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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.

168,742 papers · 148 categories

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285684112 · May 202619922001200920172026
48 results for affine regions

BN refines local partition geometry in piecewise-affine networks during training.

problem Understanding the effect of BN on the function realized during training in piecewise-affine networks.
method Analyzing the geometry of switching hyperplanes and affine-region partition conditioned on a mini-batch.
result BN increases expected local partition refinement in ReLU and piecewise-affine networks.

Improved bounds on neural network regions using activation histograms.

problem Bounding the number of affine regions in ReLU networks.
method Analysis of algebraic topology problem, extension of framework to subnetwork composition.
result Slightly tighter bounds and insights into parameter initialization.

We study the geometry of deep (neural) networks (DNs) with piecewise affine and convex nonlinearities. The layers of such DNs have been shown to be {\em max-affine spline operators} (MASOs) that partition their input space and apply a region-dependent affine mapping to their input to produce their output. We demonstrat…

2019-05-21abs ↗pdf ↗

In exchange for large quantities of data and processing power, deep neural networks have yielded models that provide state of the art predication capabilities in many fields. However, a lack of strong guarantees on their behaviour have raised concerns over their use in safety-critical applications. A first step to unde…

2019-10-09abs ↗pdf ↗

Geometrization says `` any closed oriented three-manifold which is prime (not a connected sum) carries one of the eight Thurston geometries OR it has incompressible torus walls whose complementary components each carry one of four particular Thurston geometries" (see Introduction and Figure 1). These geometric componen…

2019-06-26abs ↗pdf ↗

We consider deep feedforward neural networks with rectified linear units from a signal processing perspective. In this view, such representations mark the transition from using a single (data-driven) linear representation to utilizing a large collection of affine linear representations tailored to particular regions of…

2019-03-29abs ↗pdf ↗

Study growth patterns in random networks using i.i.d. perturbations.

problem Understanding the growth of affine regions in random piecewise-linear networks.
method Analyzes a random compositional model with i.i.d. perturbations of the tent map, proving submultiplicative pressure and using finite-state defect process for upper-tail lower bounds.
result Proves the existence of a submultiplicative pressure for \(N_n\) and gives exponential upper bounds for \(n^{-1}\log N_n\).

A generalized semitoric system F:=(J,H): M --> R^2 on a symplectic 4-manifold is an integrable system whose essential properties are that F is a proper map, its set of regular values is connected, J generates an S^1-action and is not necessarily proper. These systems can exhibit focus-focus singularities, which corresp…

2013-07-29abs ↗pdf ↗

AntBO optimizes antibody design using Bayesian optimization for efficient and effective CDRH3 sequence generation.

problem Designing optimal antigen-specific CDRH3 regions in antibody design due to combinatorial sequence space.
method Combinatorial Bayesian optimization framework with trust region for developability.
result AntBO designs CDRH3 regions with diverse biophysical properties and outperforms existing methods.

This work generalizes bounds on the number of linear regions in CPWL NNs.

problem Determining the number of linear regions in CPWL neural networks is challenging.
method Generalized bounds on the maximal number of linear regions for arbitrary CPWL activation functions.
result Depth significantly increases the number of linear regions, but not exponentially.

New insights into how neural networks classify data.

problem Understanding the topological structure of decision regions in ReLU networks.
method Defining generic and transversal ReLU networks, and using linear complexes to identify obstructions.
result Generic, transversal ReLU networks have at most one bounded connected component in their decision regions.

We consider clustering problems where the goal is to determine an optimal partition of a given point set in Euclidean space in terms of a collection of affine subspaces. While there is vast literature on heuristics for this kind of problem, such approaches are known to be susceptible to poor initializations and getting…

2016-07-25abs ↗pdf ↗

The paper explores how ReLU DNNs can represent MPC policies and vice versa.

problem Representing MPC policies as ReLU DNNs and vice versa.
method Developed an approximate method for identifying input-space in ReLU nets resulting in PWA functions over polyhedral regions. Studied inverse multiparametric linear or quadratic programs for reconstruction of constraints and cost functions given a PWA function.
result Identification and representation of MPC policies as ReLU DNNs and vice versa.

POLICE enforces linear constraints on deep neural networks efficiently.

problem Enforcing constraints on deep neural networks without affecting optimization.
method Provably optimal affine constraint enforcement method that minimally modifies DNNs.
result POLICE ensures DNNs fulfill affine constraints during training and testing.

ATSM are widely applied for pricing of bonds and interest rate derivatives but the consistency of ATSM when the short rate, r, is unbounded from below remains essentially an open question. First, the standard approach to ATSM uses the Feynman-Kac theorem which is easily applicable only when r is bounded from below. Sec…

2004-04-05abs ↗pdf ↗

New method calibrates reference distributions for bounded support.

problem Lack of principled method for bounded-support statistical reference distributions.
method Formulated maximum entropy on projective space of nonnegative measures.
result Prescribed acceptance region uniquely determines deformation parameter.

Efficiently finds sparse solutions to max-plus equations for convex regression.

problem Finding sparse solutions to max-plus equations for convex multivariate regression.
method Polynomial-time algorithm for sparse approximate solutions.
result Optimal piecewise-linear fitting with minimum number of regions.

Generative networks are analyzed using spline operators to understand their properties and limitations.

problem Understanding and optimizing the properties of deep generative networks.
method Characterizing latent space partition, manifold dimension, and disentanglement using spline operators.
result Characterized the latent space partition, manifold dimension, and disentanglement of GDNs.

SC unifies ICL calibration methods and improves LLM performance.

problem Systematic biases in LLM predictions leading to unstable performance.
method Supervised Calibration (SC) learns optimal affine transformations in logit space.
result SC delivers state-of-the-art performance across multiple datasets.

Batch normalization improves deep networks by aligning their decision boundaries with data.

problem Improving the performance and generalization of deep networks.
method Theoretical analysis of batch normalization as a function approximation technique for continuous piecewise affine splines.
result Batch normalization adapts the geometry of a deep network's partition to match the data, improving learning and generalization.

We consider the optimal investment problem when the traded asset may default, causing a jump in its price. For an investor with constant absolute risk aversion, we compute indifference prices for defaultable bonds, as well as a price for dynamic protection against default. For the latter problem, our work complements S…

2017-02-28abs ↗pdf ↗

We study affine maps between affine manifolds. Even when the fibers are compact and diffeomorphic, two of them can inherit different affine structures from the source space. This leads to a fixed linear holonomy deformation theory of the affine structure of an affine manifold. We found various conditions which make the…

2001-05-22abs ↗pdf ↗

In this article, we propose the notion of the general pp-affine capacity and prove some basic properties for the general pp-affine capacity, such as affine invariance and monotonicity. The newly proposed general pp-affine capacity is compared with several classical geometric quantities, e.g., the volume, the pp-var…

2017-05-21abs ↗pdf ↗

An affine manifold is a manifold with torsion-free flat affine connection. A geometric topologist's definition of an affine manifold is a manifold with an atlas of charts to the affine space with affine transition functions; a radiant affine manifold is an affine manifold with holonomy consisting of affine transformati…

1997-12-19abs ↗pdf ↗

Two families of general affine surface areas are introduced. Basic properties and affine isoperimetric inequalities for these new affine surface areas as well as for LφL_φ affine surface areas are established.

2009-08-15abs ↗pdf ↗

This thesis is devoted to the study of affine processes and their applications in financial mathematics. In the first part we consider the theory of time-inhomogeneous affine processes on general state spaces. We present a concise setup for time-inhomogeneous Markov processes. For stochastically continuous affine proce…

2015-12-10abs ↗pdf ↗

A (flat) affine 33-manifold is a 33-manifold with an atlas of charts to an affine space R3\mathbb{R}^3 with transition maps in the affine transformation group Aff(R3)\mathrm{Aff}(\mathbb{R}^3). We will show that a connected closed affine 33-manifold is either an affine Hopf 33-manifold or decomposes canonically to conca…

2014-11-05abs ↗pdf ↗

We study affine Jacobi structures on an affine bundle π:AMπ:A\to M, i.e. Jacobi brackets that close on affine functions. We prove that there is a one-to-one correspondence between affine Jacobi structures on AA and Lie algebroid structures on the vector bundle A+=pMAff(Ap,R)A^+=\bigcup_{p\in M}Aff(A_p,\R) of affine functionals. Som…

2002-12-04abs ↗pdf ↗

Paper shows affine constraint is unnecessary for high-dimensional data.

problem The necessity of an affine constraint in affine subspace clustering.
method Theoretical and empirical analysis of conditions for correctness of affine subspace clustering methods.
result Affine constraint has negligible effect on clustering performance for high-dimensional data.

In this paper we discuss some affine properties of convex equal-area polygons, which are convex polygons such that all triangles formed by three consecutive vertices have the same area. Besides being able to approximate closed convex smooth curves almost uniformly with respect to affine length, convex equal-area polygo…

2011-03-14abs ↗pdf ↗

An affine Cartan calculus is developed. The concepts of special affine bundles and special affine duality are introduced. The canonical isomorphisms, fundamental for Lagrangian and Hamiltonian formulations of the dynamics in the affine setting are proved.

2003-03-05abs ↗pdf ↗

Calculates affine transformations for specific homogeneous spaces.

problem Computing groups of affine transformations on homogeneous spaces.
method Analyzes conditions for affine connections and uses them to establish group isomorphisms.
result Groups of affine transformations are locally isomorphic under specified conditions.

In this paper, we introduce a new structure, namely, affine Szabó connection. We prove that, on 22-dimensional affine manifolds, the affine Szabó structure is equivalent to one of the cyclic parallelism of the Ricci tensor. A characterization for locally homogeneous affine Szabó surface is obtained. Examples of two- a…

2016-04-19abs ↗pdf ↗

In this paper, we introduce a new parameter, the affine twist parameter for the affine deformation of a sphere with holes. We show that the affine deformation space can be parametrized by Margulis invariants and affine twist parameters. The affine twist parameter is canonically regarded as a correspondence to the Fench…

2015-06-01abs ↗pdf ↗

The paper studies a new class of affine maximal surfaces with singularities.

problem Understanding the properties of affine maximal surfaces with singularities.
method Defining a new subclass of affine maximal surfaces and applying Euclidean minimal surface theory.
result Affine maxfaces satisfy an Osserman-type inequality and do not contain non-trivial improper affine fronts.