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137275412549 · Jun 202019922001200920172026
48 results for complexity reduction

We study reduction of generalized complex structures. More precisely, we investigate the following question. Let JJ be a generalized complex structure on a manifold MM, which admits an action of a Lie group GG preserving JJ. Assume that M0M_0 is a GG-invariant smooth submanifold and the GG-action on M0M_0 is prop…

2005-09-18abs ↗pdf ↗

We present a theory of reduction for Courant algebroids as well as Dirac structures, generalized complex, and generalized Kähler structures which interpolates between holomorphic reduction of complex manifolds and symplectic reduction. The enhanced symmetry group of a Courant algebroid leads us to define \emph{extended…

2005-09-27abs ↗pdf ↗

Let EGE_G be a stable principal GG--bundle over a compact connected Kaehler manifold, where GG is a connected reductive linear algebraic group defined over the complex numbers. Let HGH\subset G be a complex reductive subgroup which is not necessarily connected, and let EHEGE_H\subset E_G be a holomorphic reduction of s…

2006-08-23abs ↗pdf ↗

In this paper, we develop results in the direction of an analogue of Sjamaar and Lerman's singular reduction of Hamiltonian symplectic manifolds in the context of reduction of Hamiltonian generalized complex manifolds (in the sense of Lin and Tolman). Specifically, we prove that if a compact Lie group acts on a general…

2010-03-09abs ↗pdf ↗

Improved time complexity for parallel stochastic optimization in heterogeneous systems.

problem Time complexity in parallel stochastic optimization for large-scale machine learning models.
method Proposes Rennala MVR, a variance-reduced extension of Rennala SGD based on momentum-based variance reduction.
result Variance reduction improves time complexity in relevant parameter regimes for parallel stochastic optimization in heterogeneous systems.

We consider dimension reduction for solutions of the Kähler-Ricci flow with nonegative bisectional curvature. When the complex dimension n=2n=2, we prove an optimal dimension reduction theorem for complete translating Kähler-Ricci solitons with nonnegative bisectional curvature. We also prove a general dimension reducti…

2003-02-11abs ↗pdf ↗

Study on pp-Kähler structures on fibrations and Lie groups.

problem Existence of pp-Kähler structures on complex manifolds.
method Investigation of quasi-regular fibrations and reductive Lie groups with invariant complex structures.
result Construction of non-regular complex structures on Lie algebras sl(2m1,R)\mathfrak{sl}(2m-1,\mathbb{R}) for m2m \ge 2.

Proposes a faster Isomap algorithm by reducing eigenvalue decomposition complexity.

problem High computational complexity of Isomap, especially in eigenvalue decomposition stage.
method Introduces a projection operator to reduce the complexity of the eigenvalue decomposition stage to linear order.
result Reduces Isomap's computational complexity to linear order while preserving structural information.

We realise the first and second Grushin distributions as symmetry reductions of the 3-dimensional Heisenberg distribution and 4-dimensional Engel distribution respectively. Similarly, we realise the Martinet distribution as an alternative symmetry reduction of the Engel distribution. These reductions allow us to derive…

2012-07-23abs ↗pdf ↗

We show that certain submanifolds of generalized complex manifolds ("weak branes") admit a natural quotient which inherits a generalized complex structure. This is analog to quotienting coisotropic submanifolds of symplectic manifolds. In particular Gualtieri's generalized complex submanifolds ("branes") quotient to sp…

2007-01-25abs ↗pdf ↗

Improved variance reduction for Riemannian non-convex optimization with adaptive batch size.

problem Optimizing non-convex functions on Riemannian manifolds.
method Batch size adaptation in R-SVRG, R-SRG, and R-SPIDER.
result Achieves lower total complexities for various non-convex functions.

Efficiently reduces rank of non-negative matrices with quadratic time complexity.

problem Efficiently reducing the rank of non-negative matrices.
method Formulated rank reduction as a mean-field approximation using a log-linear model.
result Optimal solution for minimizing KL divergence can be computed in closed form.

The paper simplifies symmetries in complex geometric structures.

problem Redundancy in conditions for symmetry reduction in polysymplectic and polycosymplectic structures.
method Exploring and proving necessary and sufficient conditions for polycosymplectic reduction.
result A one-to-one relationship between polycosymplectic reduction and the reduction of a larger polysymplectic manifold.

Extending our reduction construction in \cite{Hu} to the Hamiltonian action of a Poisson Lie group, we show that generalized Kähler reduction exists even when only one generalized complex structure in the pair is preserved by the group action. We show that the constructions in string theory of the (geometrical) TT-dua…

2005-12-29abs ↗pdf ↗

We consider locally conformal Kaehler geometry as an equivariant (homothetic) Kaehler geometry: a locally conformal Kaehler manifold is, up to equivalence, a pair (K,Γ) where K is a Kaehler manifold and Γa discrete Lie group of biholomorphic homotheties acting freely and properly discontinuously. We define a new invari…

2005-02-28abs ↗pdf ↗

This work compares data reduction criteria for online Gaussian Processes.

problem The computational complexity of Gaussian Processes limits their applicability to small datasets and streaming scenarios.
method Unified comparison of several data reduction criteria, analyzing computational complexity and reduction behavior.
result Practical guidelines for choosing a suitable data reduction criterion for online Gaussian Processes.

FibeRed reduces complex data dimensions while preserving topology.

problem Hard embedding of topologically complex datasets in low-dimensional Euclidean space.
method Modeling datasets with vector bundles, reducing fibers while preserving topology.
result FibeRed learns topologically faithful embeddings in lower dimensions than existing methods.

We discuss a natural extension of the Kähler reduction of Fujiki and Donaldson, which realises the scalar curvature of Kähler metrics as a moment map, to a hyperkähler reduction. Our approach is based on an explicit construction of hyperkähler metrics due to Biquard and Gauduchon. This extension is reminiscent of how o…

2018-11-05abs ↗pdf ↗

Study of hyperkähler reduction on abelian varieties and toric manifolds.

problem Understanding hyperkähler reduction on specific manifolds.
method Lifts canonical Kähler reduction to hyperkähler, studies on abelian varieties and toric manifolds.
result Obtains decoupling result, variational characterisation, relation to KK-stability, and proves existence and uniqueness under suitable assumptions.

Let GG be a connected reductive complex affine algebraic group and KGK\subset G a maximal compact subgroup. Let MM be a compact complex torus equipped with a flat Kähler structure and (EG,θ)(E_G ,θ) a polystable Higgs GG-bundle on MM. Take any CC^\infty reduction of structure group EKEGE_K \subset E_G to the subgroup $K…

2014-11-11abs ↗pdf ↗

Let PP be a parabolic subgroup of a connected simply connected complex semisimple Lie group GG. Given a compact Kähler manifold XX, the dimensional reduction of GG-equivariant holomorphic vector bundles over X×G/PX\times G/P was carried out by the first and third authors. This raises the question of dimensional reduct…

2016-09-13abs ↗pdf ↗

WeldNet reduces complex dynamics to simpler, manageable segments.

problem Complex, high-dimensional time-dependent datasets from physical processes are costly to simulate.
method Windowed Encoders for Learning Dynamics, splitting time domain into windows for nonlinear dimension reduction and propagator training.
result WeldNet captures nonlinear latent structures and dynamics, outperforming existing methods.

We recall the presentation of the generalized, complex structures by classical tensor fields, while noticing that one has a similar presentation and the same integrability conditions for generalized, paracomplex and subtangent structures. This presentation shows that the generalized, complex, paracomplex and subtangent…

2005-11-01abs ↗pdf ↗

New technique reduces bias in CSO problems, improving sample complexity.

problem Reducing bias in conditional stochastic optimization problems.
method Introducing a stochastic extrapolation technique combined with variance reduction.
result Achieved significantly better sample complexity for nonconvex smooth objectives.

This article addresses the question of whether Langlands duality for complex reductive Lie groups may be implemented by T-dualization. We prove that for reductive groups whose simple factors are of Dynkin type A, D, or E, the answer is yes.

2012-11-05abs ↗pdf ↗

New algorithms reduce variance in solving complex mathematical problems.

problem Solving convex-concave saddle point problems, variational inequalities, and inclusions.
method Stochastic variance reduction for extragradient, forward-backward-forward, and forward-reflected-backward methods.
result All proposed methods converge with complexities matching or improving deterministic counterparts.

We develop a theory of reduction for generalized Kahler and hyper-Kahler structures which uses the generalized Riemannian metric in an essential way, and which is not described with reference solely to a single generalized complex structure. We show that our construction specializes to the usual theory of Kahler and hy…

2007-02-05abs ↗pdf ↗

A trisymplectic structure on a complex 2n-manifold is a triple of holomorphic symplectic forms such that any linear combination of these forms has constant rank 2n, n or 0, and degenerate forms in ΩΩ belong to a non-degenerate quadric hypersurface. We show that a trisymplectic manifold is equipped with a holomorphic 3…

2011-03-23abs ↗pdf ↗

The diverse world of machine learning applications has given rise to a plethora of algorithms and optimization methods, finely tuned to the specific regression or classification task at hand. We reduce the complexity of algorithm design for machine learning by reductions: we develop reductions that take a method develo…

2016-03-17abs ↗pdf ↗

We give a reduction from {\sc clique} to establish that sparse PCA is NP-hard. The reduction has a gap which we use to exclude an FPTAS for sparse PCA (unless P=NP). Under weaker complexity assumptions, we also exclude polynomial constant-factor approximation algorithms.

2015-02-19abs ↗pdf ↗

We discuss Poincaré duality complexes X and the question whether or not their Spivak normal fibration admits a reduction to a vector bundle in the case where the dimension of X is at most 4. We show that in dimensions less than 4 such a reduction always exists, and in dimension 4 such a reduction exists provided X is o…

2017-11-22abs ↗pdf ↗