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arXiv research

A locally-built, LLM-digested index of recent arXiv papers in quant finance, geometry/topology, and statistical ML — keyword search served straight from SQLite on this machine.

168,657 papers · 148 categories

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59118177236 · May 202619922001200920172026
48 results for Separation Equivalence

Study of eigenvalues in nonlinear kernels for classification of separable data.

problem Understanding the applicability of linear equivalents in nonlinearly separable data classification.
method Analysis of conjugate kernels and their quadratic equivalents for a canonical nonlinearly separable dataset (XOR problem).
result Identification of regimes where nonlinear kernels deviate from linear equivalents, leading to label-aligned eigenspaces.

Geodesic flows on Kähler manifolds are quantum integrable when metrics are c-projectively equivalent.

problem Quantum integrability of geodesic flows on Kähler manifolds under c-projective equivalence.
method Construction of Poisson-commuting integrals of motion and their quantum counterparts.
result The geodesic flow's integrals of motion commute as quantum operators, leading to separation of variables in Schrödinger's equation.

We solve the equivalence problem for the orthogonally separable webs on the three-sphere under the action of the isometry group. This continues a classical project initiated by Olevsky in which he solved the corresponding canonical forms problem. The solution to the equivalence problem together with the results by Olev…

2010-09-22abs ↗pdf ↗

Characterizes Bayesian networks up to unconditional equivalence.

problem Characterizing Bayesian networks up to unconditional equivalence.
method Transformational characterization via undirected graphs and specified moves.
result Two DAGs are in the same UEC if and only if one can be transformed into the other via a finite sequence of moves.

We show that the Prüfer surface, which is a separable non-metrizable 2-manifold, has not the homotopy type of a CW-complex. This will follow easily from J. H. C. Whitehead's result: if one has a good approximation of an arbitrary space by a CW-complex, which fails to be a homotopy equivalence, then the given space is n…

2006-09-23abs ↗pdf ↗

Separates estimation and control in risk-sensitive investment problems with partial observation.

problem Risk-sensitive investment problems with incomplete observation.
method Investigates separability of a general class of risk-sensitive investment management problems using a finite-dimensional filter.
result The separated problem is strictly equivalent to the original control problem.

Paper investigates separating times for general diffusions, providing new insights.

problem Understanding phase transitions between equivalence and singularity in diffusions.
method Representation of separating time as hitting time of a deterministic set, characterized by speed and scale.
result Explicit and easy-to-check conditions for absolute continuity and singularity of diffusions.

We prove that each coarsely homogenous separable metric space XX is coarsely equivalent to one of the spaces: the sigleton, the Cantor macro-cube or the Baire macro-space. This classification is derived from coarse characterizations of the Cantor macro-cube and of the Baire macro-space given in this paper. Namely, we …

2011-03-26abs ↗pdf ↗

Constructs classifiers for neural networks with specific data configurations.

problem Finding global minima of deep ReLU neural networks on sequentially separable data.
method Explicitly constructs zero loss neural network classifiers using cumulative parameters and truncation maps.
result Global minimizers can be described with a limited number of parameters based on the data structure.

For each nn, we construct a separable metric space Un\mathbb{U}_n that is universal in the coarse category of separable metric spaces with asymptotic dimension (asdim\mathop{asdim}) at most nn and universal in the uniform category of separable metric spaces with uniform dimension (udim\mathop{udim}) at most nn. Thus, $\m…

2017-08-11abs ↗pdf ↗

A new method speeds up overlapping group lasso computations.

problem Time-consuming optimization of overlapping group lasso on large-scale problems.
method Non-overlapping statistical approximation to overlapping group lasso.
result The proposed penalty is statistically equivalent to overlapping group lasso.

In this paper, we shall show a condition for that a chart is C-move equivalent to the product of two charts, the union of two charts ΓΓ^* and ΓΓ^{**} which are contained in disks DD^* and DD^{**} with DD=D^*\cap D^{**}=\emptyset.

2016-03-27abs ↗pdf ↗

We consider the notion of dimension in four categories: the category of (unbounded) separable metric spaces and (metrically proper) Lipschitz maps, and the category of (unbounded) separable metric spaces and (metrically proper) uniform maps. A unified treatment is given to the large scale dimension and the small scale …

2006-07-10abs ↗pdf ↗

New PCstar algorithm discovers causal structure of max-linear Bayesian networks.

problem Discovering causal structure in max-linear Bayesian networks due to non-faithfulness.
method PC algorithm modified with CC^\ast-separation assumptions.
result PCstar algorithm can orient additional edges not possible with standard PC algorithm.

Study tackles causal structure learning in linear models with unobserved variables and measurement error.

problem Challenges of unobserved common causes and measurement error in causal structure learning.
method Introduces LV-SEM-ME model with four types of variables and characterizes identifiability under separability condition.
result Establishes form of identification robustness for target effect in broader LV-SEM-ME model.

Gradient descent is a simple and widely used optimization method for machine learning. For homogeneous linear classifiers applied to separable data, gradient descent has been shown to converge to the maximal margin (or equivalently, the minimal norm) solution for various smooth loss functions. The previous theory does …

2019-07-26abs ↗pdf ↗

We formalize causal separation in portfolio theory, deriving a closed-form projected Markowitz solution.

problem Portfolio optimization under causal separation conditions.
method Derive a closed-form solution for portfolio optimization using causal separation conditions.
result A closed-form projected Markowitz solution is derived under causal separation conditions.

The paper proposes a new method for comparing logistic regression models across different populations.

problem Comparing logistic regression models across sub-populations can lead to misleading results.
method Develops a cascading set of equivalence tests for logistic regression models, addressing coding, predictions, and overall accuracy.
result Equivalence testing incentivizes accurate inference and avoids perverse incentives from significance tests.

Learning rule consistency tied to non-existence of real-valued measurable cardinals.

problem Consistency of k-NN learning rule in metric spaces.
method Analyzing separable subspaces and density conditions.
result The k-NN classifier's consistency depends on the absence of real-valued measurable cardinals.

This article establishes the performance of stochastic blockmodels in addressing the co-clustering problem of partitioning a binary array into subsets, assuming only that the data are generated by a nonparametric process satisfying the condition of separate exchangeability. We provide oracle inequalities with rate of c…

2012-12-17abs ↗pdf ↗

Motivated by the study of the interrelation between functorial and algebraic quantum field theory, we point out that on any locally trivial bundle of compact groups, representations up to homotopy are enough to separate points by means of the associated representations in cohomol- ogy. Furthermore, we observe that the …

2015-11-06abs ↗pdf ↗

Kernel embeddings separate distinct probability distributions, simplifying testing.

problem Testing equality of non-atomic probability distributions.
method Kernel covariance embeddings and Gaussian measures in reproducing kernel Hilbert spaces.
result Testing for singularity between Gaussian measures is equivalent to testing for equality of non-atomic probability distributions.

The paper explores how different patterns of heterophily affect Graph Neural Networks.

problem Understanding the impact of heterophily on Graph Neural Networks.
method Theoretical analysis and experiments with Heterophilous Stochastic Block Models (HSBM).
result The impact of heterophily on classification depends on the Euclidean distance of neighborhood distributions and the averaged node degree.

We show, up to h-cobordism, that the existence and uniqueness of connected sum decompositions of oriented 4-dimensional manifolds is an invariant of homotopy equivalence, assuming that the fundamental group of each summand is "good" in the sense of Freedman and Quinn. On a separate note, we observe that the Borel Conje…

2009-07-02abs ↗pdf ↗

Unified geometric framework for integrability of conservative and dissipative systems.

problem Unified definition of integrability for both conservative and dissipative systems.
method Introducing Jacobi-Haantjes manifolds and contact-Haantjes manifolds to unify definitions.
result Equivalence of integrability in contact Hamiltonian systems and existence of Abelian extended Haantjes algebra.

The unknot U in S^4 has non-unique smooth spanning 3-balls up to isotopy fixing U. Equivalently there are properly embedded non-separating 3-balls in S^1xB^3 not properly isotopic to 1xB^3. More generally there exist non-separating 3-spheres in S^1xS^3 not isotopic to 1xS^3 and non trivial elements of π_0 Diff_0(S^1xS^…

2019-12-19abs ↗pdf ↗

Existing depth separation results for constant-depth networks essentially show that certain radial functions in Rd\mathbb{R}^d, which can be easily approximated with depth 33 networks, cannot be approximated by depth 22 networks, even up to constant accuracy, unless their size is exponential in dd. However, the func…

2019-04-15abs ↗pdf ↗

This is a concise introduction to the theory of Lie groupoids, with emphasis in their role as models for stacks. After some preliminaries, we review the foundations on Lie groupoids, and we carefully study equivalences and proper groupoids. Differentiable stacks are geometric objects which have manifolds and orbifolds …

2012-12-30abs ↗pdf ↗

Garside groupoids, as recently introduced by Krammer, generalise Garside groups. A weak Garside group is a group that is equivalent as a category to a Garside groupoid. We show that any periodic loop in a Garside groupoid $\CG$ may be viewed as a Garside element for a certain Garside structure on another Garside groupo…

2006-10-26abs ↗pdf ↗