Research
On-device research index

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.

168,695 papers · 148 categories

Trend · papers per month

0111 · Sep 200319922001200920172026
13 results for ISLE

Study reviews tree-based methods and introduces new ensemble strategies.

problem Improving the efficiency and performance of tree-based machine learning models.
method Review of tree-based methods, introduction of ISLE framework, ARM model combination strategy, and modified ISLEs.
result Performance evaluation of modified ISLEs on real data sets.

ISL improves causal structure learning with invariant structures across different environments.

problem Improving causal structure discovery for better generalization and explainability.
method ISL splits data into environments, learns invariant structures, and selects optimal classifiers based on graph structures.
result ISL accurately discovers causal structures and outperforms alternative methods on synthetic and real-world datasets.

Dual-ISL improves implicit generative model training with convex optimization and explicit density approximation.

problem Training implicit generative models with robust and practical likelihood-free objectives.
method Introduces dual-ISL, a novel likelihood-free objective using a convex divergence derived from the invariant statistical loss (ISL) framework.
result Dual-ISL yields a convex optimization problem in the space of model densities, providing explicit density approximation and improved training stability.

We improve generative models for heavy-tailed multivariate data using an invariant statistical loss.

problem Traditional generative models struggle with heavy-tailed and multivariate data, leading to unstable training and mode dropping.
method We extend the invariant statistical loss method to handle heavy-tailed and multivariate data using a Pareto-ISL generator trained with input noise from a generalised Pareto distribution.
result Pareto-ISL accurately models the tails of heavy-tailed distributions while capturing central characteristics.

In this article we explore an alternative approach to address deep exploration and we introduce the ISL algorithm, which is efficient at performing deep exploration. Similarly to maximum entropy RL, we derive the algorithm by augmenting the traditional RL objective with a novel regularization term. A distinctive featur…

2019-09-13abs ↗pdf ↗

Starfield optimizes satellite links for LEO mega-constellations by aligning ISLs with regional traffic patterns.

problem Forming a stable satellite topology in LEO mega-constellations with limited ISLs and unstable acquisition.
method Starfield uses a demand-aware heuristic algorithm based on traffic flows and Riemannian geometry to assign satellite links.
result Starfield reduces hop count and improves stretch factor by up to 30% compared to existing methods.

In this article supervised learning problems are solved using soft rule ensembles. We first review the importance sampling learning ensembles (ISLE) approach that is useful for generating hard rules. The soft rules are then obtained with logistic regression from the corresponding hard rules. In order to deal with the p…

2012-05-21abs ↗pdf ↗

Pseudo healthy synthesis, i.e. the creation of a subject-specific `healthy' image from a pathological one, could be helpful in tasks such as anomaly detection, understanding changes induced by pathology and disease or even as data augmentation. We treat this task as a factor decomposition problem: we aim to separate wh…

2019-01-10abs ↗pdf ↗

BESS shows potential in European markets for frequency support, but not for energy arbitrage.

problem Lack of profitability for BESS in energy arbitrage in most European markets.
method Proposed a general payoff model for BESS operation and calculated utilization factors for common applications.
result BESS shows higher potential in providing frequency support services, especially in Central Western and Northern Europe.

Ischaemic stroke is a medical condition caused by occlusion of blood supply to the brain tissue thus forming a lesion. A lesion is zoned into a core associated with irreversible necrosis typically located at the center of the lesion, while reversible hypoxic changes in the outer regions of the lesion are termed as the …

2019-08-03abs ↗pdf ↗

Deep learning model detects and corrects outliers in crowd-sourced weather data.

problem Data quality issues in crowd-sourced weather data.
method Bayesian deep learning approach with Gaussian-uniform mixture density network.
result Automated outlier detection in spatio-temporal environmental modeling.