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We study which machine learning algorithms have tight generalization bounds. First, we present conditions that preclude the existence of tight generalization bounds. Specifically, we show that algorithms that have certain inductive biases…

Machine Learning · Computer Science 2024-10-04 Michael Gastpar , Ido Nachum , Jonathan Shafer , Thomas Weinberger

We provide theoretical bounds on the worst case performance of the greedy algorithm in seeking to maximize a normalized, monotone, but not necessarily submodular objective function under a simple partition matroid constraint. We also…

Systems and Control · Electrical Eng. & Systems 2022-10-19 Benjamin Biggs , James McMahon , Philip Baldoni , Daniel J. Stilwell

In this work we obtain a transference theorem for Lebesgue spaces with $A_{\infty }$ weights, namely, starting from some uniform-norm inequalities it is possible to obtain similar inequalities in Lebesgue spaces with $A_{\infty }$ weights.…

Functional Analysis · Mathematics 2023-07-27 Ramazan Akgün

In this work, we unify several expected generalization error bounds based on random subsets using the framework developed by Hellstr\"om and Durisi [1]. First, we recover the bounds based on the individual sample mutual information from Bu…

Information Theory · Computer Science 2021-07-27 Borja Rodríguez-Gálvez , Germán Bassi , Ragnar Thobaben , Mikael Skoglund

We study the problem of improving the greedy constant or the democracy constant of a basis of a Banach space by renorming. We prove that every Banach space with a greedy basis can be renormed, for a given $\vare>0$, so that the basis…

Functional Analysis · Mathematics 2014-03-18 S. J. Dilworth , D. Kutzarova , E. Odell , Th. Schlumprecht , A. Zsák

We obtain the decay bounds for Chebyshev series coefficients of functions with finite Vitali variation on the unit square. A generalization of the well known identity, which relates exact and approximated coefficients, obtained using the…

Numerical Analysis · Mathematics 2022-05-12 Akansha

The greedy algorithm adapted from Kruskal's algorithm is an efficient and folklore way to produce a $k$-spanner with girth at least $k+2$. The greedy algorithm has shown to be `existentially optimal', while it's not `universally optimal'…

Data Structures and Algorithms · Computer Science 2024-11-05 Yeyuan Chen

It is shown that that the fractional integral operators with the parameter $\alpha$, $0<\alpha<1$, are not bounded between the generalized grand Lebesgue spaces $L^{p), \theta_1}$ and $L^{q), \theta_2}$ for $\theta_2 < (1+\alpha…

Functional Analysis · Mathematics 2010-07-08 Alexander Meskhi

A novel and detailed convergence analysis is presented for a greedy algorithm that was previously introduced for operator reconstruction problems in the field of quantum mechanics. This algorithm is based on an offline/online decomposition…

Optimization and Control · Mathematics 2020-11-02 S Buchwald , G Ciaramella , Julien Salomon

We study sparse approximate solutions to convex optimization problems. It is known that in many engineering applications researchers are interested in an approximate solution of an optimization problem as a linear combination of elements…

Machine Learning · Statistics 2012-06-05 V. N. Temlyakov

Let $X$ be a Banach space and $\mathcal{K}$ be a compact subset in $X$. We consider a greedy algorithm for finding an $n$-dimensional subspace $V_n\subset X$ which can be used to approximate the elements of $\mathcal{K}$. We are interested…

Functional Analysis · Mathematics 2019-08-06 Van Kien Nguyen

We introduce a new PAC-Bayes oracle bound for unbounded losses that extends Cram\'er-Chernoff bounds to the PAC-Bayesian setting. The proof technique relies on controlling the tails of certain random variables involving the Cram\'er…

Machine Learning · Statistics 2024-10-31 Ioar Casado , Luis A. Ortega , Aritz Pérez , Andrés R. Masegosa

We consider the problem of sparse atomic optimization, where the notion of "sparsity" is generalized to meaning some linear combination of few atoms. The definition of atomic set is very broad; popular examples include the standard basis,…

Optimization and Control · Mathematics 2019-12-30 Thomas Zhang

Many policy problems involve designing individualized treatment allocation rules to maximize the equilibrium social welfare of interacting agents. Focusing on large-scale simultaneous decision games with strategic complementarities, we…

Econometrics · Economics 2024-11-12 Guanyi Wang

It is known that a basis is almost greedy if and only if the thresholding greedy algorithm gives essentially the smallest error term compared to errors from projections onto intervals or in other words, consecutive terms of $\mathbb{N}$. In…

Functional Analysis · Mathematics 2025-02-12 Miguel Berasategui , Pablo M. Berná , Hung Viet Chu

This paper proposes and evaluates the k-greedy equivalence search algorithm (KES) for learning Bayesian networks (BNs) from complete data. The main characteristic of KES is that it allows a trade-off between greediness and randomness, thus…

Machine Learning · Computer Science 2012-12-12 Jens D. Nielsen , Tomas Kocka , Jose M. Pena

We describe an adaptive greedy algorithm for Thiele continued-fraction approximation of a function defined on a continuum domain in the complex plane. The algorithm iteratively selects interpolation nodes from an adaptively refined set of…

Numerical Analysis · Mathematics 2025-10-09 Tobin A. Driscoll , Yuxing Zhou

We demonstrate that the greedy algorithm for reduction of divisors on metric graphs need not terminate by modeling the Euclidean algorithm in this context. We observe that any infinite reduction has a well defined limit allowing us to treat…

Combinatorics · Mathematics 2015-04-17 Spencer Backman

In the paper two-weighted norm estimates with general weights for Hardy-type transforms, maximal functions, potentials and Calder\'on-Zygmund singular integrals in variable exponent Lebesgue spaces defined on quasimetric measure spaces $(X,…

Functional Analysis · Mathematics 2010-07-09 Vakhtang Kokilashvili , Alexander Meskhi And Muhammad Sarwar

For a real-valued measurable function $f$ and a nonnegative, nondecreasing function $\phi$, we first obtain a Chebyshev type inequality which provides an upper bound for $\displaystyle \phi(\lambda_{1}) \mu(\{x \in \Omega : f(x) \geq…

Functional Analysis · Mathematics 2022-09-14 M. Ashraf Bhat , G. Sankara Raju Kosuru
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