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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.

169,051 papers · 148 categories

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8.3%16.7%25.0%33.3% · Jan 199319922001200920182026
48 results for Mirror

We describe mirror symmetry on higher dimensional tori, paying special attention to the behaviour of D-branes under mirror symmetry. To find the mirror D-branes the description of mirror symmetry on D-branes due to Ooguri, Oz en Yin is used. This method allows us to deal with the coisotropic D-branes recently introduce…

2001-11-06abs ↗pdf ↗

Study homological mirror symmetry for Hirzebruch surfaces using Morse homotopy.

problem Homological mirror symmetry for Hirzebruch surfaces Fk\mathbb{F}_k.
method Using Strominger-Yau-Zaslow construction and Morse homotopy.
result Homological mirror symmetry holds for Hirzebruch surfaces Fk\mathbb{F}_k.

This paper deforms complex tori and their mirrors using gerbes.

problem Deforming complex tori and their mirror partners.
method Using flat gerbes to deform complex tori and their mirrors, constructing holomorphic line bundles over deformed objects.
result Deformed complex tori and their mirrors can be studied using flat gerbes.

New analysis shows GMD can converge linearly under PL-like conditions.

problem Establishing linear convergence for generalized mirror descent.
method PL-based analysis for time-dependent mirrors, Taylor-series approach for stochastic GMD.
result Linear convergence of stochastic GMD under PL-like conditions.

In this article we explore some finer properties of equi-areal mirrors and introduce techniques for developing new mirror surfaces that simultaneously minimize angular and areal distortion.

2014-10-24abs ↗pdf ↗

Mirror flow optimizes separable data problems, converging to a maximum margin classifier.

problem Optimizing classification problems with separable data using mirror flow.
method Examine mirror flow on linearly separable classification problems, focusing on the horizon function of the mirror potential.
result Mirror flow converges to a maximum margin classifier for separable data under certain conditions.

Reparameterizes mirror descent as gradient descent for efficient sparse learning.

problem Efficiently training small sparse networks with mirror descent.
method Develops a framework to convert mirror descent updates into gradient descent updates on different parameters.
result Mirror descent can be reparameterized as gradient descent on modified parameters, facilitating standard backpropagation.

This paper focuses on a topological version on the Strominger-Yau-Zaslow mirror symmetry conjecture. Roughly put, the SYZ conjecture suggests that mirror pairs of Calabi-Yau manifolds are related by the existence of dual special Lagrangian torus fibrations. We explore this conjecture without reference to the special La…

1999-09-02abs ↗pdf ↗

NGMs create mirrored features to assess neural network feature importance.

problem Lack of feature relevance information in DNNs limits their applicability.
method Structured perturbation and kernel-based conditional dependence measure for feature importance evaluation.
result Controls feature selection error rate and maintains high selection power with correlated features.

The paper discusses a solution to homological mirror symmetry for complex tori, especially when the matrix is singular.

problem Homological mirror symmetry for complex tori, particularly when the matrix is singular.
method Proposes a new approach to define a mirror partner for complex tori of dimension n2n \geq 2 when the matrix is singular.
result Proposes a method to avoid the problem of defining a mirror partner for complex tori of higher dimensions when the matrix is singular.

Find first (0,2) mirror symmetry examples on Hopf surfaces.

problem Find (0,2) mirror symmetry on compact non-Kähler manifolds.
method Use Borisov's approach with vertex algebras and chiral de Rham complex. Study Killing spinors on quadratic Lie algebras and embeddings of superconformal vertex algebras.
result Construct first (0,2) mirror pairs of Hopf surfaces.

Inspired by the paper on quantum knots and knot mosaics [23] and grid diagrams (or arc presentations), used extensively in the computations of Heegaard-Floer knot homology [2,3,7,24], we construct the more concise representation of knot mosaics and grid diagrams via mirror-curves. Tame knot theory is equivalent to knot…

2011-06-19abs ↗pdf ↗

We discuss mirror symmetry in generalized Calabi-Yau compactifications of type II string theories with background NS fluxes. Starting from type IIB compactified on Calabi-Yau threefolds with NS three-form flux we show that the mirror type IIA theory arises from a purely geometrical compactification on a different class…

2002-11-12abs ↗pdf ↗

In this article we discuss the geometry of moduli spaces of (1) flat bundles over special Lagrangian submanifolds and (2) deformed Hermitian-Yang-Mills bundles over complex submanifolds in Calabi-Yau manifolds. These moduli spaces reflect the geometry of the Calabi-Yau itself like a mirror. Strominger, Yau and Zaslow c…

2002-04-12abs ↗pdf ↗

Continuous-time mirror descent solves sparse phase retrieval efficiently.

problem Recovering sparse signals from magnitude-only measurements.
method Continuous-time mirror descent applied to unconstrained empirical risk minimization problem.
result Mirror descent recovers kk-sparse vectors with minimum non-zero entry order of x2/k\| \mathbf{x}^\star \|_2/\sqrt{k} from k2k^2 Gaussian measurements.

Mirror descent linked to information ratio via Bayesian regret bounds.

problem Understanding stability in mirror descent and its relation to information ratio.
method Developed a connection between mirror descent and information ratio using Bayesian regret bounds.
result Mirror descent with suitable estimators and distributions achieves bounds similar to information-directed sampling.

Paper studies early-stopped mirror descent for noisy sparse phase retrieval.

problem Recovering a sparse signal from noisy quadratic measurements.
method Early-stopped mirror descent with hyperbolic entropy mirror map.
result Achieves nearly minimax-optimal rate of convergence for kk-sparse signals.

The present paper deals with mirror symmetry aspects of compact ``barely'' G2G_2 manifolds, that is, G2G_2 manifolds of the form (CY×S1)/Z2\times S^1)/\mathbb{Z}_2. We propose that the mirror of any barely G2G_2 manifold is another barely one and which is constructed as a fibration of the \emph{mirror} of the CY base. Also,…

2007-07-10abs ↗pdf ↗

New method improves generative modeling on convex domains using regularized mirror maps and Student-t priors.

problem Challenges in generative modeling on convex domains with heavy-tailed targets.
method Mirror Flow Matching with regularized mirror maps and Student-t priors.
result Empirically outperforms baselines and achieves competitive sample quality.

CatNet controls FDR in LSTM models using SHAP feature importance and Gaussian mirrors.

problem Controlling False Discovery Rate (FDR) in LSTM models with feature selection.
method CatNet uses SHAP values for feature importance and Gaussian Mirror algorithm for FDR control. It introduces a kernel-based independence measure to handle feature correlations.
result CatNet reduces overfitting and improves model interpretability on simulated and real-world data.

Continuous-time distributed mirror descent with integral feedback converges to global optimum.

problem Distributed optimization of a global strongly convex function with local convex components.
method Continuous-time distributed mirror descent with integral feedback.
result Asymptotic convergence to global optimum with constant step-size.

We explore the intrinsic geometry of tangent bundles and properties of the mirror map.

problem Understanding the intrinsic geometry of tangent bundles and properties of the mirror map.
method Review and solve cohomological questions related to the mirror map and related operators.
result Solved some cohomological questions and raised other induced by the d_B operator.

Study mirrors descent's early stopping for linear and kernel models, improving risk guarantees.

problem Understanding the statistical performance of early-stopped mirror descent algorithms.
method Characterized convexity of squared loss, identified link between offset Rademacher complexities and mirror descent convergence.
result Excess risk guarantees for mirror descent iterates traced by the path, expressed in terms of offset complexities.

This paper explores a new framework for reinforcement learning based on online convex optimization, in particular mirror descent and related algorithms. Mirror descent can be viewed as an enhanced gradient method, particularly suited to minimization of convex functions in highdimensional spaces. Unlike traditional grad…

2012-10-16abs ↗pdf ↗

The study connects K-stability and large complex structure limits in mirror symmetry.

problem Understanding K-stability and its relation to large complex structure limits in mirror symmetry.
method Analyzing Kähler test configurations and their mirror Landau-Ginzburg models, studying scaling behavior, and focusing on specific limiting cases.
result New formulae for the Donaldson-Futaki invariant are derived in terms of theta functions on the mirror in certain limiting cases.

The paper connects tempering and entropic mirror descent for sampling.

problem Sampling from a target distribution with known unnormalized density.
method Establishes the connection between tempering SMC and entropic mirror descent, deriving convergence rates and geometric insights.
result Tempering SMC iterates correspond to entropic mirror descent on the reverse KL divergence, providing new optimization perspectives.

Stochastic mirror descent improves performance on ensemble models.

problem Improving performance of ensemble models using stochastic mirror descent.
method Utilizes mirror potential to influence training algorithm's implicit bias, mapping evolution to continuous time process.
result Converges to a nonlinear PDE in asymptotic regime of large networks, with mirror potential affecting gradient flow.

The mirror of a projective toric manifold XΣX_Σ is given by a Landau-Ginzburg model (Y,W)(Y,W). We introduce a class of Lagrangian submanifolds in (Y,W)(Y,W) and show that, under the SYZ mirror transformation, they can be transformed to torus-invariant hermitian metrics on holomorphic line bundles over XΣX_Σ. Through this ge…

2009-03-06abs ↗pdf ↗

The paper explores non-Kähler SYZ mirrors for solvmanifolds, proving cohomological properties and constructing new mirror pairs.

problem Understanding non-Kähler SYZ mirrors for solvmanifolds and their cohomological properties.
method Investigates geometric and cohomological properties, proving relationships and constructing mirror pairs.
result Proves the Fourier-Mukai transform exchanges type-A and type-B cycles, and provides criteria for non-Kähler SYZ mirror pairs.