arXiv research

For harmonic maps of degree 2, a similar quantitative stability estimate does not hold uniformly.

In this paper, we give the sharp estimates for the degree of symmetry and the semi-simple degree of symmetry of certain four dimensional fiber bundles by virtue of the rigidity theorem of harmonic maps due to Schoen and Yau. As a corollary of this estimate, we compute the degree of symmetry and the semi-simple degree o…

We define and study the statistical models in exponential family form whose sufficient statistics are the degree distributions and the bi-degree distributions of undirected labelled simple graphs. Graphs that are constrained by the joint degree distributions are called $dK$-graphs in the computer science literature and…

New evidence shows computational barriers in graphon estimation using low-degree polynomials.

New findings on computational limits for estimating hidden structures.

New work shows FP potential monotonicity equals low-degree polynomial estimators limits.

The paper corrects for node degree in spectral clustering using random walk Laplacian.

Survey on using low-degree polynomials to assess statistical tasks complexity.

Extends Popularity Bias Memorization theorem to new conditions.

We give estimates for the eigenvalues of multi-form modified Dirac operators which are constructed from a standard Dirac operator with the addition of a Clifford algebra element associated to a multi-degree form. In particular such estimates are presented for modified Dirac operators with a $k$-degree form $0\leq k\leq…

We study the degree of polynomial representations of knots. We give the lexicographic degree of all two-bridge knots with 11 or fewer crossings. First, we estimate the total degree of a lexicographic parametrisation of such a knot. This allows us to transform this problem into a study of real algebraic trigonal plane c…

Developed a new thresholding method that connects soft and hard thresholding.

The paper proposes a new model to analyze directed networks and accurately estimate community memberships.

This paper tests the multivariate normality of node degrees in Erdős-Rényi graphs.

Improved model for grouping nodes in bipartite networks.

The derivation of statistical properties for Partial Least Squares regression can be a challenging task. The reason is that the construction of latent components from the predictor variables also depends on the response variable. While this typically leads to good performance and interpretable models in practice, it ma…

New framework reduces sum-of-squares proof degree, speeding up clustering and robust moment estimation.

In this paper, we explore degrees of freedom in deep sigmoidal neural networks. We show that the degrees of freedom in these models is related to the expected optimism, which is the expected difference between test error and training error. We provide an efficient Monte-Carlo method to estimate the degrees of freedom f…

We prove in this paper that, under suitable coinditions on an initial data set, we can obtain Area and Curvature Estimates for simple marginally outer trapped surfaces (or MOTS). Using this estimates, we derive a Compactness Theorem for MOTS. Moreover, the Compactness Theorem will allow us to adapt the recent Degree Th…

Corrects GCV for inconsistent risk estimation in finite ensembles of penalized estimators.

Study privacy vs. utility in estimating network parameters with aggregated data.

We show a connection between the Fourier spectrum of Boolean functions and the REINFORCE gradient estimator for binary latent variable models. We show that REINFORCE estimates (up to a factor) the degree-1 Fourier coefficients of a Boolean function. Using this connection we offer a new perspective on variance reduction…

Paper estimates area covered by a line-sweep sensor in robotics.

We prove that a bounded open set U in Euclidean n-space has k-width less than C(n) Volume(U)^{k/n}. Using this estimate, we give lower bounds for the k-dilation of degree 1 maps between certain domains in Euclidean space. In particular, we estimate the smallest (n-1)-dilation of any degree 1 map between two n-dimension…

Paper studies Hessian quotient equations in warped product manifolds.

Estimates the degree of trace fields of hyperbolic Dehn fillings.

A new method estimates uncertainty without explicit prediction models.

Spectral clustering is a fast and popular algorithm for finding clusters in networks. Recently, Chaudhuri et al. (2012) and Amini et al.(2012) proposed inspired variations on the algorithm that artificially inflate the node degrees for improved statistical performance. The current paper extends the previous statistical…

A central question in modern machine learning and imaging sciences is to quantify the number of effective parameters of vastly over-parameterized models. The degrees of freedom is a mathematically convenient way to define this number of parameters. Its computation and properties are well understood when dealing with di…

The paper approximates smooth hypersurfaces with algebraic ones, controlling the degree.

Paper develops methods for estimating and simulating a Student-t Lévy regression model.

We apply Murasugi-Tristram inequality to real algebraic curves of odd degree on $RP^2$ with a deep nest, i.e. a nest of the depth $k-1$ where $2k+1$ is the degree. For such curves, the ingredients of the Murasugi-Tristram inequality can be computed (or estimated) inductively using the computations for iterated torus li…

New spectral clustering method for graphs with uneven node degrees.

The sinh-Gordon equation is solved on finite, symmetric graphs.

We estimate the linear isoperimetric constants of an n-dimensional ellipse. Using these estimates and a technique of Gromov, we estimate the Hopf and linking invariants of Lipschitz maps from ellipses to round spheres. Using these estimates, we give a lower bound for the k-dilation of degree non-zero maps between ellip…

Christoffel function characterizes the corruption a bounded-degree certificate cannot remove in robust halfspace learning.

Develops a new tensor model for clustering with degree correction.

Feature importance estimates that inform users about the degree to which given inputs influence the output of a predictive model are crucial for understanding, validating, and interpreting machine-learning models. However, providing fast and accurate estimates of feature importance for high-dimensional data, and quanti…

In this paper, we study the Khovanov homology of cable links. We first estimate the maximal homological degree term of the Khovanov homology of the ($2k+1$, $(2k+1)n$)-torus link and give a lower bound of its homological thickness. Specifically, we show that the homological thickness of the ($2k+1$, $(2k+1)n$)-torus li…

The stochastic block model (SBM) is a popular framework for studying community detection in networks. This model is limited by the assumption that all nodes in the same community are statistically equivalent and have equal expected degrees. The degree-corrected stochastic block model (DCSBM) is a natural extension of S…

Measures neural network complexity via effective degrees of freedom.

The paper studies inference in hypergraph β-models with multiple layers.

The paper argues for using more degrees of freedom in empirical financial analysis to improve conclusions.

Estimates curvature for holomorphic maps on Riemann surfaces.

Sharp estimate shows maps with small energy defect are close to rational maps.

Let $β$ be a braid on $n$ strands, with exponent sum $w$. Let $Δ$ be the Garside half-twist braid. We prove that the coefficient of $v^{w-n+1}$ in the Homfly polynomial of the closure of $β$ agrees with $(-1)^{n-1}$ times the coefficient of $v^{w+n^2-1}$ in the Homfly polynomial of the closure of $βΔ^2$. This coinciden…

Unified spectral clustering for sparse networks with heterogeneous degrees.

The paper provides an algorithm for the risk estimation when a company selects an outsourcing service provider for innovation product. Calculations are based on expert surveys conducted among customers and among providers of outsourcing. The surveys assessed the degree of materiality of species at risk.