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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.

168,657 papers · 148 categories

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20405979 · Jun 202019922001200920172026
48 results for subset wTGS

New sampler reduces MCMC complexity for Bayesian variable selection.

problem High-dimensional Bayesian variable selection with high computation complexity.
method Variable-complexity subset weighted-Tempered Gibbs Sampler (wTGS) with Rao-Blackwellized estimator.
result Variances of Rao-Blackwellized estimator are smaller than those of subset wTGS.

We define regular points of an extremal subset in an Alexandrov space and study their basic properties. We show that a neighborhood of a regular point in an extremal subset is almost isometric to an open subset in Euclidean space and that the set of regular points in an extremal subset has full measure and is dense in …

2019-05-14abs ↗pdf ↗

The paper defines quasi-convex subsets in spaces with lower curvature bound.

problem Understanding the geometry of spaces with lower curvature bound.
method Introducing and exploring quasi-convex subsets in Alexandrov spaces.
result Quasi-convex subsets are a fundamental concept for comparing Riemannian and Alexandrov spaces.

To find efficient screening methods for high dimensional linear regression models, this paper studies the relationship between model fitting and screening performance. Under a sparsity assumption, we show that a subset that includes the true submodel always yields smaller residual sum of squares (i.e., has better model…

2012-12-04abs ↗pdf ↗

Study on extremal subsets in geodesically complete spaces with curvature constraints.

problem Characterizing extremal subsets in GCBA spaces.
method Introduced and analyzed extremal subsets in GCBA spaces, proving their properties.
result Set of topological singularities forms an extremal subset under additional assumptions.

One-pass algorithm finds small subset for p\ell_p subspace approximation with additive error.

problem Finding a small subset of data points for p\ell_p subspace approximation.
method One-pass subset selection with additive approximation guarantee for p[1,)p \in [1, \infty).
result First one-pass algorithm with additive error for p\ell_p subspace approximation.

Let T\mathcal{T} be the group of smooth concordance classes of topologically slice knots, and {0}Tn+1TnT0T\{0\}\subset\cdots\subset \mathcal{T}_{n+1}\subset\mathcal{T}_{n}\subset \cdots\subset \mathcal{T}_{0}\subset \mathcal{T} be the bipolar filtration. In this paper, we show that a proper collection of the knots employed by H…

2017-12-27abs ↗pdf ↗

In each Menger manifold MM we construct: (i) a closed nowhere dense subset M0M_0 which is homeomorphic to MM and is universal nowhere dense in the sense that for each nowhere dense set AMA\subset M there is a homeomorphism hh of MM such that h(A)M0h(A)\subset M_0; (ii) a meager FσF_σ-set Σ0MΣ_0\subset M which is univers…

2013-02-22abs ↗pdf ↗

Bayesian approach selects subsets of variables for interpretable prediction and identifies key factors in educational outcomes.

problem Challenges in subset selection for stability, regularization, and inference.
method Bayesian perspective on subset selection, deriving optimal subsets and variable importance metrics.
result Better prediction, interval estimation, and variable selection compared to competing methods.

This paper improves volatility forecasting using dynamic subset selection in genetic programming.

problem Improving accuracy of implied volatility forecasting.
method Dynamic training-subset selection methods applied to genetic programming.
result Dynamic subset selection improves predictive accuracy of genetic programming models.

Proposes a neural framework to select subsets efficiently across different models.

problem Lack of generalizability in subset selection methods for unseen architectures.
method Introduces a trainable subset selection framework, SubSelNet, that uses attention-based neural gadgets and subset samplers.
result SubSelNet generalizes across architectures and outperforms existing methods.

In each manifold MM modeled on a finite or infinite dimensional cube [0,1]n[0,1]^n we construct a meager FσF_σ-subset XMX\subset M which is universal meager in the sense that for each meager subset AMA\subset M there is a homeomorphism h:MMh:M\to M such that h(A)Xh(A)\subset X. We also prove that any two universal meager FσF_σ

2013-02-22abs ↗pdf ↗

In this paper, we study extremal subsets in Alexandrov spaces with dimension nn, curvature κ\geκ, and diameter D\le D. We show that the following three quantities are uniformly bounded above in terms of nn, κκ, and DD: (1) the number of extremal subsets in an Alexandrov space; (2) the Betti numbers of an extremal…

2018-09-03abs ↗pdf ↗

Many machine learning tasks require sampling a subset of items from a collection based on a parameterized distribution. The Gumbel-softmax trick can be used to sample a single item, and allows for low-variance reparameterized gradients with respect to the parameters of the underlying distribution. However, stochastic o…

2019-01-29abs ↗pdf ↗

New MCMC algorithm reduces subset selection passes to 2 for optimal kk-dimensional subspace approximation.

problem Subset selection for kk-dimensional subspace approximation with εε-approximation.
method MCMC sampling algorithm reducing passes to 2 for p=2p=2 case, poly(k/ε) size subset.
result Subset selection of nearly optimal size in 2 passes, (1+ε)(1+ε) approximation.

We consider combinatorial online learning with subset choices when only relative feedback information from subsets is available, instead of bandit or semi-bandit feedback which is absolute. Specifically, we study two regret minimisation problems over subsets of a finite ground set [n][n], with subset-wise relative prefe…

2019-03-01abs ↗pdf ↗

The kth finite subset space of a topological space X is the space exp_k X of non-empty finite subsets of X of size at most k, topologised as a quotient of X^k. The construction is a homotopy functor and may be regarded as a union of configuration spaces of distinct unordered points in X. We show that the finite subset …

2003-11-21abs ↗pdf ↗

In each manifold MM modeled on a finite or infinite dimensional cube [0,1]n[0,1]^n we construct a closed nowhere dense subset SMS\subset M (called a spongy set) which is a universal nowhere dense set in MM in the sense that for each nowhere dense subset AMA\subset M there is a homeomorphism h:MMh:M\to M such that $h(A)\sub…

2013-02-22abs ↗pdf ↗

New algorithm finds best subset in high-dimensional data models.

problem Finding the best subset of predictors in high-dimensional data models.
method Proposes a scalable algorithm using a generalized information criterion.
result Directly proves consistency and oracle property for the best-subset selection.

The current article stems from our study on the asymptotic behavior of holomorphic isometric embeddings of the Poincaré disk into bounded symmetric domains. As a first result we prove that any holomorphic curve exiting the boundary of a bounded symmetric domain ΩΩ must necessarily be asymptotically totally geodesic. A…

2018-07-19abs ↗pdf ↗

B Wilking has recently shown that one can associate a Ricci flow invariant cone of curvature operators C(S)C(S), which are nonnegative in a suitable sense, to every $Ad_{SO(n,\C)}$ invariant subset $S \subset {\bf so}(n,\C)$. For curvature operators of a Kähler manifold of complex dimension nn, one considers $Ad_{GL(n,\…

2011-01-31abs ↗pdf ↗

Defines weak geodesics on specific subsets of manifolds.

problem Characterizing geodesics on prox-regular subsets of Riemannian manifolds.
method Defining weak geodesics as continuous curves with weak regularities, and characterizing them as viscosity critical points of the energy functional.
result Characterizes weak geodesics on prox-regular subsets of Riemannian manifolds.

The paper develops an algorithm to select a subset of training data for efficient regression models.

problem Designing an efficient algorithm for selecting a subset of training data to train regression models quickly without sacrificing accuracy.
method The paper tackles this problem by formulating it as a minimization of training loss with respect to both trainable parameters and subset of training data, subject to error bounds on the validation set. They use a novel problem formulation and represent it with simplified constraints using the dual of the original training problem. They then develop SELCON, an efficient majorization-minimization algorithm for data subset selection, which admits an approximation guarantee.
result The experiments show that SELCON trades off accuracy and efficiency more effectively than the current state-of-the-art.

Study efficient algorithms for identifying minimum interventional sets to learn causal relationships.

problem Identify the smallest set of interventions to learn causal relationships between a subset of edges.
method Develop algorithms for subset verification and search problems under assumptions of faithfulness, causal sufficiency, and ideal interventions.
result For subset verification, an efficient algorithm is provided to compute a minimum sized interventional set.

New suboptimal algorithm for best subset selection in high-dimensional data.

problem Nonconvex and computationally challenging best subset selection in linear regression.
method Introducing a new suboptimal algorithm and comparing it with other popular methods.
result The new procedure is a competitive suboptimal algorithm for high-dimensional data.

Efficiently selects predictors in sparse regression without approximations.

problem High computational cost in subset selection for sparse regression.
method Conditional uncorrelation formula and efficient non-approximate method.
result Significant reduction in computational complexity for subset selection.

We introduce and study the space of \emph{subset currents} on the free group FNF_N. A subset current on FNF_N is a positive FNF_N-invariant locally finite Borel measure on the space CN\mathfrak C_N of all closed subsets of FN\partial F_N consisting of at least two points. While ordinary geodesic currents generalize con…

2011-05-28abs ↗pdf ↗

We prove that for a coarse space XX the ideal S(X)S(X) of small subsets of XX coincides with the ideal D<(X)D_<(X) of subsets AXA\subset X of asymptotic dimension asdim(A)<asdim(X)asdim(A)<asdim(X) provided that XX is coarsely equivalent to an Euclidean space RnR^n. Also we prove that for a locally compact Abelian group XX, the equali…

2012-10-25abs ↗pdf ↗

Let n2n\ge 2 be an integer, and BnCnB^{n}\subset \mathbb{C}^{n} the unit ball. Let KBnK\subset B^{n} be a compact subset such that BnKB^n\setminus K is connected, or K={z=(z1,,zn)z1=z2=0}CnK=\{z=(z_1,\cdots, z_n)|z_1=z_2=0\}\subset \mathbb{C}^{n}. By the theory of developing maps, we prove that a Kähler metric on BnKB^{n}\setminus K with consta…

2018-12-31abs ↗pdf ↗

An open subset U of a complex surface can be topologically perturbed to yield an open subset whose inherited complex structure is Stein, if and only if U is homeomorphic to the interior of a handlebody whose handles all have index equal or less than 2.

2005-01-28abs ↗pdf ↗

The nn-solvable filtration of the mm-component smooth (string) link concordance group, Fn+1mFn.5mFnmF1mF0.5mF0mF0.5mCm,\dots \subset \mathcal{F}^m_{n+1} \subset \mathcal{F}^m_{n.5} \subset \mathcal{F}^m_n \dots \subset \mathcal{F}^m_1 \subset \mathcal{F}^m_{0.5} \subset \mathcal{F}^m_0 \subset \mathcal{F}^m_{-0.5} \subset \mathcal{C}^m, as defi…

2015-10-31abs ↗pdf ↗