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We introduce property-independent kernels for machine learning modeling of arbitrarily many molecular properties. The kernels encode molecular structures for training sets of varying size, as well as similarity measures sufficiently diffuse…

Chemical Physics · Physics 2015-03-18 Raghunathan Ramakrishnan , O. Anatole von Lilienfeld

Binary neural networks, i.e., neural networks whose parameters and activations are constrained to only two possible values, offer a compelling avenue for the deployment of deep learning models on energy- and memory-limited devices. However,…

We describe a bilinear identity satisfied by certain multidimensional q-hypergeometric integrals. The identity can be considered as a deformation of the Riemann bilinear relation for the twisted de Rham (co)homologies. The identity also…

q-alg · Mathematics 2008-02-03 Vitaly Tarasov

We consider a class of operator-induced norms, acting as finite-dimensional surrogates to the L2 norm, and study their approximation properties over Hilbert subspaces of L2 . The class includes, as a special case, the usual empirical norm…

Statistics Theory · Mathematics 2011-06-01 Arash A. Amini , Martin J. Wainwright

We study representations of positive definite kernels $K$ in a general setting, but with view to applications to harmonic analysis, to metric geometry, and to realizations of certain stochastic processes. Our initial results are stated for…

Functional Analysis · Mathematics 2017-06-30 Palle Jorgensen , Feng Tian

We provide a framework for the sparse approximation of multilinear problems and show that several problems in uncertainty quantification fit within this framework. In these problems, the value of a multilinear map has to be approximated…

Numerical Analysis · Mathematics 2018-07-17 Fabio Nobile , Raul Tempone , Soeren Wolfers

We obtain a family of new combinatorial identities for symmetric formal power series.

Quantum Algebra · Mathematics 2016-09-07 A. Sevostyanov

We introduce several new identities combining basic hypergeometric sums and integrals. Such identities appear in the context of superconformal index computations for three-dimensional supersymmetric dual theories. We give both analytic…

High Energy Physics - Theory · Physics 2016-11-08 Ilmar Gahramanov , Hjalmar Rosengren

We show that sampling or interpolation formulas in reproducing kernel Hilbert spaces can be obtained by reproducing kernels whose dual systems form molecules, ensuring that the size profile of a function is fully reflected by the size…

Functional Analysis · Mathematics 2022-05-04 José Luis Romero , Jordy Timo van Velthoven , Felix Voigtlaender

The structure of transformation semigroups on a finite set is analyzed by introducing a hierarchy of functions mapping subsets to subsets. The resulting hierarchy of semigroups has a corresponding hierarchy of minimal ideals, or kernels.…

Probability · Mathematics 2016-12-02 G. Budzban , Ph. Feinsilver

We characterize the reproducing kernel Hilbert spaces whose elements are $p$-integrable functions in terms of the boundedness of the integral operator whose kernel is the reproducing kernel. Moreover, for $p=2$ we show that the spectral…

Functional Analysis · Mathematics 2007-05-23 Claudio Carmeli , Ernesto De Vito , Alessandro Toigo

In this paper we consider a large class of fully nonlinear integro-differential equations. The class of our nonlocal operators we consider is not spatial homogeneous and we put mild assumptions on its kernel near zero. We prove the H\"older…

Probability · Mathematics 2014-05-12 Jongchun Bae

Applying kernel methods to matchings is challenging due to their discrete, non-Euclidean nature. In this paper, we develop a principled framework for constructing geometric kernels that respect the natural geometry of the space of…

Machine Learning · Computer Science 2026-04-17 Dmitry Eremeev , Salem Said , Viacheslav Borovitskiy

We start by showing how to approximate unitary and bounded self-adjoint operators by operators in finite dimensional spaces. Using ultraproducts we give a precise meaning for the approximation. In this process we see how the spectral…

Logic · Mathematics 2022-08-16 Åsa Hirvonen , Tapani Hyttinen

This is Part 1 of two papers where we develop the basic potential theory of elliptic operators on posssibly singular almost minimzers using their hyperbolic unfoldings. We can establish surprisingly robust boundary Harnack inequalities…

Differential Geometry · Mathematics 2018-10-09 Joachim Lohkamp

With the advent of kernel methods, automating the task of specifying a suitable kernel has become increasingly important. In this context, the Multiple Kernel Learning (MKL) problem of finding a combination of pre-specified base kernels…

Machine Learning · Computer Science 2012-07-03 Abhishek Kumar , Alexandru Niculescu-Mizil , Koray Kavukcuoglu , Hal Daume

We present a spectral theory of hypergraphs that closely parallels Spectral Graph Theory. A number of recent developments building upon classical work has led to a rich understanding of "hyperdeterminants" of hypermatrices, a.k.a.…

Combinatorics · Mathematics 2011-10-27 Joshua Cooper , Aaron Dutle

We develop a systematic procedure for constructing quantum many-body problems whose spectrum can be partially or totally computed by purely algebraic means. The exactly-solvable models include rational and hyperbolic potentials related to…

Exactly Solvable and Integrable Systems · Physics 2008-11-26 D. Gomez-Ullate , A. Gonzalez-Lopez , M. A. Rodriguez

We consider positive semidefinite kernels which have values given by bounded linear operators on certain bundles of Hilbert spaces and which are invariant under actions of $*$-semigroupoids. For these kernels, we prove that there exist…

Functional Analysis · Mathematics 2026-02-20 Aurelian Gheondea

In this paper, we characterize the families of those bounded linear operators on a separable Hilbert space which are simultaneously unitarily equivalent to integral bi-Carleman operators on $L_2(R)$ having arbitrarily smooth kernels of…

Spectral Theory · Mathematics 2007-05-23 Igor M. Novitskii
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