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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.

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48 results for simplicity index

Unbounded primitivity index in free groups linked to Chebyshev function.

problem Analyzing primitivity and simplicity indices in free groups.
method Combining topological, group-theoretic, and number-theoretic approaches, including asymptotic properties of the second Chebyshev function.
result Proved the unboundedness of the primitivity index sequence and its asymptotic behavior.

Finite index subgroups of relatively hyperbolic groups have equal index.

problem Finite index subgroups of relatively hyperbolic groups have equal index.
method Demonstrating that the number of simplices in a simplicial classifying space grows linearly with index.
result Finite index subgroups of relatively hyperbolic groups have equal index.

Shellable tilings on simplicial complexes help understand their structure.

problem Understanding the structure of simplicial complexes through tilings.
method Proving the existence of shellable h-tilings on finite simplicial complexes after stellar subdivisions.
result The h-vector of a tiling is determined by the critical vector, with palindromic properties for closed triangulated manifolds.

Proposes a score to compare rule-based algorithms' interpretability.

problem Lack of consensus on interpretability for predictive models.
method Defines a score with three terms: predictivity, stability, and simplicity, each quantified by simple formulas.
result Compares interpretability of rule-based and tree-based algorithms for regression and classification.

The paper establishes conditions for Riemannian connections and semi-simplicity of Lie algebras using spray structures.

problem Conditions for Riemannian connections and semi-simplicity of Lie algebras.
method Using almost product structures and spray, the paper provides necessary and sufficient conditions for these properties.
result Equivalence of semi-simplicity of Lie algebras to derived ideal coincidence, interiority of derivations, and adjoint representation semi-simplicity.

The construction of efficient and effective decision trees remains a key topic in machine learning because of their simplicity and flexibility. A lot of heuristic algorithms have been proposed to construct near-optimal decision trees. ID3, C4.5 and CART are classical decision tree algorithms and the split criteria they…

2015-11-25abs ↗pdf ↗

Framework reduces simplicity bias in NNs, improving OOD generalization and robustness.

problem Simplicity bias in deep learning models leads to biased predictions and poor OOD generalization.
method Proposes a framework that regularizes conditional mutual information to encourage use of diverse features.
result Demonstrates effectiveness in various settings, enhancing OOD generalization and robustness.

Quadratic discriminant analysis (QDA) is a standard tool for classification due to its simplicity and flexibility. Because the number of its parameters scales quadratically with the number of the variables, QDA is not practical, however, when the dimensionality is relatively large. To address this, we propose a novel p…

2015-10-01abs ↗pdf ↗

New framework shows CC^*-simplicity for groups without certain subalgebras.

problem Characterizing CC^*-simplicity of groups.
method Introducing confined subalgebras and Uniformly Recurrent States.
result A countable discrete group is CC^*-simple if it has no non-trivial amenable confined subalgebras.

A knot type is exchange reducible if an arbitrary closed n-braid representative can be changed to a closed braid of minimum braid index by a finite sequence of braid isotopies, exchange moves and +/- destabilizations. In the manuscript [J Birman and NC Wrinkle, On transversally simple knots, preprint (1999)] a transver…

2000-02-14abs ↗pdf ↗

We study a natural intrinsic definition of geometric simplices in Riemannian manifolds of arbitrary dimension nn, and exploit these simplices to obtain criteria for triangulating compact Riemannian manifolds. These geometric simplices are defined using Karcher means. Given a finite set of vertices in a convex set on t…

2014-06-14abs ↗pdf ↗

Research reveals simplicity bias in random logistic map, impacting data analysis and forecasting.

problem Simplicity bias in dynamical systems and its impact on data analysis and prediction.
method Examined the logistic map and random logistic map, focusing on simplicity bias and noise effects.
result Simplicity bias is observable in the random logistic map, persisting even with small noise levels.

The Apollonius theorem is generalized for m-simplices, with applications in geometry and optimization.

problem Generalizing the Apollonius theorem for m-simplices.
method Direct generalization of the theorem to m-simplices in n-dimensional space.
result Applications in geometry and optimization, including minimal surface enclosures, simplex thickness, and root-finding methods.

We study prismatics sets analogously to simplical sets except that realization involves prisms, i.e., products of simplices rather than just simplices. Particular examples are the prismatic subdivision of a simplicial set S and the prismatic star of S. Both have the same homotopy type as S and in particular the latter …

2008-07-31abs ↗pdf ↗

We generalize the very well known boundary operator of the ordinary singular homology theory, defined in many books about algebraic topology. We describe a variant of this ordinary simplicial boundary operator where the usual boundary (n-1)-simplices of each n-simplex are replaced by combinations of internal (n-1)- sim…

2011-09-09abs ↗pdf ↗

Simple method for estimating missing panel data entries with confidence intervals.

problem Estimating missing values in panel data with staggered adoption.
method Simple matrix algebra and singular value decomposition for estimation, with data-driven confidence intervals.
result Confidence intervals match non-asymptotic lower bounds, proving instance optimality.

The paper explores how simplicity leads to better out-of-distribution generalization in models.

problem Understanding the theoretical principles behind out-of-distribution (OOD) generalization in modern models.
method Examining diffusion models in image generation to analyze compositional generalization abilities and develop a theoretical framework for simplicity-based OOD generalization.
result The true, generalizable model corresponds to the simplest among consistent models, and this simplicity can be quantified and used to establish sample complexity guarantees.

The study reveals simplicity bias in neural networks leading to better compositional mappings.

problem Understanding when and how to encourage neural networks to learn compositional mappings.
method Examined compositional mappings through coding length and gradient descent dynamics.
result Neural networks tend to learn the simplest bijections, explaining their good generalization.

Study on simplicity of Lie skew braces, proving new results for compact cases.

problem Simplicity of Lie skew braces, focusing on compact connected cases.
method Reviewing correspondence, investigating ideals and rigidity, proving main result for compact Lie skew braces.
result Compact connected simple Lie skew braces are either trivial or have simple underlying Lie groups.

Stochastic volatility (SV) models mimic many of the stylized facts attributed to time series of asset returns, while maintaining conceptual simplicity. The commonly made assumption of conditionally normally distributed or Student-t-distributed returns, given the volatility, has however been questioned. In this manuscri…

2013-08-27abs ↗pdf ↗

Two-layer networks favor simple features, especially in complex datasets.

problem Simplicity bias in neural networks over-reliing on simple features.
method Characterization of two-layer neural networks with small weights and gradient flow.
result Features learned in middle training stages are more useful for out-of-distribution transfer.

We give several new criteria to judge whether a simple convex polytope in a Euclidean space is combinatorially equivalent to a product of simplices. These criteria are mixtures of combinatorial, geometrical and topological conditions that are inspired by the ideas from toric topology.

2016-09-19abs ↗pdf ↗

Neural nets learn simple distributions first, then more complex ones.

problem Understanding how neural networks generalize from simple to complex functions.
method Stochastic gradient descent training, synthetic data, CIFAR10, ImageNet pre-training.
result Neural networks initially use lower-order statistics, then higher-order ones.

The paper proves eigenvalues are simple for specific operators on bundles.

problem Eigenvalue simplicity for connection Laplacian and GG-simplicity on bundles.
method Analyzes connections on vector bundles and principal bundles, proving eigenvalue simplicity for a residual set of connections.
result Eigenvalues of the connection Laplacian and Laplace-Beltrami operator are simple for specified conditions.

Hedge Funds are considered as one of the portfolio management sectors which shows a fastest growing for the past decade. An optimal Hedge Fund management requires an appropriate risk metrics. The classic CAPM theory and its Ratio Sharpe fail to capture some crucial aspects due to the strong non-Gaussian character of He…

2006-10-20abs ↗pdf ↗

Everyone knows that the Euler characteristic of a combinatorial manifold is given by the alternating sum of its numbers of simplices. It is shown that there are other linear combinations of the numbers of simplices which are combinatorial invariants, but that all such invariants are multiples of the Euler characteristi…

2002-01-18abs ↗pdf ↗

Proves simplicity of Lyapunov exponents for specific Anosov flows.

problem Proving all Lyapunov exponents have multiplicity 1 for certain Anosov flows.
method Perturbative results for flows, modification of eigenvalues, Markov partition, and simplicity criterion.
result In a C1C^1-open and CkC^k-dense set of Anosov flows, all Lyapunov exponents have multiplicity 1.