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This study investigates imposing hard inequality constraints on the outputs of convolutional neural networks (CNN) during training. Several recent works showed that the theoretical and practical advantages of Lagrangian optimization over…

Computer Vision and Pattern Recognition · Computer Science 2023-08-31 Hoel Kervadec , Jose Dolz , Jing Yuan , Christian Desrosiers , Eric Granger , Ismail Ben Ayed

Central issues of the Dirac constraint formalism are discussed in relation to the algorithmic methods of commutative algebra based on the Groebner basis techniques. For a wide class of finite dimensional polynomial degenerate Lagrangian…

Mathematical Physics · Physics 2007-05-23 V. Gerdt , A. Khvedelidze , Yu. Palii

This paper studies expurgated random-coding bounds and exponents for channel coding with a given (possibly suboptimal) decoding rule. Variations of Gallager's analysis are presented, yielding several asymptotic and non-asymptotic bounds on…

Information Theory · Computer Science 2016-11-17 Jonathan Scarlett , Li Peng , Neri Merhav , Alfonso Martinez , Albert Guillén i Fàbregas

A detailed discussion of the renormalization properties of a class of gauges which interpolates among the Landau, Coulomb and Maximal Abelian gauges is provided in the framework of the algebraic renormalization in Euclidean Yang-Mills…

High Energy Physics - Theory · Physics 2008-11-26 M. A. L. Capri , R. F. Sobreiro , S. P. Sorella , R. Thibes

Effective Lagrangians containing arbitrary interactions of massive vector fields are quantized within the Hamiltonian path integral formalism. It is proven that correct Hamiltonian quantization of these models yields the same result as…

High Energy Physics - Phenomenology · Physics 2009-10-22 Carsten Grosse-Knetter

A covariant quantization scheme employing reducible representations of canonical commutation relations with positive-definite metric and Hermitian four-potentials is tested on the example of quantum electrodynamic fields produced by a…

High Energy Physics - Theory · Physics 2014-11-18 Marek Czachor , Jan Naudts

We study the spectral implications of re-weighting a graph by the $\ell_\infty$-Lewis weights of its edges. Our main motivation is the ER-Minimization problem (Saberi et al., SIAM'08): Given an undirected graph $G$, the goal is to find…

Data Structures and Algorithms · Computer Science 2023-02-14 Amit Suliman , Omri Weinstein

We derive a high-resolution formula for the quantization and entropy coding approximation quantities for fractional Brownian motion, respective to the supremum norm and L^p[0,1]-norm distortions. We show that all moments in the quantization…

Probability · Mathematics 2007-05-23 Steffen Dereich , Michael Scheutzow

Based on the results of a recent reexamination of the quantization of systems with first-class and second-class constraints from the point of view of coherent-state phase-space path integration, we give additional examples of the…

Quantum Physics · Physics 2007-05-23 John R. Klauder

We examine the Einstein-Cartan (EC) theory in first-order form, which has a diffeomorphism as well as a local Lorentz invariance. We study the renormalizability of this theory in the framework of the Batalin-Vilkovisky formalism, which…

High Energy Physics - Theory · Physics 2024-09-27 F. T. Brandt , J. Frenkel , S. Martins-Filho , D. G. C. McKeon

The rules of local superfield Lagrangian quantization in reducible non-Abelian hypergauge functions are formulated for an arbitrary gauge theory. The generating functionals of standard and vertex Green's functions which depend on the…

High Energy Physics - Theory · Physics 2008-03-26 Alexander A. Reshetnyak

The role of cut-off and dimensional regularizations is discussed in the context of obtaining a renormalized nucleon-nucleon potential from the chiral Lagrangian formulation of the effective field theory due to Weinberg. Both types of…

Nuclear Theory · Physics 2007-05-23 Sadhan K. Adhikari

This paper addresses optimal decoding strategies in lossy compression where the assumed distribution for compressor design mismatches the actual (true) distribution of the source. This problem has immediate relevance in standardized…

Information Theory · Computer Science 2026-02-04 Saeed R. Khosravirad , Ahmed Alkhateeb , Ingrid van de Voorde

We examine a covariant quantization of electromagnetic fields by using an operator derived from a constant scalar that can be called extended Lorentz gauge. The quantization can avoid an inconsistency between Lorentz gauge and a commutation…

General Physics · Physics 2020-08-03 Masahito Morimoto

Large alphabet source coding is a basic and well-studied problem in data compression. It has many applications such as compression of natural language text, speech and images. The classic perception of most commonly used methods is that a…

Information Theory · Computer Science 2016-07-26 Amichai Painsky , Saharon Rosset , Meir Feder

The recently proposed renormalization scheme based on the definition of field operators as operator valued distributions acting on specific test functions is shown to be very convenient in explicit calculations of physical observables…

High Energy Physics - Theory · Physics 2009-12-10 P. Grange , J. -F. Mathiot , B. Mutet , E. Werner

We develop in this paper a new framework for discrete calculus of variations when the actions have densities involving an arbitrary discretization operator. We deduce the discrete Euler-Lagrange equations for piecewise continuous critical…

Optimization and Control · Mathematics 2011-06-28 Philippe Ryckelynck , Laurent Smoch

This paper describes a general formalism for obtaining localized solutions to a class of problems in mathematical physics, which can be recast as variational optimization problems. This class includes the important cases of Schr\"odinger's…

Numerical Analysis · Mathematics 2014-03-05 Vidvuds Ozoliņš , Rongjie Lai , Russel Caflisch , Stanley Osher

A renormalized version of the von Neumann quantum entropy (which is finite and continuous in general, infinite dimensional case) and which obeys several of the natural physical demands (as expected for a "good" measure of entanglement in…

Quantum Physics · Physics 2022-11-11 Roman Gielerak

For optimization problems with nonlinear constraints, linearly constrained Lagrangian (LCL) methods sequentially minimize a Lagrangian function subject to linearized constraints. These methods converge rapidly near a solution but may not be…

Optimization and Control · Mathematics 2007-05-23 Michael P. Friedlander , Michael A Saunders