Research
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.

169,341 papers · 148 categories

Trend · papers per month

99199298397 · Jun 202019922001200920182026
48 results for infinite order plug

The paper introduces new 4D twists and exotic families from a plug, with applications to knot surgeries.

problem Exploring new 4-dimensional twists and exotic families from a plug.
method Defined an infinite order plug (P,φ)(P,\varphi) and used it to create families YnY_n, ZnZ_n of exotic enlargements.
result Introduced a new method to produce 2-bridge knot or link surgeries.

Every exotic pair in 4-dimension is obtained each other by twisting a {\it cork} or {\it plug} which are codimension 0 submanifolds embedded in the 4-manifolds. The twist was an involution on the boundary of the submanifold. We define cork (or plug) with order pN{}p\in {\Bbb N}\cup \{\infty\} and show there exists a plug…

2012-01-28abs ↗pdf ↗

Develops robust estimators for high-frequency data with market microstructure noise.

problem Estimating prices in the presence of market microstructure noise.
method Plug-in versions of existing estimators, using raw price and limit order book data.
result Noise-robust estimators can be applied to various high-frequency data problems.

It is known that every exotic smooth structure on a simply connected closed 4-manifold is determined by a codimention zero compact contractible Stein submanifold and an involution on its boundary. Such a pair is called a cork. In this paper, we construct infinitely many knotted imbeddings of corks in 4-manifolds such t…

2008-12-30abs ↗pdf ↗

Semiparametric method removes bias in functional bilevel gradient estimation.

problem First-order bias in plug-in hypergradient when lower-level problem is nonparametric.
method Semiparametric debiasing theory based on efficient influence function leads to cross-fitted orthogonal hypergradient estimator.
result Asymptotic normality and uniform control over outer parameter established for the estimator.

We discuss corks, and introduce new objects which we call plugs. Though plugs are fundamentally different objects, they also detect exotic smooth structures in 4-manifolds like corks. We discuss relation between corks, plugs and rational blow-downs. We show how to detect corks and plugs inside of some exotic manifolds.…

2008-06-18abs ↗pdf ↗

Transformers approximate Bayesian posteriors but not exactly.

problem Bayesian accounts of in-context learning face challenges due to task-preserving order changes in transformers.
method Showed that excess prequential code length is exactly cumulative predictive KL, decomposing expected regret into order-averaged predictor and order-averaging gain.
result Transformers approximate Bayesian posteriors but not exactly, priced by log loss.

The paper proves statistical consistency and fairness guarantees for a plug-in algorithm.

problem Establishing statistical guarantees for fairness-aware binary classification.
method Proves statistical consistency and derives finite sample guarantees for the plug-in algorithm.
result The plug-in algorithm is statistically consistent and guarantees fairness and differential privacy.

Learn to automatically plug domain-specific modules into a common network.

problem Learning inflexibility and computational intensiveness in multi-domain learning.
method Neural Architecture Search (NAS) for data-driven adapter plugging and structure design.
result NAS-driven MDL model achieves comparable performance to existing approaches.

Information theory provides principled ways to analyze different inference and learning problems such as hypothesis testing, clustering, dimensionality reduction, classification, among others. However, the use of information theoretic quantities as test statistics, that is, as quantities obtained from empirical data, p…

2012-11-11abs ↗pdf ↗

Optimal sample complexity analysis for plug-in approach in average-reward MDPs.

problem Learning optimal policies in average-reward MDPs with a generative model.
method Plug-in approach that constructs a model estimate and computes an optimal policy.
result Optimal sample complexities for the plug-in approach without prior knowledge of problem parameters.

Estimates change point in high dimensional time series models.

problem Change point estimation in high dimensional time series.
method Plug-in least squares estimator with sufficient conditions for adaptivity.
result Optimal rate of convergence Op(ξ2)O_p(ξ^{-2}) in integer scale.

Simplified plug-in loss approximates EDL for reliable uncertainty estimation.

problem Efficient and reliable uncertainty estimation in real-world sensor-based learning systems.
method Approximate Dirichlet expected objectives with plug-in losses evaluated at the Dirichlet mean.
result Plug-in losses provide comparable predictive accuracy and selective prediction performance to classical EDL, while being simpler to implement.

Study minimax off-policy evaluation in multi-armed bandits with known and unknown behavior policies.

problem Evaluate policies in multi-armed bandits with unknown behavior policies.
method Develop minimax rate-optimal procedures for known and unknown behavior policies, including the Switch estimator and Chebyshev polynomial-based estimator.
result Plug-in estimator achieves optimal competitive ratio up to a logarithmic factor when behavior policy is unknown.

Every infinite order mapping class has an infinite order action on the homology of some finite cover.

problem Proving every infinite order mapping class has an infinite order action on the homology of some finite cover.
method Theory of homological shadows and Fourier analysis.
result There exists a finite solvable cover and a lift of an infinite order mapping class with an infinite order action on the homology.

Develops a new method for statistical optimal allocation problems.

problem Statistical optimal allocation problems with constraints.
method Functional differentiability approach and Hadamard differentiability of value functions.
result Validates margin assumption for fast convergence rate of plug-in methods.

Develops a robust method for image reconstruction from limited data.

problem Inference of unknown images from few measurements, often ill-posed.
method Introduces DPnP, a diffusion plug-and-play method combining likelihood and score-based samplers.
result Establishes performance guarantees for DPnP, demonstrating robustness and efficiency.

The paper analyzes rates of convergence for optimal transport map estimators using barycentric projections.

problem Estimating optimal transport maps from data sampled according to two distributions.
method Comprehensive analysis of rates of convergence for plug-in estimators defined via barycentric projections.
result New stability estimate for barycentric projections under minimal smoothness assumptions.

We construct a new aperiodic symplectic plug and hence new smooth counterexamples to the Hamiltonian Seifert conjecture in R^{2n} for n>2. In other words, we develop an alternative procedure, to those of V. L. Ginzburg and M. Herman, for constructing smooth Hamiltonian flows, on the standard symplectic R^{2n} for n>2, …

2001-01-23abs ↗pdf ↗

Plug-and-play L-GM-AMP improves CS recovery for any i.i.d. source prior.

problem Efficiently recovering signals from compressed measurements with unknown priors.
method Deep learning with Gaussian-mixture model to approximate source prior, combined with learned denoising.
result L-GM-AMP achieves state-of-the-art performance without prior knowledge of source distribution.

New method improves online covariance estimation for SGD.

problem Improving online covariance estimation for SGD.
method Proposes a de-biased covariance estimator that eliminates second-order derivatives.
result Achieves a convergence rate of n(α1)/2lognn^{(α-1)/2} \sqrt{\log n}, outperforming existing methods.

Develops non-standard analysis for coherent risk estimation.

problem Estimating coherent risk measures in financial contexts.
method Non-standard analysis, hyperfinite representations, discrete Kusuoka formulae, plug-in asymptotics.
result Uniform almost sure consistency and asymptotic normality of spectral plug-in estimators.

A new method debiases multiple target parameters without IFs.

problem Debiasing multiple target parameters in nonparametric models.
method Kernel Debiased Plug-in Estimation (KDPE) using TMLE and reproducing kernel Hilbert spaces.
result KDPE simultaneously debiases all pathwise differentiable target parameters.

We use the Heegaard Floer obstructions defined by Grigsby, Ruberman, and Strle to show that forty-six of the sixty-seven knots through eleven crossings whose concordance orders were previously unknown have infinite concordance order.

2008-05-15abs ↗pdf ↗

The paper addresses supervised learning with censored data, proposing a method to estimate risk.

problem Learning from censored data in regression problems.
method Proposes a plug-in estimate of the true risk based on a Kaplan-Meier estimator of the censorship distribution.
result The learning rate of minimizers of the proposed risk functional is of order \(O_{\mathbb{P}}(\sqrt{\log(n)/n})\).

Let (W,S) be a finite rank Coxeter system with W infinite. We prove that the limit weak order on the blocks of infinite reduced words of W is encoded by the topology of the Tits boundary of the Davis complex X of W. We consider many special cases, including W word hyperbolic, and X with isolated flats. We establish tha…

2013-01-05abs ↗pdf ↗

This paper provides a method for noise-calibrated inference from DP synthetic data.

problem Inference from DP synthetic data is often miscalibrated and lacks principled uncertainty quantification.
method Release DP sufficient statistics, perform noise-calibrated likelihood-based inference, and optional synthetic data generation.
result Asymptotic normality and valid confidence intervals for the plug-in DP MLE.