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.
Paper studies simplified trisections and their equivalence classes.
Calibration of simplified vine copulas using noise contrastive estimation
Simplified proof for Cheeger's isoperimetric constant.
A simplified trisection is a trisection map on a 4-manifold such that, in its critical value set, there is no double point and cusps only appear in triples on innermost fold circles. We give a necessary and sufficient condition for a 3-tuple of systems of simple closed curves in a surface to be a diagram of a simplifie…
Classifies 3-manifolds from simplified (2,0)-trisections of 4-manifolds.
Shapes of four dimensional spaces can be studied effectively via maps to standard surfaces. We explain, and illustrate by quintessential examples, how to simplify such generic maps on 4-manifolds topologically, in order to derive simple decompositions into much better understood manifold pieces. Our methods not only al…
Simplified proof of Honda-Huang's contact convexity result.
Study on nonorientable 4-manifolds using simplified fibrations and trisections.
A branched covering surface-knot is a surface-knot in the form of a branched covering over a surface-knot. For a branched covering surface-knot, we have a numerical invariant called the simplifying number. We show that branched covering surface-knots with degree three have the simplifying numbers less than three.
Simplified argument for second order estimate in quaternionic Calabi-Yau problem.
Residual Neural Networks (ResNets) achieve state-of-the-art performance in many computer vision problems. Compared to plain networks without residual connections (PlnNets), ResNets train faster, generalize better, and suffer less from the so-called degradation problem. We introduce simplified (but still nonlinear) vers…
We give a new algorithm to simplify a given triangulation with respect to a given curve. The simplification uses flips together with powers of Dehn twists in order to complete in polynomial time in the bit-size of the curve.
Simplified DGPs training by fixing inducing inputs to subset of data.
We compare two different bilateral counterparty valuation adjustment (BVA) formulas. The first formula is an approximation and is based on subtracting the two unilateral Credit Valuation Adjustment (CVA)'s formulas as seen from the two different parties in the transaction. This formula is only a simplified representati…
We consider a Black-Scholes market in which a number of stocks and an index are traded. The simplified Capital Asset Pricing Model is the conjunction of the usual Capital Asset Pricing Model, or CAPM, and the statement that the appreciation rate of the index is equal to its squared volatility plus the interest rate. (T…
Simplified optimization for structured matrices in deep learning.
Use simplified layerwise linear models to understand neural dynamics.
In this paper we describe a procedure to simplify any given triangulation of the 3-sphere using Pachner moves. We obtain an explicit exponential-type bound on the number of Pachner moves needed for this process. This leads to a new recognition algorithm for the 3-sphere.
Simplified analysis of diffusion models using discrete random variables.
New axioms for singquandles simplify applications and reveal algebraic aspects.
Simplified proofs and new distributions on anti-quasi-Sasakian manifolds.
Simplified proof of gluing formula for analytic torsion forms.
Unified analysis simplifies Johnson-Lindenstrauss lemma for data reduction.
The Min-Hashing approach to sketching has become an important tool in data analysis, information retrial, and classification. To apply it to real-valued datasets, the ICWS algorithm has become a seminal approach that is widely used, and provides state-of-the-art performance for this problem space. However, ICWS suffers…
A simplified tutorial on diffusion models for beginners.
In this article, we generalize the classification of genus one Lefschetz fibrations to genus one simplified broken Lefschetz fibrations, which have fibers of genera one and zero. We classify genus one Lefschetz fibrations over the 2-disk with certain non-trivial global monodromies using chart descriptions, and identify…
Simplified classification of special measures in CAT(-1) spaces.
Simplified approach to pseudo-Anosov flows on 3-manifolds.
Simplified and extended a method for rearranging infinite configurations of cubes.
Auroux, Donaldson and Katzarkov introduced broken Lefschetz fibrations as a generalization of Lefshcetz fibrations in order to describe near-symplectic 4-manifolds. We first study monodromy representations of higher sides of genus-1 simplified broken Lefschetz fibrations. We then completely classify diffeomorphism type…
Simplifies RF predictions by focusing on a subset of nearest neighbors.
The paper classifies knot Floer complexes of low width, simplifying knot bases.
Survey on metrics with conic singularities on Riemann surfaces.
We show that there exists a non-trivial simplified broken Lefschetz fibration which has infinitely many homotopy classes of sections. We also construct a non-trivial simplified broken Lefschetz fibration which has a section with non-negative square. It is known that no Lefschetz fibration satisfies either of the above …
Simplifies study of multivariate shortfall risk measures.
Constructs simplified or complexified simplicial complexes.
Simplified image clustering achieves competitive results without text-based embeddings.
The paper simplifies calculus for semimartingales using multiplicative compensation.
Simplified calculus for semimartingales makes complex transformations easier.
Deep learning using multi-layer neural networks (NNs) architecture manifests superb power in modern machine learning systems. The trained Deep Neural Networks (DNNs) are typically large. The question we would like to address is whether it is possible to simplify the NN during training process to achieve a reasonable pe…
We present explicit algorithms for simplifying the topology of indefinite fibrations on 4-manifolds, which include broken Lefschetz fibrations and indefinite Morse 2-functions. The algorithms consist of sequences of moves, which modify indefinite fibrations in smooth 1-parameter families. In particular, given an arbitr…
New method simplifies data analysis.
In a recent work "Arc-presentation of links: Monotonic simplification" Ivan Dynnikov showed that each rectangular diagram of the unknot, composite link, or split link can be monotonically simplified into a trivial, composite, or split diagram, respectively. The following natural question arises: Is it always possible t…
Simplifies neural network models by explicitly enforcing constraints in Cartesian coordinates.
Simplified Variational Bayes for easier inference.
The aim of this note is to extend the results in arXiv:1504.02043 to the case of approximate harmonic maps. More precisely, we will proved that the singular strata of an approximate harmonic map are k-rectifiable, and we will show effect bounds on the quantitative strata. In the process we will simplify many o…
Simplified neural network EFTs reveal a single critical condition.
Simplified analysis of SGD for linear regression with weight averaging.