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48 results for deficiency

Generalizing the theorem of Green--Lazarsfeld and Gromov, we classify Kaehler groups of deficiency at least two. As a consequence we see that there are no Kaehler groups of even and strictly positive deficiency. With the same arguments we prove that Kaehler groups that are non-Abelian and are limit groups in the sense …

2012-04-27abs ↗pdf ↗

The study shows subgroup separability conditions for specific groups.

problem Conditions for subgroup separability in free-by-cyclic and deficiency 1 groups.
method Analyzes polynomially growing monodromy and asymptotic probability of random groups.
result Random deficiency 1 groups are not subgroup separable with positive probability.

The study calculates the Smith-Thom deficiency of Hilbert squares and provides conditions for maximality.

problem Calculating the Smith-Thom deficiency of Hilbert squares and conditions for maximality.
method Using Mayer-Vietoris mapping and rank calculations.
result Established necessary and sufficient conditions for maximality of Hilbert squares in projective complete intersections.

The paper calculates the number of oriented rational links with a given deficiency.

problem Counting oriented rational links with a specific deficiency.
method Derived precise formulas for the number of oriented rational links with crossing number n and deficiency d.
result Precise formulas for the number of oriented rational links with crossing number n and deficiency d.

We examine certain symmetries in the deficiencies of a rational surgery on a knot in S3S^3 by comparing the Spinc\text{Spin}^c-structures on the rational surgery with those on a related integral surgery. We then provide an application of these symmetries in the form of a theorem that obstructs Dehn surgeries in S3S^3. Thi…

2013-04-01abs ↗pdf ↗

Specialists tolerate defects to gain flexibility, which can be removed when needed.

problem The economic benefits and limitations of deliberately tolerating defects in decision-making.
method Analyzes the conditions under which defects can be kept and removed, using economic models and structural analysis.
result A defect is profitably removable if certain conditions are met, and the premium is the support function of the class's ROC set.

Specialists tolerate defects to gain flexibility, which can be removed when needed.

problem The economic benefits and limits of deliberately tolerating defects in decision-making.
method Analyzes the economic position of keeping and removing defects, using a coupling lemma and structural economic models.
result A defect is profitably removable if the detector-relevant distinction survives a restriction and the advantage condition holds.

"Deep Learning" methods attempt to learn generic features in an unsupervised fashion from a large unlabelled data set. These generic features should perform as well as the best hand crafted features for any learning problem that makes use of this data. We provide a definition of generic features, characterize when it i…

2014-02-20abs ↗pdf ↗

A new algorithm solves constrained optimization problems with stochastic gradients.

problem Nonlinear equality constrained optimization with rank-deficient Jacobians.
method Step decomposition strategy combining normal and tangential steps.
result Convergence guarantees in rank-deficient Jacobian cases.

For every N > 0 there exists a group of deficiency less than -N that arises as the fundamental group of a smooth homology 4-sphere and also as the fundamental group of the complement of a compact contractible submanifold of the 4-sphere. A group is the fundamental group of the complement of a contractible submanifold o…

2003-02-03abs ↗pdf ↗

We address two fundamental and well-known problems of Gromov and Lyndon: \demo{Problem A} (Gromov, see [5]). Consider a category MnM_n of closed manifolds of dimension nn with nonzero-degree ways as morphisms. Study a partial order MNMor(M,N)φM \ge N \Leftrightarrow Mor (M, N) \neq φ. For which NN the degrees of maps $f: M \t…

1995-06-25abs ↗pdf ↗

A new method combines online and offline learning to tackle contextual bandits with missing action support.

problem Learning optimal policies with logged data when the logging policy has deficient support.
method Hybrid approach using online exploration to exploit supported actions and offline learning to avoid unnecessary explorations.
result Determines an optimal policy with theoretical guarantees using minimal online explorations.

We study "how far away" a finite index subgroup G of SL(2,Z) is from being a congruence group. For this we define its deficiency of being a congruence group. We show that the index of the image of G in SL(2,Z/nZ) is biggest, if n is the general Wohlfahrt level. We furthermore show that the Veech groups of origamis (or …

2012-08-09abs ↗pdf ↗

Bayesian model predicts iron deficiency from multi-source multi-way molecular data.

problem Predicting iron deficiency in rhesus monkeys from multi-source multi-way molecular data.
method Developed a Bayesian approach with a linear model incorporating multi-way dependence and varying signal sizes across sources.
result Model accurately classifies iron deficiency in monkeys and outperforms simpler models.

Improved risk-sensitive RL with exponential Bellman equation and better regret bounds.

problem Exponential gap between upper and lower bounds in risk-sensitive RL.
method Identified and addressed deficiencies in existing algorithms and analysis; developed novel analysis and exploration mechanism.
result Improved regret upper bounds over existing ones.

We consider options that pay the complexity deficiency of a sequence of up and down ticks of a stock upon exercise. We study the price of European and American versions of this option numerically for automatic complexity, and theoretically for Kolmogorov complexity. We also consider run complexity, which is a restricte…

2015-05-14abs ↗pdf ↗

Paper addresses OPE for dependent bandit samples using MDS and batch updates.

problem Evaluating policies from non-i.i.d. historical data in contextual bandits.
method Constructs an MDS-based estimator for dependent samples, solves batch update and deficient support issues.
result Derives an asymptotically normal estimator for evaluation policy value.

The performance of standard learning procedures has been observed to differ widely across groups. Recent studies usually attribute this loss discrepancy to an information deficiency for one group (e.g., one group has less data). In this work, we point to a more subtle source of loss discrepancy---feature noise. Our mai…

2019-11-22abs ↗pdf ↗

We compute the characteristic varieties and the Alexander polynomial of a finitely generated nilpotent group. We show that the first characteristic variety may be used to detect nilpotence. We use the Alexander polynomial to deduce that the only torsion-free, finitely generated nilpotent groups with positive deficiency…

2007-10-29abs ↗pdf ↗

The study connects knot crossing numbers to surface properties and tunnel numbers.

problem Understanding the relationship between knot crossing numbers and surface properties.
method Combines surface ascending-number estimates, bridge-number estimates, and amalgamation arguments for Heegaard splittings.
result Establishes a linear relationship between the crossing number and the Heegaard deficiency of the surface.

Gradient descent with preconditioning finds global optima in overparameterized nonconvex factorization.

problem Finding global optima in nonconvex Burer-Monteiro factorization.
method Preconditioned gradient descent for overparameterized nonconvex function minimization.
result Gradient descent with preconditioning achieves linear convergence in the overparameterized case.

New method differentiates square-root Kalman filters robustly.

problem Gradient calculation issues in square-root Kalman filters.
method Closed-form chain rule derived from Gramian identity, resolves non-orthogonal and rank-deficient issues.
result Robust automatic differentiation for Kalman filters, resolving numerical stability and gradient issues.

We show that if ππ is the fundamental group of a 4-dimensional infrasolvmanifold then 2def(π)0-2\leq{def(π)}\leq0, and give examples realizing each of these values. We also determine the abstract commensurators of such groups. Finally we show that if GG is a finitely generated group the kernel of the natural homomorphism f…

2015-10-02abs ↗pdf ↗

The paper discusses fairness in bank stress tests, comparing various methods to address institutional differences.

problem Fair aggregation of bank-specific stress test models into a common model.
method Comparing various notions of regression fairness, including estimating and discarding centered bank fixed effects.
result The method of estimating and discarding centered bank fixed effects is preferable for linear models, improving forecast accuracy and equal treatment.

The paper analyzes a five-factor capital market model and facilitates exact simulation.

problem Analyzing and simulating a five-factor capital market model.
method Using a Vasicek interest rate model, mean-reverting excess return, and realized inflation with expectation, the paper derives the necessary distributional results and describes practical methods to overcome rank deficiency.
result Exact simulation from the model can be achieved by sampling from a seven-dimensional normal distribution.

DDN models flexible free-form conditional distributions.

problem Difficulty in explicitly approximating arbitrary conditional distributions.
method Deconvolutional neural network framework for discretizing continuous domains.
result DDN outperforms other density-estimation methods on various tasks.

Inequalities between the Dirichlet and Neumann eigenvalues of the Laplacian have received much attention in the literature, but open problems abound. Here, we study the number of Neumann eigenvalues no greater than the first Dirichlet eigenvalue. Based on a combination of analytical and numerical results, we conjecture…

2019-06-24abs ↗pdf ↗

A parametric manifold is a manifold on which all tensor fields depend on an additional parameter, such as time, together with a parametric structure, namely a given (parametric) 1-form field. Such a manifold admits natural generalizations of Lie differentiation, exterior differentiation, and covariant differentiation, …

1994-07-12abs ↗pdf ↗

Study improves seasonal forecasts using deep learning.

problem Challenges in generating large forecast ensembles and limited observations for verification.
method Developed a probabilistic deep neural network model.
result Demonstrated favorable skill compared to state-of-the-art dynamical forecast systems.

We derive an efficient method to perform clustering of nodes in Gaussian graphical models directly from sample data. Nodes are clustered based on the similarity of their network neighborhoods, with edge weights defined by partial correlations. In the limited-data scenario, where the covariance matrix would be rank-defi…

2019-10-05abs ↗pdf ↗

We study the asymptotic growth of homology groups and the cellular volume of classifying spaces as one passes to normal subgroups Gn<GG_n<G of increasing finite index in a fixed finitely generated group GG, assuming nGn=1\bigcap_n G_n =1. We focus in particular on finitely presented residually free groups, calculating thei…

2013-09-07abs ↗pdf ↗

In response to the development of recent efficient dense layers, this paper shows that something as simple as replacing linear components in pointwise convolutions with structured linear decompositions also produces substantial gains in the efficiency/accuracy tradeoff. Pointwise convolutions are fully connected layers…

2019-06-03abs ↗pdf ↗

In various classes of infinite groups, we identify groups that are presentable by products, i.e. groups having finite index subgroups which are quotients of products of two commuting infinite subgroups. The classes we discuss here include groups of small virtual cohomological dimension and irreducible Zariski dense sub…

2014-09-25abs ↗pdf ↗

Study nondifferentiable metrics in general relativity, resolving causality issues and limits evolution scenarios.

problem Causality issues and evolution scenarios in black hole interiors with closed timelike geodesics.
method Method of equivalence on Courant algebroids to derive new differential invariants.
result Resolved causality issues and limited evolution scenarios for gravitational collapse.

A new framework for robust transfer learning that avoids negative transfer in domains with unequal information.

problem Negative transfer in unsupervised domain adaptation, especially when source and target domains have different levels of informativeness.
method Decision-theoretic framework based on Le Cam's theory of statistical experiments, using constructive approximations to replace strict invariance with directional simulability.
result Le Cam Distortion achieves near-perfect frequency estimation and zero source utility loss in various domains, demonstrating superior performance compared to traditional methods.