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Related papers: Interacting Copies of Random Constraint Satisfacti…

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The Constraint Satisfaction Problem (CSP) and its counting counterpart appears under different guises in many areas of mathematics, computer science, and elsewhere. Its structural and algorithmic properties have demonstrated to play a…

Combinatorics · Mathematics 2020-07-15 Raimundo Briceño , Andrei Bulatov , Victor Dalmau , Benoit Larose

Contrastive Language and Image Pairing (CLIP), a transformative method in multimedia retrieval, typically trains two neural networks concurrently to generate joint embeddings for text and image pairs. However, when applied directly, these…

Computer Vision and Pattern Recognition · Computer Science 2024-09-04 Konstantin Schall , Kai Uwe Barthel , Nico Hezel , Klaus Jung

We consider a random geometric graph with vertices sampled from a probability measure supported on $\mathbb R^d$, and study its connectivity. We show the graph is typically disconnected, unless the sampling density has superexponential…

Probability · Mathematics 2021-04-07 Henry-Louis de Kergorlay

Mixture model-based frameworks are very popular for statistical inference in clustering. While convenient for producing probabilistic estimates of cluster assignments and uncertainty, they are prone to misspecification, which can lead to…

Statistics Theory · Mathematics 2026-05-15 Yu Zheng , Leo L. Duan , Arkaprava Roy

We study the phase fluctuations in the normal state of generic two-dimensional superconducting systems with s-wave pairing. The effect of phase fluctuations of the pairing fields can be dealt with perturbatively using disorder averaging,…

Superconductivity · Physics 2023-06-02 Xu-Cheng Wang , Yang Qi

We present the complete phase diagram for one-dimensional binary mixtures of bosonic ultracold atomic gases in a harmonic trap. We obtain exact results with direct numerical diagonalization for small number of atoms, which permits us to…

Dual decomposition provides a tractable framework for designing algorithms for finding the most probable (MAP) configuration in graphical models. However, for many real-world inference problems, the typical decomposition has a large…

Data Structures and Algorithms · Computer Science 2012-10-19 David Sontag , Do Kook Choe , Yitao Li

In his classical work, Kuramoto analytically described the onset of synchronization in all-to-all coupled networks of phase oscillators with random intrinsic frequencies. Specifically, he identified a critical value of the coupling…

Dynamical Systems · Mathematics 2018-08-15 Hayato Chiba , Georgi S. Medvedev , Matthew S. Mizuhara

We present new results for LambdaCC and MotifCC, two recently introduced variants of the well-studied correlation clustering problem. Both variants are motivated by applications to network analysis and community detection, and have…

Computational Complexity · Computer Science 2018-09-26 David F. Gleich , Nate Veldt , Anthony Wirth

The development of numerical methods capable of simulating realistic materials with strongly correlated electrons, with controllable errors, is a central challenge in quantum many-body physics. Here we describe how a hybrid between…

Strongly Correlated Electrons · Physics 2015-04-23 Alexei A. Kananenka , Emanuel Gull , Dominika Zgid

Zimmermann's Reduction of Couplings (RoC) method is a powerful tool for addressing the problem of the excess of parameters in a field theory, as it yields relations among couplings that are invariant under the renormalization group. Its…

High Energy Physics - Phenomenology · Physics 2026-05-07 Luis Enrique Reyes Rodríguez , Myriam Mondragón

Quality by design in pharmaceutical manufacturing hinges on computational methods and tools that are capable of accurate quantitative prediction of the design space. This paper investigates Bayesian approaches to design space…

Correlation Clustering (CC) is a fundamental unsupervised learning primitive whose strongest LP-based approximation guarantees require $\Theta(n^3)$ triangle inequality constraints and are prohibitive at scale. We initiate the study of…

Machine Learning · Computer Science 2026-02-17 Ibne Farabi Shihab , Sanjeda Akter , Anuj Sharma

We introduce a method that uses the Cauchy-Crofton formula and a new curvature formula from integral geometry to reweight the sampling probabilities of Metropolis-within-Gibbs algorithms in order to increase their convergence speed. We…

Probability · Mathematics 2015-03-13 Oren Mangoubi , Alan Edelman

Hamiltonian Monte Carlo (HMC) algorithms which combine numerical approximation of Hamiltonian dynamics on finite intervals with stochastic refreshment and Metropolis correction are popular sampling schemes, but it is known that they may…

Computation · Statistics 2022-08-16 Peter A. Whalley , Daniel Paulin , Benedict Leimkuhler

In many applications of Bayesian clustering, posterior sampling on the discrete state space of cluster allocations is achieved via Markov chain Monte Carlo (MCMC) techniques. As it is typically challenging to design transition kernels to…

Computation · Statistics 2019-06-14 Masoud Asgharian , Martin Lysy , Vahid Partovi Nia

We investigate the Constraint Satisfaction Problem (CSP) over templates with a group structure, and algorithms solving CSP that are equivariant, i.e. invariant under a natural group action induced by a template. Our main result is a method…

Logic in Computer Science · Computer Science 2016-04-06 Sławomir Lasota

The 1-loop evolution of couplings in the minimal supersymmetric standard model, extended to include baryon nonconserving $(B\!\!\!/)$ operators through explicit $R$-parity violation, is considered keeping only $B\!\!\!/$ superpotential…

High Energy Physics - Phenomenology · Physics 2014-11-17 Biswajoy Brahmachari , Probir Roy

We model the equilibrium properties of a two-dimensional electron gas in a square lateral superlattice of quantum dots in a GaAs heterostructure subject to an external homogeneous perpendicular magnetic field and a far-infrared circular…

We present a Monte Carlo method for computing the renormalized coupling constants and the critical exponents within renormalization theory. The scheme, which derives from a variational principle, overcomes critical slowing down, by means of…

Statistical Mechanics · Physics 2017-12-06 Yantao Wu , Roberto Car