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.
ReliefE ranks features faster and better in high-dimensional data.
Feature selection plays a critical role in biomedical data mining, driven by increasing feature dimensionality in target problems and growing interest in advanced but computationally expensive methodologies able to model complex associations. Specifically, there is a need for feature selection methods that are computat…
Model analyzes mortgage relief during financial hardship.
Basel III introduces new capital charges for CVA. These charges, and the Basel 2.5 default capital charge can be mitigated by CDS. Therefore, to price in the capital relief that CDS contracts provide, we introduce a CDS pricing model with three legs: premium; default protection; and capital relief. If markets are compl…
Estimates funding impact from an algorithmic relief rule, finding little effect on hospital activities.
RGRR allocates between QQQ and DIA based on relative states, improving Sharpe and CAGR.
A scheme for UAVs to borrow spectrum from terrestrial networks for disaster relief.
Proposes semi-supervised feature ranking for handling high-dimensional, unlabeled data.
The cost of belief changes with precision and is a hyperbolic geometry.
A framework for cost of belief revision in uncertain agents.
Machine learning improves ASD diagnosis accuracy.
In this paper we introduce a new feature selection algorithm to remove the irrelevant or redundant features in the data sets. In this algorithm the importance of a feature is based on its fitting to the Catastrophe model. Akaike information crite- rion value is used for ranking the features in the data set. The propose…
Relief based algorithms have often been claimed to uncover feature interactions. However, it is still unclear whether and how interaction terms will be differentiated from marginal effects. In this paper, we propose IMMIGRATE algorithm by including and training weights for interaction terms. Besides applying the large …
Between 2003 and 2015 the prices of apartments in Hong Kong (adjusted for inflation) increased by a factor of 3.8. This is much higher than in the United States prior to the so-called subprime crisis of 2007. The analysis of this speculative episode confirms the mechanism and regularities already highlighted by the pre…
This paper proposes a continuous timing strategy for growth vs. defensive style allocation.
We present our first efforts in building an automatic speech recognition system for Somali, an under-resourced language, using 1.57 hrs of annotated speech for acoustic model training. The system is part of an ongoing effort by the United Nations (UN) to implement keyword spotting systems supporting humanitarian relief…
Retirement gratuity is the money companies typically pay their employees at the end of their contracts or at the time of leaving the company. It is a defined benefit plan and is often given as an alternative to a pension plan. In Botswana, there is now a new pattern whereby companies give their employees the option to …
With the advent of Big Data era, data reduction methods are highly demanded given its ability to simplify huge data, and ease complex learning processes. Concretely, algorithms that are able to filter relevant dimensions from a set of millions are of huge importance. Although effective, these techniques suffer from the…
Bayesian optimization is popular for optimizing time-consuming black-box objectives. Nonetheless, for hyperparameter tuning in deep neural networks, the time required to evaluate the validation error for even a few hyperparameter settings remains a bottleneck. Multi-fidelity optimization promises relief using cheaper p…
We consider multilingual bottleneck features (BNFs) for nearly zero-resource keyword spotting. This forms part of a United Nations effort using keyword spotting to support humanitarian relief programmes in parts of Africa where languages are severely under-resourced. We use 1920 isolated keywords (40 types, 34 minutes)…
Paper presents a model for identifying informative COVID-19 tweets.
In this paper, the authors aim to combine the latest state of the art models in image recognition with the best publicly available satellite images to create a system for landslide risk mitigation. We focus first on landslide detection and further propose a similar system to be used for prediction. Such models are valu…
Twitter is recently being used during crises to communicate with officials and provide rescue and relief operation in real time. The geographical location information of the event, as well as users, are vitally important in such scenarios. The identification of geographic location is one of the challenging tasks as the…
Develops a two-layer model to design mortgage assistance products.
New insights into how to inspect and learn from multi-stage processes and AI reasoning.
New method estimates active subspaces for jump-discontinuous functions.
We compare features for dynamic time warping (DTW) when used to bootstrap keyword spotting (KWS) in an almost zero-resource setting. Such quickly-deployable systems aim to support United Nations (UN) humanitarian relief efforts in parts of Africa with severely under-resourced languages. Our objective is to identify aco…
Improved agnostic boosting with better sample efficiency.
Unified RMOT framework for non-modelable risk factors reduces audit bounds.
DeepBark improves tree bark re-identification accuracy.
Implementing large-scale deep neural networks with high computational complexity on low-cost IoT devices may inevitably be constrained by limited computation resource, making the devices hard to respond in real-time. This disjunction makes the state-of-art deep learning algorithms, i.e. CNN (Convolutional Neural Networ…
Algorithmic insurance tackles financial risks from AI errors, proving CVaR-optimal thresholds reduce tail risk.
End-to-end deep learning detects emotions in real-life emergency calls.
This manuscript presents the following: (1) an improved version of the Binary Simultaneous Perturbation Stochastic Approximation (SPSA) Method for feature selection in machine learning (Aksakalli and Malekipirbazari, Pattern Recognition Letters, Vol. 75, 2016) based on non-monotone iteration gains computed via the Barz…
New metric -coherence measures gradient alignment during training, revealing surprising memorization patterns.
Bayesian model uses mobile data to assess business resilience after hurricanes.
Constructs families of Toeplitz operators for symplectic fibrations.
In the paper we formulate and derive the family blowup formula of family Seiberg-Witten invariants. The formula has been used in the enumerative application of counting singular curves on algebraic surfaces. We first give a topological derivation of the formula by using family index theorem. Then we define the algebrai…
Proves an equivariant version of index theorem for geometric families.
Squared families are a new model class derived from linear transformations, offering convenient properties and universal approximation.
Smooth families of biholomorphisms between strongly pseudoconvex domains are shown to be smooth.
Computes Seiberg-Witten invariants for Kähler families of 4-manifolds.
We investigate families of Legendrian submanifolds of 1-jet spaces by developing and applying a theory of families of generating family homologies. This theory allows us to detect an infinite family of loops of Legendrian n-spheres embedded in the standard contact (2n+1)-space (for n>1) that are contractible in the smo…
Study families of flat connections with nilpotent Higgs fields, showing similar monodromy to regular Higgs bundles.
Tangential families are 1-parameter families of rays emanating tangentially from smooth curves. We classify tangential family germs up to Left-Right equivalence: we prove that there are two infinite series and four sporadic simple singularities of tangential family germs (in addition to two stable singularities). We gi…
Study families of Morse functions for manifolds with boundary.
We consider the local analytic behavior for a family of holomorphic differentials on a family of degenerating annuli. Three results and discussion are presented. The first is the normal families Lemma 1. The second is an isomorphism of sheaves, formula (3), giving a direct description of families of regular -differe…
Extends width estimates to family case using index theory.