of applications in machine learning (e.g., feature engineering and active learning). For many large-scale…

Data Structures and Algorithms · Computer Science 2023-04-11 Matthew Fahrbach , Vahab Mirrokni , Morteza Zadimoghaddam

Practical online learning tasks are often naturally defined on unconstrained domains, where optimal algorithms for general convex losses are characterized by the notion of comparator adaptivity. In this paper, we design such algorithms in…

Machine Learning · Computer Science 2022-10-13 Zhiyu Zhang , Ashok Cutkosky , Ioannis Ch. Paschalidis

This paper proposes a computationally tractable algorithm for learning infinite-horizon average-reward linear Markov decision processes (MDPs) and linear mixture MDPs under the Bellman optimality condition. While guaranteeing computational…

Machine Learning · Computer Science 2024-09-25 Woojin Chae , Dabeen Lee

We prove convergence with optimal algebraic rates for an adaptive finite element method for nonlinear equations with strongly monotone operator. Unlike prior works, our analysis also includes the iterative and inexact solution of the…

Numerical Analysis · Mathematics 2018-11-27 Gregor Gantner , Alexander Haberl , Dirk Praetorius , Bernhard Stiftner

We compute non-perturbatively the renormalization constants of composite operators for overlap fermions by using the regularization independent scheme. The scaling behavior of the renormalization constants is investigated using the data…

High Energy Physics - Lattice · Physics 2007-05-23 J. B. Zhang , D. B. Leinweber , A. G. Williams

We present the domain-wall fermion operator which is reflection symmetric in the fifth dimension, with the approximate sign function $ S(H) $ of the effective 4-dimensional Dirac operator satisfying the bound $ |1-S(\lambda)| \le 2 d_Z $…

High Energy Physics - Lattice · Physics 2015-12-29 Ting-Wai Chiu

We show that, for each symmetry class based on the tenfold way classification, the effective Dirac operator obtained by integrating out the additional bulk direction takes a value in the corresponding classifying space, from which we obtain…

High Energy Physics - Theory · Physics 2023-09-22 Taro Kimura , Masataka Watanabe

In the moldable job scheduling problem one has to assign a set of $n$ jobs to $m$ machines, in order to minimize the time it takes to process all jobs. Each job is moldable, so it can be assigned not only to one but any number of the equal…

Data Structures and Algorithms · Computer Science 2023-03-03 Kilian Grage , Klaus Jansen , Felix Ohnesorge