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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.

169,291 papers · 148 categories

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3671107142 · May 202619922001200920182026
48 results for Lück's theorem

Final revision. To appear in the Journal of Differential Geometry. This paper studies knots that are transversal to the standard contact structure in R3\reals^3, bringing techniques from topological knot theory to bear on their transversal classification. We say that a transversal knot type $\cTK$ is {\it transversally…

1999-10-29abs ↗pdf ↗

We construct a cubical CW-complex CK(M^3) whose rational cohomology algebra contains Vassiliev invariants of knots in the 3-manifold M^3. We construct \bar{CK}(R^3) by attaching cells to CK(R^3) for every degenerate 1-singular and 2-singular knot, and we show that π_1(\bar{CK}(R^3))=1 and π_2(\bar{CK}(R^3))=Z. We give …

2000-10-02abs ↗pdf ↗

CK simplifies ML model deployment and reproducibility with open APIs and DevOps.

problem Making ML models reproducible and deployable across different environments.
method Decompose complex systems into reusable sub-components with unified APIs and DevOps principles.
result Automatically co-design and optimize ML models for speed, accuracy, energy, and size.

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.

Study eigenvalue distributions of neural kernels for linear-width networks.

problem Eigenvalue distributions of neural kernels in linear-width networks.
method Asymptotic analysis of Conjugate Kernel and Neural Tangent Kernel under random initialization and approximate orthogonality.
result Eigenvalue distributions converge to deterministic limits, described by recursive fixed-point equations.

Study eigenvalues and eigenvectors in neural networks, focusing on signal propagation.

problem Characterize signal eigenvalues and eigenvectors in neural networks.
method Characterizes signal eigenvalues and eigenvectors for a nonlinear spiked covariance model.
result Provides precise quantitative characterizations of signal eigenvalues and eigenvectors in neural networks.

DEQs and explicit networks are nearly equivalent for Gaussian mixtures.

problem Understanding the equivalence between DEQs and explicit neural networks.
method Random matrix theory and analysis of kernel matrices.
result A shallow explicit network can mimic the kernel of a DEQ.

We consider canonical metrics on Fano manifolds. First we introduce a norm-type functional on Fano manifolds, which has Kahler-Einstein or Kahler-Ricci soliton as its critical point and the Kahler-Ricci flow can be viewed as its (reduced) gradient flow. We then obtain a natural lower bound of this functional. As an app…

2012-08-05abs ↗pdf ↗

Study finds new minimal surfaces in Schwarzschild space.

problem Existence of non-totally geodesic minimal surfaces in Schwarzschild space.
method Family of properly embedded free boundary minimal hypersurfaces of revolution.
result Existence of new minimal surfaces with circular boundaries in Schwarzschild space.

A hypercomplex manifold M is a manifold with a triple I,J,K of complex structure operators satisfying quaternionic relations. For each quaternion L=aI +bJ+cK, L^2=-1, L is also a complex structure operator on M, called an induced complex structure. We are studying compact complex subvarieties of (M,L), when L is a gene…

2012-02-01abs ↗pdf ↗

We develop an algebraic representation for (1,1)-knots using the mapping class group of the twice punctured torus MCG(T,2). We prove that every (1,1)-knot in a lens space L(p,q) can be represented by the composition of an element of a certain rank two free subgroup of MCG(T,2) with a standard element only depending on …

2002-05-13abs ↗pdf ↗

The paper studies neural networks with wide layers and finds a deformed semicircle law.

problem Investigating spectral distributions of neural networks in the ultra-wide regime.
method Analyzes empirical kernel matrices, proves deformed semicircle law, provides nonlinear Hanson-Wright inequality.
result Emergence of a deformed semicircle law in the ultra-wide neural network regime.

This paper analyzes the Bochner formula for Riemannian flows and derives eigenvalue estimates.

problem Analyzing the Bochner formula for Riemannian flows and deriving eigenvalue estimates.
method The approach involves studying the curvature term in the Bochner-Weitzenb{ö}ck formula of the basic Laplacian on M, splitting it into two parts, and establishing eigenvalue estimates.
result Established an eigenvalue estimate of the basic Laplacian on basic forms, and discussed the limiting case of the estimate.

In this paper, we show that the Lie superalgebra spo(2l+2n)\mathfrak{spo}(2l+2|n) is into the intersection of Lie superalgebra of contact vector fields K(2l+1n)\mathcal{K}(2l+1|n) and the Lie superalgebra of projective vector fields pgl(2l+2n)\mathfrak{pgl}(2l+2|n). We use mainly the embedding used by P. Mathonet and F. Radoux in "\textit{ …

2016-06-30abs ↗pdf ↗

Paper analyzes learning dynamics in quasi-periodic environments, showing consistent solutions.

problem Challenges in stochastic gradient learning for complex environments.
method Uses energy balance equations derived from Caldirola-Kanai Hamiltonian to model learning.
result In quasi-periodic environments, learning yields consistent solutions for similar patterns.

Proposes a linear model for facial action recognition without requiring large datasets.

problem Limited annotated data for facial expression and action units.
method Exploits low-rank property across frames and group sparsity to subtract neutral faces and recognize actions.
result One-shot automatic method on raw face videos performs competitively and better than previous methods.

New insights into query complexity for Nash equilibrium learning.

problem Characterizing the number of queries needed to learn approximate Nash equilibria in matrix games.
method Introduced a new technique to prove lower bounds on query complexity, improving previous techniques.
result Lower bounds of order Ω(log(1Kε))Ω(\log(\frac{1}{Kε})) for any ε1/(cK4)ε\leq 1 / (cK^4), where cc is a constant.

Study estimates squared error in high-dimensional binary regression, revealing phase transitions and structural properties.

problem Estimating squared error in high-dimensional regression with binary coefficients.
method Novel conditional second moment method to approximate optimal squared error.
result Establishes a phase transition point \( n^* = 2k \log p / \log (2k/\sigma^2 + 1) \) for binary regression, revealing structural properties and information-theoretic threshold.

New algorithm reduces online learning regret in uninformed Markov games.

problem Achieving no external regret in uninformed Markov games is impossible.
method Empirical Nash-value regret, parameter-free algorithm, adaptive restart.
result Achieves O(min{K+(CK)1/3,LK})O(\min \{\sqrt{K} + (CK)^{1/3},\sqrt{LK}\}) regret bound.

The paper proves a new theorem in Riemannian geometry and offers a new proof for Toponogov's theorem in Alexandrov geometry.

problem Proving new theorems in Riemannian and Alexandrov geometries.
method Inspired by the proof of the Schur-Toponogov theorem, a new proof of Toponogov's theorem is provided.
result A new theorem in Riemannian geometry and a new proof of Toponogov's theorem in Alexandrov geometry.

The paper proves three circles theorems and Liouville type theorems for subharmonic and holomorphic functions.

problem Establishing theorems for subharmonic and holomorphic functions on specific geometric structures.
method Using subharmonic and holomorphic functions on Riemannian manifolds and gradient shrinking Ricci solitons.
result Proves Liouville type theorems as applications of the established theorems.

Paper generalizes complex Brunn-Minkowski theory and proves new extension theorems.

problem Complex Brunn-Minkowski theory and extension theorems.
method Hilbert bundle approach to complex Brunn-Minkowski theory.
result Generalizes Guan's sharp strong openness theorem and sharp Ohsawa-Takegoshi extension theorem.

Formulates Index III lemma and Rauch III theorem with applications.

problem Develops new mathematical theorems based on existing ones.
method Formulation of Index III lemma and Rauch III theorem based on Index I, II lemmas and Rauch I, II theorems.
result Presented Rauch's type theorem and volume comparison result as applications.

In LM, we proved a family version of the famous Witten rigidity theorems and several family vanishing theorems for elliptic genera. In this paper, we gerenalize our theorems LM in two directions. First we establish a family rigidity theorem for the Dirac operator on loop space twisted by general positive energy loop gr…

1999-11-05abs ↗pdf ↗

The paper explains the topological origin of the distinction between incidence theorems over division rings and fields.

problem Understanding the distinction between incidence theorems over division rings and fields.
method Extending the surface-graph approach to noncommutative settings, the paper analyzes the topological properties of graphs embedded on surfaces of different genera.
result Theorems associated with graphs on the sphere hold over any division ring, while those on surfaces of positive genus typically hold only if the ground ring is a field.