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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.

168,694 papers · 148 categories

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75150224299 · Jun 202019922001200920172026
48 results for weight modules

Combinatorial approach to compute satellite knot invariants using graph theory.

problem Computing knot invariants for satellite knots using bordered Heegaard Floer homology.
method Construct weighted AA_\infty-modules using decorated planar graphs and prove their isomorphism.
result Combinatorial proof of AA_\infty structure relations for the constructed modules.

L-modules are a combinatorial analogue of constructible sheaves on the reductive Borel-Serre compactification of a locally symmetric space. We define the micro-support of an L-module; it is a set of irreducible modules for the Levi quotients of the parabolic Q-subgroups associated to the strata. We prove a vanishing th…

2001-12-22abs ↗pdf ↗

Laplacian matrices of weighted graphs in surfaces SS are used to define module and polynomial invariants of Z/2Z/2-homologically trivial links in S×[0,1]S \times [0,1]. Information about virtual genus is obtained.

2020-02-24abs ↗pdf ↗

Verma Howe duality connects tensor products of Verma modules to LKB representations.

problem Understanding the relationship between tensor products of Verma modules and LKB representations.
method Established a quantized version of Verma Howe duality and used it to prove the simplicity of LKB representations.
result LKB representations arise from the quantized Verma Howe duality and are shown to be simple modules.

This note is dedicated to the study of a Hopf module structures on the space of framed chord diagrams and framed graphs. We also introduce a framed version of the chromatic polynomial and propose two methods to construct framed weight systems.

2014-03-31abs ↗pdf ↗

In this work, we propose a novel meta-learning approach for few-shot classification, which learns transferable prior knowledge across tasks and directly produces network parameters for similar unseen tasks with training samples. Our approach, called LGM-Net, includes two key modules, namely, TargetNet and MetaNet. The …

2019-05-15abs ↗pdf ↗

As an effective data preprocessing step, feature selection has shown its effectiveness to prepare high-dimensional data for many machine learning tasks. The proliferation of high di-mension and huge volume big data, however, has brought major challenges, e.g. computation complexity and stability on noisy data, upon exi…

2019-02-28abs ↗pdf ↗

New homological results for bordered Floer algebras derived from hypertoric categories.

problem Homological properties of bordered Floer algebras.
method Affine quasi hereditary property of equivariant hypertoric convolution algebras and computation of Ext groups.
result Existence of standard modules and isomorphism of Ext groups to bordered strands dg algebras.

Spatio-temporal (ST) data, which represent multiple time series data corresponding to different spatial locations, are ubiquitous in real-world dynamic systems, such as air quality readings. Forecasting over ST data is of great importance but challenging as it is affected by many complex factors, including spatial char…

2018-09-28abs ↗pdf ↗

The paper is motivated by the study of graded representations of Takiff algebras, cominuscule parabolics, and their generalizations. We study certain special subsets of the set of weights (and of their convex hull) of the generalized Verma modules (or GVM's) of a semisimple Lie algebra $\lie g$. In particular, we exten…

2010-05-07abs ↗pdf ↗

This research explores complex-valued neural networks and their implementation.

problem The challenges of implementing complex-valued neural networks and their potential for non-complex data.
method Detailed theory and implementation of CVNN, including Wirtinger calculus, complex backpropagation, and modules like complex layers and activation functions. Python implementation using cvnn toolbox.
result Demonstrates the potential of CVNN for non-complex data through simulations.

A {\em balanced} spatial graph has an integer weight on each edge, so that the directed sum of the weights at each vertex is zero. We describe the Alexander module and polynomial for balanced spatial graphs (originally due to Kinoshita \cite{ki}), and examine their behavior under some common operations on the graph. We…

2015-06-19abs ↗pdf ↗

We consider the aff(n1)\mathfrak{aff}(n|1)-module structure on the spaces of differential bilinear operators acting on the superspaces of weighted densities. We classify aff(n1)\mathfrak{aff}(n|1)-invariant binary differential operators acting on the spaces of weighted densities. This result allows us to compute the first $\math…

2018-02-03abs ↗pdf ↗

Paper proposes a new pipeline for few-shot classification using forget-update module and channel vector sequence.

problem Few-shot classification with limited support samples.
method Channel vector sequence construction module and forget-update module.
result Pipeline achieves state-of-the-art results on various datasets.

The paper proves a Hard Lefschetz Theorem for push-forwards of polarized twistor modules.

problem Proving a Hard Lefschetz Theorem for push-forwards of polarized twistor modules.
method Using Kashiwara and Kawai's theorem on Hodge structures and regular polarized twistor modules.
result Proves the Hard Lefschetz Theorem for push-forwards of polarized twistor modules.

For p>3 a prime, and g>2 an integer, we use Topological Quantum Field Theory (TQFT) to study a family of p-1 highest weight modules L_p(lambda) for the symplectic group Sp(2g,K) where K is an algebraically closed field of characteristic p. This permits explicit formulae for the dimension and the formal character of L_p…

2016-06-30abs ↗pdf ↗

We introduce a quotient of the affine Temperley-Lieb category that encodes all weight-preserving linear maps between finite-dimensional sl(2)-representations. We study the diagrammatic idempotents that correspond to projections onto extremal weight spaces and find that they satisfy similar properties as Jones-Wenzl pro…

2017-01-09abs ↗pdf ↗

Let F_λ(S1){\cal F}\_λ(S^1) be the space of tensor densities of degree (or weight) λλ on the circle S1S^1. The space Dk_λ,μ(S1){\cal D}^k\_{λ,μ}(S^1) of kk-th order linear differential operators from F_λ(S1){\cal F}\_λ(S^1) to F_μ(S1){\cal F}\_μ(S^1) is a natural module over Diff(S1)\mathrm{Diff}(S^1), the diffeomorphism group of S1S^1. We deter…

2005-06-16abs ↗pdf ↗

We study a notion of pre-quantization for bb-symplectic manifolds. We use it to construct a formal geometric quantization of bb-symplectic manifolds equipped with Hamiltonian torus actions with nonzero modular weight. We show that these quantizations are finite dimensional TT-modules.

2016-08-30abs ↗pdf ↗

The main result of this paper is the following: any `weighted' Riemannian manifold (M,g,μ)(M,g,μ) - i.e. endowed with a generic non-negative Radon measure μμ - is `infinitesimally Hilbertian', which means that its associated Sobolev space W1,2(M,g,μ)W^{1,2}(M,g,μ) is a Hilbert space. We actually prove a stronger result: the abstrac…

2018-09-16abs ↗pdf ↗

We consider framed chord diagrams, i.e. chord diagrams with chords of two types. It is well known that chord diagrams modulo 4T-relations admit Hopf algebra structure, where the multiplication is given by any connected sum with respect to the orientation. But in the case of framed chord diagrams a natural way to define…

2015-06-30abs ↗pdf ↗

We propose two new approaches to the Tannakian Galois groups of holonomic D-modules on abelian varieties. The first is an interpretation in terms of principal bundles given by the Fourier-Mukai transform, which shows that they are almost connected. The second constructs a microlocalization functor relating characterist…

2016-04-08abs ↗pdf ↗

Extends hyperparameter transfer across model sizes and modules, improving training speed.

problem Training stability and performance of large-scale models with optimal hyperparameters.
method Complete(d)^{(d)} Parameterisation, per-module hyperparameter optimisation and transfer.
result Hyperparameter transfer holds even in the per-module hyperparameter regime, improving training speed.

We introduce an autoregressive-type model of prices in financial market taking into account the self-modulation effect. We find that traders are mainly using strategies with weighted feedbacks of past prices. These feedbacks are responsible for the slow diffusion in short times, apparent trends and power law distributi…

2003-12-20abs ↗pdf ↗

We propose a new nonlinear factorization model for graphs that are with topological structures, and optionally, node attributes. This model is based on a pseudometric called Gromov-Wasserstein (GW) discrepancy, which compares graphs in a relational way. It estimates observed graphs as GW barycenters constructed by a se…

2019-11-19abs ↗pdf ↗

Let X be a locally symmetric space associated to a reductive algebraic group G defined over Q. L-modules are a combinatorial analogue of constructible sheaves on the reductive Borel-Serre compactification of X; they were introduced in [math.RT/0112251]. That paper also introduced the micro-support of an L-module, a com…

2004-12-20abs ↗pdf ↗

A new method for feature fusion in U-Net decoders using difference-based gating.

problem Precise fusion of high-level semantics and low-level details in U-Net decoder reconstruction.
method Proposes two difference-based gating approaches: Feature-difference gating (FDG) and Entropy-difference gating (EDG).
result Both FDG and EDG methods outperform existing attention-based fusion methods, with EDG showing superior performance.

KM method reduces ConvNet parameters to 9% higher accuracy with minimal additional memory.

problem Expensive memory usage for training ConvNets on embedded devices.
method Kernel Modulation (KM) method that adapts all network parameters for each task.
result KM delivers up to 9% higher accuracy than other parameter-efficient methods.

Pion optimizes LLMs by preserving weight matrix singular values.

problem Training large language models (LLMs) with standard optimizers leads to unstable weight matrices.
method Pion uses orthogonal transformations to update weight matrices, preserving their singular values.
result Pion offers a stable alternative to standard optimizers for LLM pretraining and finetuning.

New Bol operators found for supermanifolds with specific dimensions.

problem Finding invariant differential operators for supermanifolds.
method Described analogs of Bol operators for pgl(a+1b)\mathfrak{pgl}(a+1\vert b)-invariant differential operators.
result Many new differential operators discovered for (ab)=(20),(03)(a|b)=(2|0), (0|3) and 111\vert 1-dimensional superstring.

Weibull framework diagnoses transformer weight distributions, revealing distinct patterns across modules.

problem Diagnosing weight distributions in transformer models for better understanding of training dynamics.
method Applied Weibull distribution to diagnose weight magnitude distributions in transformer models, fitting each weight matrix independently.
result Distinct patterns of weight distributions across different transformer modules were identified.