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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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57113170226 · Jun 202019922001200920172026
48 results for Orthogonal group synchronization

Study optimizes estimation of orthogonal and rotation matrices from noisy data.

problem Estimating orthogonal and rotation matrices from noisy data.
method Iterative polar decomposition algorithm initialized by spectral methods.
result Algorithm achieves optimal error rate of $(1+o(1)) rac{σ^2 d(d-1)}{2np}$.

Spectral methods achieve near-optimal performance in orthogonal and permutation group synchronization.

problem Recovering group elements from pairwise measurements in computer vision.
method Spectral methods applied with the leave-one-out technique.
result Near-optimal performance bounds for orthogonal and permutation group synchronization established.

Spectral method for joint community detection and group synchronization.

problem Jointly detecting communities and synchronizing orthogonal groups in graphs.
method Spectral decomposition followed by CPQR factorization.
result Near-optimal guarantees for exact and stable recovery of cluster memberships and orthogonal transforms.

Paper addresses group synchronization with incomplete measurements and proves linear convergence of GPM.

problem Orthogonal group synchronization with incomplete measurements and additive noise.
method Generalized power method (GPM) with local error bound analysis.
result Linear convergence of GPM to a global maximizer under general additive noise model.

Novel higher-order group synchronization for noisy local measurements on hypergraphs.

problem Synchronizing higher-order local measurements on hyperedges to global estimates on nodes.
method Message passing algorithm for global synchronization of higher-order measurements.
result Higher-order method outperforms standard pairwise synchronization methods in certain applications.

New method solves group synchronization with cycle-edge message passing.

problem Solving group synchronization with adversarial or uniform corruption and small noise.
method Cycle-edge message passing procedure using cycle consistency information.
result Exact recovery and linear convergence guarantees under adversarial corruption.

New method uses neural networks for accurate angle estimation in noisy conditions.

problem Accurately estimate angles from noisy measurements in various applications.
method Directed Graph Neural Networks (GNNSync) for end-to-end trainable framework.
result GNNSync achieves competitive performance, even at high noise levels.

Paper proposes GPM for simultaneous community detection and group synchronization.

problem Simultaneous community detection and group synchronization in networks.
method Generalized Power Method (GPM) for non-convex optimization.
result GPM achieves exact recovery in O(nlog2n)O(n\log^2n) time, outperforming SDP.

Extends angular synchronization to heterogeneous groups, improving accuracy in multiple applications.

problem Recovering angles from noisy pairwise measurements in a heterogeneous setting.
method Probabilistic generative model and spectral algorithm with robustness analysis.
result Spectral algorithm provides improved recovery accuracy in various parameter regimes.

Study isotropy groups for complex orthogonal and skew-symmetric matrices.

problem Understanding isotropy subgroups of orthogonal similarity transformations.
method Analysis of group structure of nonsingular block matrices.
result Group structure of isotropy subgroups related to block Toeplitz matrices.

DS-Sync improves distributed DNN training efficiency by 94% with minimal accuracy loss.

problem Network bottlenecks in distributed DNN training.
method Divide workers into non-overlapping groups for independent synchronization, then shuffle workers among groups iteratively.
result DS-Sync achieves up to 94% improvement in training time with minimal accuracy loss.

The present paper considers distributed consensus algorithms that involve N agents evolving on a connected compact homogeneous manifold. The agents track no external reference and communicate their relative state according to a communication graph. The consensus problem is formulated in terms of the extrema of a cost f…

2008-11-26abs ↗pdf ↗

Computes isotropy subgroups of orthogonal matrices acting on Hermitian matrices.

problem Computing isotropy subgroups of orthogonal matrices acting on Hermitian matrices.
method Algorithm for solving a matrix equation to compute isotropy subgroups.
result Computed isotropy subgroups of orthogonal matrices acting on Hermitian matrices.

We prove that a polar orthogonal representation of a real reductive algebraic group has the same closed orbits as the isotropy representation of a pseudo-Riemannian symmetric space. We also develop a partial structural theory of polar orthogonal representations of real reductive algebraic groups which slightly generali…

2008-01-03abs ↗pdf ↗

An algorithm for efficient computation of equivariant neural network layers.

problem Efficiently computing with Brauer's group equivariant neural network layers.
method Category theoretic constructions and Kronecker product matrices.
result Significant reduction in computational cost compared to naive implementation.

We study the Chern-Simons partition function of orthogonal quantum group invariants, and propose a new orthogonal Labastida-Mariño-Ooguri-Vafa conjecture as well as degree conjecture for free energy associated to the orthogonal Chern-Simons partition function. We prove the degree conjecture and some interesting cases o…

2010-07-09abs ↗pdf ↗

Curious structure of special orthogonal, unitary, and symplectic groups as products of Grassmannians discovered.

problem Understanding the structure of special orthogonal, unitary, and symplectic groups.
method Expressing these groups as products of Grassmannians realized as involution matrices.
result Special orthogonal, special unitary, and symplectic groups can be expressed as products of their corresponding Grassmannians.

New algorithm improves PPS for multi-object matching.

problem Efficiently synchronize partial permutations for multi-object matching.
method Proposed CEMP-Partial algorithm for partial permutation synchronization (PPS). Uses sparse matrix operations and nonconvex weighted projected power method.
result Proves CEMP-Partial can exactly classify corrupted and clean partial permutations under adversarial corruption.

We analyze how an observer synchronizes to the internal state of a finite-state information source, using the epsilon-machine causal representation. Here, we treat the case of exact synchronization, when it is possible for the observer to synchronize completely after a finite number of observations. The more difficult …

2010-08-25abs ↗pdf ↗

Characterizes group-equivariant neural networks for three groups.

problem Understanding equivariant neural networks for orthogonal, special orthogonal, and symplectic groups.
method Characterized all possible group-equivariant neural networks for three groups.
result Found spanning sets of matrices for learnable, linear equivariant layer functions.

In this paper we study contact structure on 2-step nilpotent, Heisenberg type Lie groups. We decompose this Lie groups to center and orthogonal complement, then investigate properties of both orthogonal Lie subgroups. Finally, we provide a connection between matchings in groups and field extensions and 2-step nilpotent…

2013-11-26abs ↗pdf ↗

New method explains computational barriers in high-dimensional statistical models.

problem Understanding detection-recovery gaps in high-dimensional inference.
method Combining algorithmic contiguity and cross-validation reduction to obtain conditional computational lower bounds.
result Mild control of low-degree advantage is sufficient to explain computational barriers for recovery.

New measures on orbit spaces for orthogonal groups identified.

problem Characterizing measures on orbit spaces of orthogonal groups.
method Constructing Hilbert measures on orbit spaces of coregular representations of orthogonal groups.
result Hilbert measures have singularities if and only if the number of copies equals the dimension.

New algorithm uses PSO to optimize DNN training parameters in distributed systems.

problem Reducing synchronization frequency in DNN training leads to poor convergence.
method Integrates PSO into distributed training to automatically compute new parameters.
result Proposed algorithm outperforms synchronous methods in distributed DNN training.

ShadowSync separates background synchronization for scalable distributed training.

problem Reducing synchronization overhead in distributed training for high scalability.
method Separates synchronization from training and runs it in the background.
result Achieves both high throughput and excellent model quality at scale.