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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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5101419 · Jun 202019922001200920182026
48 results for excision trick

In this article, we introduce the notion of a functor on coarse spaces being coarsely excisive- a coarse analogue of the notion of a functor on topological spaces being excisive. Further, taking cones, a coarsely excisive functor yields a topologically excisive functor, and for coarse topological spaces there is an ass…

2010-02-24abs ↗pdf ↗

Study contact structures and sutured monopole Floer homology, computing and deriving formulas.

problem Understanding the relationship between contact structures and sutured monopole Floer homology.
method Exploring contact elements under Floer excisions, computing sutured monopole Floer homology, and deriving formulas.
result Obtained exact triangles and connected sum formulas for sutured monopole Floer homology.

Relates two types of skein algebras using explicit correspondences.

problem Defining and relating stated and internal skein algebras.
method Explicit correspondence between stated and internal skein algebras, distinguishing between left and right boundary edges, proving excision properties.
result Agrees with excision properties of stated skein algebras under specific conditions.

Formulae prove equivalence of two invariants on specific 4-manifolds.

problem Equivalence of two invariants on homology S1imesS3S^1 imes S^3.
method Surgery and excision formulas for Furuta-Ohta invariant λFOλ_{FO}.
result Computes λFOλ_{FO} of certain families of manifolds.

New mapping class group actions on Hochschild complexes for modular categories.

problem Understanding actions of mapping class groups on Hochschild complexes of modular categories.
method Construction of a symmetric monoidal functor with excision property.
result Homotopy coherent projective action of mapping class groups on Hochschild complexes.

Paper compares higher torsions and removes fiberwise Morse function assumption.

problem Comparing higher torsions from analytic and topological perspectives.
method Introduced fiberwise generalized Morse functions (GMFs) and excised neighborhoods around birth-death points.
result Established a generalized version of the higher Cheeger-Müller/Bismut-Zhang theorem.

The Gumbel-max trick and its extensions simplify sampling from categorical distributions in machine learning.

problem Sampling from categorical distributions with unnormalized probabilities.
method Extensions of the Gumbel-max trick for various applications.
result Simplified and efficient methods for sampling and gradient estimation.

A new gradient estimator for categorical distributions reduces bias and variance.

problem Intractability of gradients for categorical distributions in discrete latent variable models.
method CatLog-Derivative trick and IndeCateR gradient estimator.
result IndeCateR reduces bias and variance of gradients for categorical distributions.

Expands Bredon's trick for applications in geometry and topology.

problem Local-to-global extension principles in geometric and topological contexts.
method Novel applications and frameworks for stratified pseudomanifolds, Ricci flow, and persistent homology.
result Establishes Bredon's trick as a unifying framework.

We develop an epsilon-controlled algebraic L-theory, extending our earlier work on epsilon-controlled algebraic K-theory. The controlled L-theory is very close to being a generalized homology theory; we study analogues of the homology exact sequence of a pair, excision properties, and the Mayer--Vietoris exact sequence…

2004-02-13abs ↗pdf ↗

We observe that gradients computed via the reparameterization trick are in direct correspondence with solutions of the transport equation in the formalism of optimal transport. We use this perspective to compute (approximate) pathwise gradients for probability distributions not directly amenable to the reparameterizati…

2018-06-05abs ↗pdf ↗

The Gumbel trick is a method to sample from a discrete probability distribution, or to estimate its normalizing partition function. The method relies on repeatedly applying a random perturbation to the distribution in a particular way, each time solving for the most likely configuration. We derive an entire family of r…

2017-06-13abs ↗pdf ↗

An online reinforcement learning algorithm is anytime if it does not need to know in advance the horizon T of the experiment. A well-known technique to obtain an anytime algorithm from any non-anytime algorithm is the "Doubling Trick". In the context of adversarial or stochastic multi-armed bandits, the performance of …

2018-03-19abs ↗pdf ↗

We prove a generalization of Bennequin's inequality for Legendrian knots in a 3-dimensional contact manifold (Y,xi), under the assumption that Y is the boundary of a 4-dimensional manifold M and the version of Seiberg-Witten invariants introduced by Kronheimer and Mrowka [Invent. Math. 130 (1997) 209-255] is nonvanishi…

2004-10-26abs ↗pdf ↗

In this paper, we study a certain cohomology attached to a smooth function, which arose naturally in Poisson geometry. We explain how this cohomology depends on the function, and we prove that it satisfies both the excision and the Mayer-Vietoris axioms. For a regular function we show that the cohomology is related to …

2002-12-03abs ↗pdf ↗

Inference in popular nonparametric Bayesian models typically relies on sampling or other approximations. This paper presents a general methodology for constructing novel tractable nonparametric Bayesian methods by applying the kernel trick to inference in a parametric Bayesian model. For example, Gaussian process regre…

2011-03-09abs ↗pdf ↗

New methods for estimating gradients of expectations using pairwise interactions.

problem Estimating gradients of expectations for complex models.
method Introducing new pairwise stochastic gradient estimators based on the log-derivative trick and reparameterisation.
result New estimators are unbiased and offer variance reduction compared to the log-derivative estimator.

We define a cobordism category of topological manifolds and prove that if d4d \neq 4 its classifying space is weakly equivalent to Ω1MTTop(d)Ω^{\infty -1} MTTop(d), where MTTop(d)MTTop(d) is the Thom spectrum of the inverse of the canonical bundle over BTop(d)BTop(d). We also give versions with tangential structures and boundary. The pro…

2018-10-11abs ↗pdf ↗

Boltzmann machines (BMs) are appealing candidates for powerful priors in variational autoencoders (VAEs), as they are capable of capturing nontrivial and multi-modal distributions over discrete variables. However, non-differentiability of the discrete units prohibits using the reparameterization trick, essential for lo…

2018-05-18abs ↗pdf ↗