arXiv research

Paper provides a performance guarantee for spectral clustering.

A novel hypergraph partitioning method using tensor eigenvalue decomposition captures super-dyadic interactions.

Spectral clustering is sensitive to how graphs are constructed from data particularly when proximal and imbalanced clusters are present. We show that Ratio-Cut (RCut) or normalized cut (NCut) objectives are not tailored to imbalanced data since they tend to emphasize cut sizes over cut values. We propose a graph partit…

Spectral clustering methods which are frequently used in clustering and community detection applications are sensitive to the specific graph constructions particularly when imbalanced clusters are present. We show that ratio cut (RCut) or normalized cut (NCut) objectives are not tailored to imbalanced cluster sizes sin…

Spectral Clustering as a relaxation of the normalized/ratio cut has become one of the standard graph-based clustering methods. Existing methods for the computation of multiple clusters, corresponding to a balanced $k$-cut of the graph, are either based on greedy techniques or heuristics which have weak connection to th…

This paper establishes the consistency of a family of graph-cut-based algorithms for clustering of data clouds. We consider point clouds obtained as samples of a ground-truth measure. We investigate approaches to clustering based on minimizing objective functionals defined on proximity graphs of the given sample. Our f…

A recent theoretical analysis shows the equivalence between non-negative matrix factorization (NMF) and spectral clustering based approach to subspace clustering. As NMF and many of its variants are essentially linear, we introduce a nonlinear NMF with explicit orthogonality and derive general kernel-based orthogonal m…

Spectral clustering (SC) and graph-based semi-supervised learning (SSL) algorithms are sensitive to how graphs are constructed from data. In particular if the data has proximal and unbalanced clusters these algorithms can lead to poor performance on well-known graphs such as $k$-NN, full-RBF, $ε$-graphs. This is becaus…

We relax indicator matrices to form a manifold for faster optimization.

Algorithms based on spectral graph cut objectives such as normalized cuts, ratio cuts and ratio association have become popular in recent years because they are widely applicable and simple to implement via standard eigenvector computations. Despite strong performance for a number of clustering tasks, spectral graph cu…

Spectral clustering has become one of the most widely used clustering techniques when the structure of the individual clusters is non-convex or highly anisotropic. Yet, despite its immense popularity, there exists fairly little theory about performance guarantees for spectral clustering. This issue is partly due to the…

Minimum Description Length prevents overfitting in noisy data.

Minimum attention improves reinforcement learning performance in high-dimensional dynamics.

The minimum number of colors is a challenging knot invariant since, by definition, its calculation requires taking the minimum over infinitely many minima. In this article we estimate and in some cases calculate the minimum number of colors for the Turk's head knots on three strands.

Minimum braids are a complete invariant of knots and links. This paper defines minimum braids, describes how they can be generated, presents tables for knots up to ten crossings and oriented links up to nine crossings, and uses minimum braids to study graph trees, amphicheirality, unknotting numbers, and periodic table…

Study tightens bounds for interpolating noisy data using minimum l1-norm.

A new classification method based on Minimum Spanning Trees

The paper finds minimum Dehn colors for knots and defines useful graphs for coloring.

The paper calculates genus bounds for multibranched surfaces.

Knots are commonly found in molecular chains such as DNA and proteins, and they have been considered to be useful models for structural analysis of these molecules. One interested quantity is the minimum number of monomers necessary to realize a molecular knot. The minimum lattice length $\mbox{Len}(K)$ of a knot $K$ i…

Study shows how networks converge to minimum norm solutions with regularization.

We find the minimum dilatation of pseudo-Anosov braids with many strands.

Study introduces AMVP and AMRR for dynamic portfolio optimization in volatile markets.

Minimum algebraic intersection found in hyperbolic surfaces, growing with genus.

Computed minimum crossing numbers for Turaev genus 2 links.

This paper studies the geometry of minimum-volume confidence sets for multinomial parameters.

Building on previous results on the quadratic helicity in magnetohydrodynamics (MHD) we investigate particular minimum helicity states. Those are eigenfunctions of the curl operator and are shown to constitute solutions of the quasi-stationary incompressible ideal MHD equations. We then show that these states have inde…

The paper calculates minimum Dehn colors for knots using symmetric local biquandle cocycles.

Inference for normal and Monte Carlo distributions using minimum relative entropy.

ML helps select variables for minimum-variance portfolios, reducing risk and improving performance.

We investigate the time series of the degree of minimum spanning trees obtained by using a correlation based clustering procedure which is starting from (i) asset return and (ii) volatility time series. The minimum spanning tree is obtained at different times by computing correlation among time series over a time windo…

Paper proves edge-connectivity equals minimum degree for graphs with non-negative curvature.

New approach finds minimum width for deep, narrow MLPs.

We consider the relations between different measures of complexity for free homotopy classes of curves on a surface $Σ$, including the minimum number of self-intersections, the minimum length of the words representing them in a geometric presentation of $π_1(Σ)$, and the minimum degree of the coverings of $Σ$ to which …

Unified framework for geometric computation of minimum-area homotopy.

The study tightens bounds on binomial probabilities and minimums using KL-divergence.

In this paper we study the minimum dilatation pseudo-Anosov mapping classes coming from fibrations over the circle of a single 3-manifold, the mapping torus for the "simplest pseudo-Anosov braid". The dilatations that arise include the minimum dilatations for orientable mapping classes for genus g=2,3,4,5,8 as well as …

Originally, the SW-equations discovered by Seiberg-Witten are 1st-order PDE, which solutions (A,φ), with φ\ne 0, are known as SW-monopoles. It is known that the solutions of these 1st-order eq correspond to the minimum of SW-functional. However, it is not true, that for all spin^{c} class α, the minimum is always attai…

Investigates the long-only minimum variance portfolio in factor models.

Paper shows minimum 10 vertices for hyperbolic origami 2-torus.

Defines MER for Bayesian learning, a gap between achievable and optimal performance.

We prove that every simple graph of order 12 which has minimum degree 6 contains a K_6 minor.

Mathematical framework for minimum enclosing ball problem.

Consider the problem of estimating the minimum entropy of pseudo-Anosov maps on a surface of genus $g$ with $n$ punctures. We determine the behaviour of this minimum number for a certain large subset of the $(g,n)$ plane, up to a multiplicative constant. In particular it has been shown that for fixed $n$, this minimum …

Study on folded ribbon knots and their minimum length.

New framework for DNN training guarantees convergence to global minimum.

Even knots with more than 30 crossings are not fertile.

Optimal estimator derived for partially observable LTI systems.