On-device research index

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.

168,657 papers · 148 categories

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6 results for “S5”

Robustifying State-space Models for Long Sequences via Approximate Diagonalizationcs.LG

New method improves deep learning model robustness and accuracy for long sequences.

problem Challenges in learning long-range sequence tasks using state-space models.

method Proposes a perturb-then-diagonalize (PTD) methodology to address ill-posed diagonalization problems in SSMs.

result Demonstrates improved robustness and accuracy of S5-PTD model on Long-Range Arena benchmark.

state-space models diagonalization long-range sequence deep learning robustness

2023-10-02abs ↗pdf ↗

Rigidity of Closed Minimal Hypersurfaces in

\mathbb{S}^5

math.DG

Paper resolves Chern conjecture for 4D minimal hypersurfaces in S5.

problem Chern conjecture for closed minimal hypersurfaces in S5.

method Constructing weighted 3-forms and proving global curvature estimates.

result Complete geometric rigidity achieved for constant Gauss-Kronecker curvature.

Chern conjecture minimal hypersurfaces S5 rigidity Gauss-Kronecker curvature

2026-06-28abs ↗pdf ↗

Conformal k-NN Anomaly Detector for Univariate Data Streamsstat.ML

Anomalies in time-series data give essential and often actionable information in many applications. In this paper we consider a model-free anomaly detection method for univariate time-series which adapts to non-stationarity in the data stream and provides probabilistic abnormality scores based on the conformal predicti…

2017-06-11abs ↗pdf ↗

Quadratic harmonic morphisms and O-systemsmath.DG

We introduce O-systems (Definition \ref{DO}) of orthogonal transformations of ${\Bbb R}^{m}$ , and establish $1-1$ correspondences both between equivalence classes of Clifford systems and that of O-systems, and between O-systems and orthogonal multiplications of the form $μ:{\Bbb R}^{n} \times {\Bbb R}^{m} \longrightarr…

1995-11-03abs ↗pdf ↗

Length independent generalization bounds for deep SSM architectures via Rademacher contraction and stability constraintscs.LG

The paper provides a theoretical justification for using stable SSM blocks in deep sequential models.

problem Developing generalization bounds for deep sequential models with varying sequence lengths.

method Using Rademacher contraction and stability constraints, the paper derives a PAC bound that is independent of sequence length.

result The derived PAC bound decreases as the stability of SSM blocks increases, providing theoretical justification for their use.

PAC bound Rademacher contraction Stability constraints Deep sequential models State-Space Models

2024-05-30abs ↗pdf ↗

Towards a unified and verified understanding of group-operation networkscs.LG

Unified understanding of neural networks on group operations verified.

problem Understanding and verifying neural networks trained on group operations.

method Investigated one-hidden-layer neural networks trained on binary operation of finite groups, revealing structure and providing a compact proof of model performance.

result Verified explanation applies to a large fraction of networks trained on the symmetric group S5, providing a >=95% accuracy bound for 45% of models.

neural networks group operations equivariance mechanistic interpretability reverse-engineering

2024-10-09abs ↗pdf ↗