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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.

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41 results for legacy

The Midwest Geometry Conference 2007 was devoted to the substantial mathematical legacy of Thomas P. Branson who passed away unexpectedly the previous year. This contribution to the Proceedings briefly introduces this legacy. We also take the opportunity of recording his bibliography. Thomas Branson was on the Editoria…

2008-04-02abs ↗pdf ↗

One major challenge for the legacy measurements at the LHC is that the likelihood function is not tractable when the collected data is high-dimensional and the detector response has to be modeled. We review how different analysis strategies solve this issue, including the traditional histogram approach used in most par…

2019-06-04abs ↗pdf ↗

This note summarizes in an informal way some geometric properties of Anosov representations into the symplectic group, which were presented in a talk at the conference What is Next. The mathematical legacy of Bill Thurston, held in June 2014 in Cornell.

2016-02-10abs ↗pdf ↗

This paper maps the insurability of AI risks across various insurance products.

problem Emerging AI risks and their implications for insurance coverage.
method Coding 55 AI threat classes against 26 insurance products using public carrier materials and threat catalogs.
result Identification of a four-tier insurability frontier: affirmatively insured, silent-AI exposures, actively excluded, and unstructured perils.

We briefly review results on nonlinear kinetic equation of Boltzmann type which describe the evolution of wealth in a simple agents market. The mathematical structure of the underlying kinetic equations allows to use well-known techniques of wide use in kinetic theory of rarefied gases to obtain information on the proc…

2010-05-27abs ↗pdf ↗

Article explores Thurston's circle packing theorem in 3-manifold geometry.

problem Understanding Thurston's circle packing theorem in 3-manifold geometry.
method Analyzes the Koebe-Andre'ev-Thurston Theorem and its relation to Thurston's circle packing theorem.
result Illustrates the significance of Thurston's circle packing theorem in 3-manifold geometry.

We present powerful new analysis techniques to constrain effective field theories at the LHC. By leveraging the structure of particle physics processes, we extract extra information from Monte-Carlo simulations, which can be used to train neural network models that estimate the likelihood ratio. These methods scale wel…

2018-04-30abs ↗pdf ↗

In this paper, we introduce the first method that (1) can complete kernel matrices with completely missing rows and columns as opposed to individual missing kernel values, (2) does not require any of the kernels to be complete a priori, and (3) can tackle non-linear kernels. These aspects are necessary in practical app…

2016-02-08abs ↗pdf ↗

Audited Conformal Prediction improves conditional coverage in pretrained models under distribution shift.

problem Uncertainty quantification for pretrained models under unknown distribution shift
method Leverages a small labeled dataset to train an audit model for marginal coverage, integrates outputs into conformal prediction framework
result Significantly higher conditional coverage than existing approaches

In his pioneering work from 1969, Jerry Levine introduced a complete set of invariants of algebraic concordance of knots. The evaluation of these invariants requires a factorization of the Alexander polynomial of the knot, and is therefore in practice often hard to realize. We thus propose the study of an alternative s…

2008-06-19abs ↗pdf ↗

Scaling relations, such as the IPAT equation and the Kaya identity, are useful for quickly gauging the scale of economic, technological, and demographic changes required to reduce environmental impacts and pressures; in the case of the Kaya identity, the environmental pressure is greenhouse gas emissions. However, when…

2011-12-04abs ↗pdf ↗

The paper extends gradient flow and relaxation studies to non-flat Riemannian manifolds.

problem Understanding gradient flows and relaxation in non-flat Riemannian manifolds.
method Developed a criterion for comparing relaxation along gradient descent curves using non-metricity tensor.
result Revealed a universal asymmetry: warming up is faster than cooling down.

aweSOM accelerates SOM clustering for large datasets.

problem Scalability issues in existing SOM implementations for large, multidimensional data.
method CPU/GPU-accelerated Self-organizing Maps (SOM) with ensemble stacking.
result 10-100x speed up and improved memory efficiency for large datasets.

We develop, discuss, and compare several inference techniques to constrain theory parameters in collider experiments. By harnessing the latent-space structure of particle physics processes, we extract extra information from the simulator. This augmented data can be used to train neural networks that precisely estimate …

2018-04-30abs ↗pdf ↗

GenAI improves actuarial practices through case studies.

problem Improving actuarial practices using AI.
method Four case studies using LLMs, Retrieval-Augmented Generation, and vision-enabled LLMs.
result GenAI enhances claim cost prediction, market comparisons, and car damage classification.

Solves challenges of drone communication in cellular networks.

problem Interference from drones to base stations in cellular networks.
method Derived analytical models, formulated optimization problem, transformed into machine learning problem, solved using deep reinforcement learning.
result Optimal handover and resource management policies for drones in cellular networks.

ReQuestNet simplifies 5G channel estimation with a unified model.

problem Complex channel estimation in 5G systems with varying conditions.
method Unified neural architecture that handles dynamic resource blocks and transmit layers.
result Significantly outperforms legacy methods, achieving up to 10dB gain at high SNRs.

Polylab is a MATLAB toolbox for multivariate polynomial modeling.

problem Efficiently modeling and manipulating multivariate polynomials across CPU and GPU.
method Unified symbolic-numeric interface, three aligned classes (MPOLY, MPOLY_GPU, MPOLY_HP), polynomial operations, differentiation, matrix computations.
result Advantages of MPOLY-HP for reduction-heavy simplification and large-scale computations, and the stochastic log-determinant variant for sparse regimes.

We take a closer look at the life and legacy of Micheal Milken. We discuss why Michael Milken, also know as the Junk Bond King, was not just any other King or run-of-the-mill Junk Dealer, but "The Junk Dealer". We find parallels between the three parts to any magic act and what Micheal Milken did, showing that his acco…

2019-10-17abs ↗pdf ↗

A quantum framework optimizes collateral allocation for derivatives.

problem Legal constraints and operational rules in collateral allocation for derivatives.
method Certified higher-order quantum framework that normalizes margin requirements and builds a bounded neighborhood of actions.
result Quantum framework improves certified sample quality compared to classical methods.

PICZL improves photometric redshifts for AGN in all-sky surveys.

problem Challenges in accurately computing photo-z for AGN due to interplay of SMBH and host galaxy emissions.
method PICZL uses an ensemble of CNNs with cross-channel integration of image and catalog data, leveraging Gaussian mixture models.
result PICZL achieves a photo-z variance of 4.5% and outlier fraction of 5.6% on a validation sample of 8098 AGN, outperforming previous methods.