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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.

168,695 papers · 148 categories

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171342512683 · Jun 202019922001200920172026
48 results for totally reducible representations

Researchers describe character varieties for Hopf links, proving geometric properties.

problem Character variety geometry of Hopf links with nn twists.
method Geometric descriptions of irreducible and totally reducible representations.
result Complete geometric description of SU(2)\mathrm{SU}(2)-character variety for r=2r=2.

Study homogeneous Lorentzian manifolds under reductive Lie groups, reducing descriptions to semisimple groups.

problem Characterize homogeneous Lorentzian manifolds under reductive Lie groups.
method Analyze manifolds M=G/LM = G/L for connected reductive Lie groups GG and reductive subgroup LL; focus on totally reducible isotropy representations.
result Homogeneous Lorentzian manifolds reduce to semisimple Lie groups, and are reductive.

We give explicit equations that describe the character variety of the figure eight knot for the groups SL(3,C), GL(3,C) and PGL(3,C). This has five components of dimension 2, one consisting of totally reducible representations, another one consisting of partially reducible representations, and three components of irred…

2015-05-17abs ↗pdf ↗

Characterizes totally elliptic surface group representations into Lie groups.

problem Understanding totally elliptic surface group representations into Lie groups.
method Characterization of representations into PSL2R\mathrm{PSL}_2\mathbb{R} and PSL2C\mathrm{PSL}_2\mathbb{C} by their mapping properties.
result They are either into a compact subgroup or Deroin--Tholozan representations.

A totally geodesic map f:X1X2f:\mathcal X_1\to\mathcal X_2 between Hermitian symmetric spaces is tight if its image contains geodesic triangles of maximal area. Tight maps were first introduced in [BIW09], and were classified in [Ham13, Ham14, HO14] in the case of irreducible domain. We complete the classification by analy…

2014-12-19abs ↗pdf ↗

Paper addresses the disparity between sampled and mean representations in disentangled learning.

problem Disparity between sampled and mean representations in disentangled learning.
method Proposes a method to eliminate the disparity by proving and utilizing the relationship between total correlation of sampled and mean representations for multivariate normal distributions.
result Demonstrates that a factorized mean representation can have lower total correlation than the sampled representation.

That announcement gives the structure of totally reducible linear Lie algebras which are the Lie algebra of the holonomy group of (at least) one torsion-free connection. The result uses the (already known) classi cation of the irreducible ones and some previous (unpublished) works by the author giving the classi cation…

2013-04-09abs ↗pdf ↗

Character varieties of knot groups into SU(3) are stratified and analyzed.

problem Characterizing representations of knot groups into SU(3).
method Stratification of character variety into reducible, 2D+1D, and irreducible representations.
result Homotopy equivalence between SU(3) and SL(3,C) character varieties.

Geometrically represents path integral reduction Jacobian for interacting systems.

problem Quantizing a model mechanical system with dependent coordinates.
method Geometric representation using scalar curvature and Christoffel symbols in a nonholonomic basis.
result Found a geometric representation for the path integral reduction Jacobian.

We consider strict and complete nearly Kaehler manifolds with the canonical Hermitian connection. The holonomy representation of the canonical Hermitian connection is studied. We show that a strict and complete nearly Kaehler is locally a Riemannian product of homogenous nearly Kaehler spaces, twistor spaces over quate…

2002-03-05abs ↗pdf ↗

Proposes TCWAE to learn disentangled representations using the Wasserstein Autoencoder.

problem Balancing reconstruction fidelity and disentanglement in learning representations.
method TCWAE (Total Correlation Wasserstein Autoencoder) using different KL estimators.
result Competitive results on data sets with known generative factors, and improved reconstructions on unknown factors.

For any Legendrian knot KK in standard contact R3{\mathbb R}^3 we relate counts of ungraded (11-graded) representations of the Legendrian contact homology DG-algebra (A(K),)(\mathcal{A}(K),\partial) with the nn-colored Kauffman polynomial. To do this, we introduce an ungraded nn-colored ruling polynomial, Rn,K1(q)R^1_{n,K}(q)

2019-08-23abs ↗pdf ↗

New proofs given for space curves with totally positive torsion.

problem Description of convex hulls of space curves with totally positive torsion.
method New proofs of parametric representation, surface area, and volume formulas.
result Recovery of formulas for convex hull's surface area and volume.

Characterizes components of representations space for punctured surfaces.

problem Characterizing connected components of representations space.
method Using relative Euler classes, signs of peripheral elements, and generalized Milnor-Wood inequality.
result Counted total number of connected components of type-preserving representations.

Let ΓΓ be a non-uniform lattice in PU(p,1)PU(p,1) without torsion and with p2p\geq2 . We introduce the notion of volume for a representation ρ:ΓPU(m,1)ρ:Γ\rightarrow PU(m,1) where mpm \geq p. We use this notion to generalize the Mostow--Prasad rigidity theorem. More precisely, we show that given a sequence of representations $ρ_n:…

2017-11-03abs ↗pdf ↗

Characterizes Anosov reducible representations in terms of eigenvalues.

problem Understanding Anosov representations in reducible settings.
method Characterizes Anosov representations using eigenvalue magnitudes of irreducible block factors.
result Connected components of character varieties do not contain reducible representations for many non-elementary hyperbolic groups.

Study Anosov representations of reducible suspensions of hyperbolic groups.

problem Characterize dynamical properties of reducible suspensions of Anosov representations.
method Analyzing linear representations of non-elementary hyperbolic groups, focusing on weak unipotent actions on subspaces.
result Characterize when reducible suspensions are discrete and faithful, quasi-isometrically embedded, and Anosov.

Using Green's theorem we reduce the variation of the total mean curvature of a smooth surface in the Euclidean 3-space to a line integral of a special vector field and obtain the following well-known theorem as an immediate consequence: the total mean curvature of a closed smooth surface in the Euclidean 3-space is sta…

2008-11-29abs ↗pdf ↗

WR-CP reduces prediction set size and coverage gap under distribution shift.

problem Guaranteed coverage under distribution shift not achievable with i.i.d. assumption.
method Wasserstein distance, probability measure pushforwards, importance weighting, regularized representation learning.
result Reduces coverage gap to 3.2% across different confidence levels.

Researchers parametrize spaces of positive representations for Lie groups.

problem Tackling spaces of positive representations for Lie groups.
method Generalizing Lusztig's total positivity, they introduce spaces of positive framed representations and parametrize them.
result The number of connected components of the space of framed positive representations agrees with the number of positive representations.

Let MφM_φ be a surface bundle over a circle with monodromy φ:SSφ:S \rightarrow S. We study deformations of certain reducible representations of π1(Mφ)π_1(M_φ) into SL(n,C)\text{SL}(n,\mathbb{C}), obtained by composing a reducible representation into SL(2,C)\text{SL}(2,\mathbb{C}) with the irreducible representation $\text{SL}(2,\mathb…

2015-09-24abs ↗pdf ↗

We study five dimensional geometries associated with the 5-dimensional irreducible representation of GL(2,R). These are special Weyl geometries in signature (3,2) having the structure group reduced from CO(3,2) to GL(2,R). The reduction is obtained by means of a conformal class of totally symmetric 3-tensors. Among all…

2007-10-01abs ↗pdf ↗

We study a particular class of representations from the fundamental groups of punctured spheres Σ0,nΣ_{0,n} to the group PSL(2,R)\text{PSL} (2,\mathbb R) (and their moduli spaces), that we call \emph{super-maximal}. Super-maximal representations are shown to be \emph{totally non hyperbolic}, in the sense that every simple clos…

2016-04-01abs ↗pdf ↗

This study finds ESG rating disagreement reduces corporate productivity, especially in certain types of firms.

problem The impact of ESG rating disagreement on corporate productivity.
method Analysis of A-share listed companies data from 2015 to 2022 using XGBoost regression and SHAP.
result ESG rating disagreement reduces corporate productivity, especially in certain types of firms.

Large batch sizes reduce gradient variance in DP-SGD, improving privacy.

problem Understanding why large batch sizes work in DP-SGD.
method Decomposed total gradient variance into subsampling and noise-induced variances, proving batch size independence in the limit.
result Large batch sizes reduce effective total gradient variance, improving privacy in DP-SGD.

New algorithm REFUEL shows multitask representation learning is more sample-efficient in RL.

problem Understanding the benefit of representation learning in reinforcement learning.
method Developed REFUEL algorithm for multitask low-rank RL, analyzing both upstream and downstream tasks.
result Multitask representation learning is provably more sample-efficient than individual task learning.

Advances in unsupervised learning enable reconstruction and generation of samples from complex distributions, but this success is marred by the inscrutability of the representations learned. We propose an information-theoretic approach to characterizing disentanglement and dependence in representation learning using mu…

2018-02-16abs ↗pdf ↗

We lift the characteristic-2 totally twisted Khovanov homology of Roberts and Jaeger to a theory with integer coefficients. The result is a complex computing reduced odd Khovanov homology for knots. This complex is equivalent to a spanning-tree complex whose differential is explicit modulo a sign ambiguity coming from …

2011-09-23abs ↗pdf ↗

Study Riemannian geometry of maximal surface group representations in pseudo-hyperbolic space.

problem Characterize the geometry of maximal surface group representations in pseudo-hyperbolic space.
method Introduced a scalar product on the first cohomology group, leading to a Riemannian metric on the smooth locus.
result Found totally geodesic sub-varieties and orbifold structures in the space of representations.

We study the normal holonomy group, i.e. the holonomy group of the normal connection, of a CR-submanifold of a complex space form. We complete the local classification of normal holonomies for complex submanifolds. We show that the normal holonomy group of a coisotropic submanifold acts as the holonomy representation o…

2013-11-22abs ↗pdf ↗

Language models allocate information storage, not collapsing into uniform representations.

problem Incomplete neural collapse in language model representations.
method Analyzing variance and information sharing across 14 models, proving an information floor.
result Within-class variance is allocated information storage, not collapsed into uniform representations.

Let ΣgΣ_g be a compact, connected, orientable surface of genus g2g \geq 2. We ask for a parametrization of the discrete, faithful, totally loxodromic representations in the deformation space Hom(π1(Σg),SU(3,1))/SU(3,1){\rm Hom}(π_1(Σ_g), {\rm SU}(3,1))/{\rm SU}(3,1). We show that such a representation, under some hypothesis, can be determined …

2014-11-25abs ↗pdf ↗

WeLa-VAE learns interpretable disentangled representations with weak supervision.

problem Learning disentangled representations without strong supervision.
method Variational inference framework with shared latent variables and modified variational lower bound.
result WeLa-VAE learns alternative disentangled representations (polar) from weak labels (distance and angle) without refined supervision.

GCAE uses density estimation to achieve reliable disentanglement in latent space.

problem Disentangled learning representations suffer from reliability issues.
method GCAE uses Gaussian Channel Autoencoder with Dual Total Correlation (DTC) to avoid the curse of dimensionality.
result GCAE achieves highly competitive and reliable disentanglement scores.