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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.

169,051 papers · 148 categories

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4.2%8.3%12.5%16.7% · Sep 199519922001200920182026
48 results for Mutual Coherence

CNNs solve inverse problems during training, proving mutual coherence crucial for convergence.

problem Validation of CNN learning during training.
method Proved CNN elements solve inverse problems, discussed mutual coherence, and set training rules.
result Mutual coherence is necessary for CNNs to converge to optimum solutions.

InfoOT improves data alignment by maximizing mutual information.

problem Optimal transport's limitations in handling clusters, outliers, and new data.
method InfoOT extends optimal transport by maximizing mutual information while minimizing distances.
result InfoOT outperforms optimal transport in domain adaptation, cross-domain retrieval, and single-cell alignment.

Parallel spinors help characterize G2* structures and isotropic forms.

problem Characterizing G2* structures and isotropic forms on pseudo-Riemannian manifolds.
method Using a correspondence between irreducible parallel spinors and solutions of a differential system for three-forms.
result Explicit description of isotropic irreducible spinors in signature (4,3) and characterization of G2* structures.

We introduce the adversarially learned inference (ALI) model, which jointly learns a generation network and an inference network using an adversarial process. The generation network maps samples from stochastic latent variables to the data space while the inference network maps training examples in data space to the sp…

2016-06-02abs ↗pdf ↗

We consider fundamental questions of arbitrage pricing arising when the uncertainty model is given by a set of possible mutually singular probability measures. With a single probability model, essential equivalence between the absence of arbitrage and the existence of an equivalent martingale measure is a folk theorem,…

2012-02-29abs ↗pdf ↗

In this paper, we address the challenging task of achieving multi-view dimensionality reduction. The goal is to effectively use the availability of multiple views for extracting a coherent low-dimensional representation of the data. The proposed method exploits the intrinsic relation within each view, as well as the mu…

2015-08-23abs ↗pdf ↗

This work analyzes privacy-utility trade-offs in linear regression with noise and projections.

problem Balancing privacy and utility in machine learning models trained on private data.
method Analyzes two schemes: additive noise and random projections, using differential privacy based on conditional mutual information.
result Projecting data to a lower-dimensional subspace before adding noise yields a better privacy-utility trade-off.

Coherent Multiplex analyzes real-time wavelet coherence among multiple signals.

problem Identifying and visualizing coherence among multiple time series.
method Fast spectral similarity based on cosine similarity metrics of Fourier-transformed signals and sparse time-frequency wavelet coherence.
result Scalable real-time system for low-latency inference and monitoring of inter-signal relationships.

The transition amplitudes between coherent states on a coherent state manifold are expressed in terms of the embedding of the coherent state manifold into a projective Hilbert space. Consequences for the dimension of projective Hilbert space and a simple geometric interpretation of Calabi's diastasis follows.

1997-07-31abs ↗pdf ↗

Researchers explore non-coherent banding in site-specific recombination.

problem Understanding non-coherent banding in site-specific recombination.
method Survey of recent developments in non-coherent banding on knots.
result Recent advances in non-coherent banding model for site-specific recombination.

Sparse coding in learned dictionaries has been established as a successful approach for signal denoising, source separation and solving inverse problems in general. A dictionary learning method adapts an initial dictionary to a particular signal class by iteratively computing an approximate factorization of a training …

2012-05-28abs ↗pdf ↗

New metric mm-coherence measures gradient alignment during training, revealing surprising memorization patterns.

problem Measuring and understanding the alignment of per-example gradients during training.
method Introducing mm-coherence as a metric to study gradient alignment, showing its advantages over existing metrics.
result Training with random labels leads to high mm-coherence, indicating common patterns even when generalization is not possible.

Develops equivariant Chern characters for coherent sheaves with group actions.

problem Computing Chern characters for coherent sheaves on manifolds with group actions.
method Introduces equivariant Chern characters and proves Riemann-Roch-Grothendieck theorem in Bott-Chern cohomology.
result Establishes a Riemann-Roch-Grothendieck theorem for coherent sheaves with finite group actions.

Generates coherent storybooks from plain text using diffusion models.

problem Ensuring coherency in a sequence of images for storytelling applications.
method Combines pre-trained LLM and text-guided Latent Diffusion Model for zero-shot generation.
result Outperforms state-of-the-art image editing baselines in generating coherent storybooks.

Low-rank matrix approximations are often used to help scale standard machine learning algorithms to large-scale problems. Recently, matrix coherence has been used to characterize the ability to extract global information from a subset of matrix entries in the context of these low-rank approximations and other sampling-…

2010-09-04abs ↗pdf ↗

The paper proves mutual information measurement is statistically limited.

problem Measuring mutual information from finite data is difficult.
method Proves statistical limitations on any method of measuring mutual information.
result Any distribution-free high-confidence lower bound on mutual information estimated from N samples cannot be larger than O(ln N ).

Morse theory extended to noncompact manifolds with complex geometric data.

problem Extending Morse theory to noncompact manifolds with intricate geometric and homotopy data.
method Defining Morse homology for pairs of manifolds and related geometric/homotopy data, constructing a homotopy coherent diagram of linear maps, and showing it computes Morse homology.
result Morse homology can be computed using a chain complex derived from a homotopy coherent diagram.

Develops non-standard analysis for coherent risk estimation.

problem Estimating coherent risk measures in financial contexts.
method Non-standard analysis, hyperfinite representations, discrete Kusuoka formulae, plug-in asymptotics.
result Uniform almost sure consistency and asymptotic normality of spectral plug-in estimators.

This paper improves facial expression recognition using CNNs and coherence constraints.

problem Facial expression recognition from static images and video sequences is challenging.
method Investigates the use of Convolutional Neural Networks (CNNs) with coherence constraints in a semi-supervised setting.
result Coherence constraints improve facial expression recognition quality, especially in the presence of occlusions.

We propose a pricing technique based on coherent risk measures, which enables one to get finer price intervals than in the No Good Deals pricing. The main idea consists in splitting a liability into several parts and selling these parts to different agents. The technique is closely connected with the convolution of coh…

2006-05-02abs ↗pdf ↗

The coherent states are viewed as a powerful tool in differential geometry. It is shown that some objects in differential geometry can be expressed using quantities which appear in the construction of the coherent states. The following subjects are discussed via the coherent states: the geodesics, the conjugate locus a…

1998-07-14abs ↗pdf ↗

We emphasize some properties of coherent state groups, i.e. groups whose quotient with the stationary groups, are manifolds which admit a holomorphic embedding in a projective Hilbert space. We determine the differential action of the generators of the representation of coherent state groups on the symmetric Fock space…

2002-11-04abs ↗pdf ↗

The paper proposes new ways to enforce orthogonality in deep CNNs training.

problem Enforcing orthogonality in deep CNNs training.
method Developed novel orthogonality regularizations using analytical tools like mutual coherence and restricted isometry property.
result Consistent performance gains in final accuracies and convergence speed after applying regularizations.

Proposes a copula-based filter for diabetes risk prediction.

problem Feature selection for robust and interpretable predictive modeling in medicine, especially for extreme patient strata.
method Copula-based supervised filter using Gumbel-copula implied upper-tail concordance score (lambda U).
result The proposed filter outperforms standard filters and provides clinically coherent predictors.

For homogeneous simply connected Hodge manifolds it is proved that the set of coherent vectors orthogonal to a given one is the divisor responsible for the homogeneous holomorphic line bundle of the coherent vectors. In particular, for naturally reductive spaces, the divisor is the cut locus.

1998-07-14abs ↗pdf ↗

A group is coherent if all its finitely generated subgroups are finitely presented. In this article we provide a criterion for positively determining the coherence of a group. This criterion is based upon the notion of the perimeter of a map between two finite 2-complexes which is introduced here. In the groups to whic…

2002-12-31abs ↗pdf ↗

Paper describes profiles of multivariate normal distributions and novel estimators for mutual information.

problem Estimating mutual information for complex distributions.
method Analytical description of profiles, introduction of Bend and Mix Models, Monte Carlo estimation.
result Bend and Mix Models accurately estimate mutual information profiles and provide Bayesian estimates.

The study examines Kähler structures on coadjoint orbits of Lie groups using coherent and squeezed states.

problem Does the coadjoint orbits of Lie groups support a Kähler structure?
method Examined three Lie groups: Weyl-Heisenberg, SU(2), and SU(1,1). Used coherent and squeezed states to explore Kähler structures.
result Coherent states provide Kähler embeddings, while squeezed states only symplectic embeddings.

For arbitrary quantizable compact Kaehler manifolds, relations between the geometry given by the coherent states based on the manifold and the algebraic (projective) geometry realised via the coherent state mapping into projective space, are studied. Polar divisors, formulas relating the scalar products of coherent vec…

1999-03-17abs ↗pdf ↗