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The fundamental principle underlying compressed sensing is that a signal, which is sparse under some basis representation, can be recovered from a small number of linear measurements. However, prior knowledge of the sparsity basis is…

Information Theory · Computer Science 2010-04-29 Sivan Gleichman , Yonina C. Eldar

We assume the direct sum <A> o <B> for the signal subspace. As a result of post- measurement, a number of operational contexts presuppose the a priori knowledge of the LB -dimensional "interfering" subspace <B> and the goal is to estimate…

Applications · Statistics 2017-04-17 Guillaume Bouleux , Rémy Boyer

We present a very simple yet powerful generalization of a previously described model and algorithm for estimation of multiple dipoles from magneto/electro-encephalographic data. Specifically, the generalization consists in the introduction…

Applications · Statistics 2020-06-09 Alessandro Viani , Gianvittorio Luria , Harald Bornfleth , Alberto Sorrentino

This paper addresses the problem of basis correction in the context of LSS identification from input-output data. It is often the case that identification algorithms for the LSSs from input-output data operate locally. The individually…

Systems and Control · Electrical Eng. & Systems 2024-07-30 Fethi Bencherki , Semiha Türkay , Hüseyin Akçay

Test-time scaling offers a promising path to improve LLM reasoning by utilizing more compute at inference time; however, the true promise of this paradigm lies in extrapolation (i.e., improvement in performance on hard problems as LLMs keep…

Machine Learning · Computer Science 2025-06-16 Amrith Setlur , Matthew Y. R. Yang , Charlie Snell , Jeremy Greer , Ian Wu , Virginia Smith , Max Simchowitz , Aviral Kumar

This paper presents a new view of Explanation-Based Learning (EBL) of natural language parsing. Rather than employing EBL for specializing parsers by inferring new ones, this paper suggests employing EBL for learning how to reduce ambiguity…

cmp-lg · Computer Science 2008-02-03 Khalil Sima'an

This article revisits the fundamental problem of parameter selection for Gaussian process interpolation. By choosing the mean and the covariance functions of a Gaussian process within parametric families, the user obtains a family of…

Methodology · Statistics 2023-08-09 Sébastien Petit , Julien Bect , Paul Feliot , Emmanuel Vazquez

Basis set convergence of the Hartree-Fock and the correlation energy is examined for the hydrogen bonded infinite bent chains (HF)_infinity and (HCl)_infinity. We employ series of correlation consistent basis sets up to quintuple zeta…

Other Condensed Matter · Physics 2007-05-23 Christian Buth , Beate Paulus

The Bethe-Salpeter equation (BSE) based on GW quasiparticle levels is a successful approach for calculating the optical gaps and spectra of solids and also for predicting the neutral excitations of small molecules. We here present an…

Materials Science · Physics 2020-02-19 Chi Liu , Jan Kloppenburg , Xinguo Ren , Heiko Appel , Yosuke Kanai , Volker Blum

In modern communication systems such as the Internet, random losses of information can be mitigated by oversampling the source. This is equivalent to expanding the source using overcomplete systems of vectors (frames), as opposed to the…

Functional Analysis · Mathematics 2025-10-20 Roman Vershynin

Calculations in field theory are usually accomplished by employing some variants of perturbation theory, for instance using loop expansions. These calculations result in asymptotic series in powers of small coupling parameters, which as a…

High Energy Physics - Phenomenology · Physics 2021-05-05 V. I. Yukalov , E. P. Yukalova

The application of error-free transformation (EFT) is recently being developed to solve ill-conditioned problems. It can reduce the number of arithmetic operations required, compared with multiple precision arithmetic, and also be applied…

Numerical Analysis · Mathematics 2019-10-24 Tomonori Kouya

We consider bounds on the generalization performance of the least-norm linear regressor, in the over-parameterized regime where it can interpolate the data. We describe a sense in which any generalization bound of a type that is commonly…

Machine Learning · Statistics 2021-10-19 Peter L. Bartlett , Philip M. Long

In this paper, we study the conditional stochastic optimization (CSO) problem which covers a variety of applications including portfolio selection, reinforcement learning, robust learning, causal inference, etc. The sample-averaged gradient…

Machine Learning · Computer Science 2023-12-05 Lie He , Shiva Prasad Kasiviswanathan

Certain quasi-exactly solvable systems exhibit an energy reflection property that relates the energy levels of a potential or of a pair of potentials. We investigate two sister potentials and show the existence of this energy reflection…

Quantum Physics · Physics 2009-11-07 Michael Kavic

We explore the robustness of the correlation matrix Hamiltonian reconstruction technique with respect to the choice of operator basis, studying the effects of bases that are undercomplete and over-complete -- too few or too many operators…

Strongly Correlated Electrons · Physics 2024-09-12 Lucas Z. Brito , Stephen Carr , J. Alexander Jacoby , J. B. Marston

This paper presents a Bayesian framework for assessing the adequacy of a model without the necessity of explicitly enumerating a specific alternate model. A test statistic is developed for tracking the performance of the model across…

Artificial Intelligence · Computer Science 2013-03-25 Kathryn Blackmond Laskey

A scheme to provide various mean-field-type approximation algorithms is presented by employing the Bethe free energy formalism to a family of replicated systems in conjunction with analytical continuation with respect to the number of…

Disordered Systems and Neural Networks · Physics 2009-11-11 Yoshiyuki Kabashima

We review the Bethe-Salpeter equation (BSE) approach to the calculation of electronic excitation energies of molecular systems. We recall the general Green's function many-theory formalism and give the working equations of the BSE approach…

Chemical Physics · Physics 2013-04-05 Elisa Rebolini , Julien Toulouse , Andreas Savin

Refining one's hypotheses in the light of data is a common scientific practice; however, the dependency on the data introduces selection bias and can lead to specious statistical analysis. An approach for addressing this is via conditioning…

Machine Learning · Computer Science 2020-03-03 Jen Ning Lim , Makoto Yamada , Wittawat Jitkrittum , Yoshikazu Terada , Shigeyuki Matsui , Hidetoshi Shimodaira
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