3-manifolds virtually 1-dominated by hyperbolic ones.
problem Domination of 3-manifolds by hyperbolic ones.
method Enhanced connection principle in good pants constructions.
result Every 3-manifold is virtually 1-dominated by a hyperbolic one.
New method ranks multivariate distributions in SMOOP using q-dominance.
problem Lack of reliable methods to rank multivariate distributions in SMOOP.
method Introduces center-outward q-dominance and develops empirical test procedures.
result Proves q-dominance implies FSD and establishes a sample size threshold.
The paper proves a comparison principle for complex Monge-Ampère flows and solves a uniqueness problem.
problem Proving uniqueness of weak solutions to the pluripotential Cauchy-Dirichlet problem.
method Proving a comparison principle for the pluripotential complex Monge-Ampère flows.
result Proves the uniqueness of the weak solution to the pluripotential Cauchy-Dirichlet problem.
Localized curvature bounds ensure harmonic maps are constant.
problem Ensuring harmonic maps are constant under localized curvature constraints.
method Localized Bochner-type rigidity theorem for harmonic maps with image-dependent curvature bounds.
result Harmonic maps are constant if minimal Ricci curvature dominates image-dependent curvature bounds.
DNNs initially capture low-frequency components before high-frequency ones, a phenomenon called F-Principle.
problem Understanding why DNNs generalize well despite overfitting.
method Empirical study on real and synthetic datasets, focusing on frequency components captured by DNNs.
result DNNs capture dominant low-frequency components first, then high-frequency ones, a phenomenon called F-Principle.
New approach analyzes ancient solutions and singularities of mean curvature flow.
problem Analyzing ancient solutions and singularities of mean curvature flow locally modeled on a cylinder.
method Introduces PDE-ODI principle to convert parabolic differential equations into systems of ordinary differential inequalities.
result Establishes the uniqueness of the bowl soliton times a Euclidean factor among ancient, cylindrical flows with dominant linear mode.
New method accelerates neural network training by focusing on flat directions.
problem Improving neural network training speed and stability.
method Bulk-SGD, interpolated gradient methods.
result Updates along the Dominant subspace can accelerate convergence but compromise stability.
Paper proposes a new learning principle based on least cognitive action.
problem Learning from temporal data, especially with time involved.
method Introduces a new learning principle based on the principle of Least Cognitive Action, which is better suited for temporal learning.
result The new principle leads to a learning process driven by differential equations, similar to natural laws.
We discuss price variations distributions in foreign exchange markets, characterizing them both in calendar and business time frameworks. The price dynamics is found to be the result of two distinct processes, a multi-variance diffusion and an error process. The presence of the latter, which dominates at short time sca…
Existence and uniqueness of bounded solutions to complex Monge-Ampère flows on Kähler manifolds.
problem Existence and uniqueness of bounded solutions to complex Monge-Ampère flows.
method Proved existence and uniqueness of bounded solutions with specific conditions on the right-hand side.
result Existence and uniqueness of bounded solutions to the complex Monge-Ampère flow on compact Kähler manifolds.
We introduce an irreversible discrete multiplicative process that undergoes Bose-Einstein condensation as a generic model of competition. New players with different abilities successively join the game and compete for limited resources. A player's future gain is proportional to its ability and its current gain. The the…
Study improves understanding and performance of FA learning rules in neural networks.
problem Lack of theoretical understanding and limited applications of Feedback Alignment (FA) methods.
method Introduces a unified framework linking synaptic weight changes to implicit regularization, providing convergence conditions and empirical evidence.
result Better alignment can enhance FA performance on complex multi-class tasks.
Abstract: Heat kernel estimates lead to compactness results for perturbations by potentials.
problem Relative compactness of perturbations by potentials.
method Heat kernel estimates and domination principle.
result Abstract results on relative compactness of perturbations by potentials.
BoostTransformer uses boosting to improve transformer efficiency and accuracy.
problem Heavy computational resources and hyperparameter tuning in transformer architectures.
method Augments transformers with boosting principles through subgrid token selection and importance-weighted sampling, incorporating a least square boosting objective directly into the pipeline.
result BoostTransformer demonstrates faster convergence and higher accuracy compared to standard transformers.
Bayesian Scattering offers a simple baseline for image data uncertainty.
problem Lack of interpretable, mathematically grounded uncertainty quantification methods for image data.
method Coupling wavelet scattering transform with a simple probabilistic head.
result Bayesian Scattering provides sensible uncertainty estimates under distribution shifts.
Develops a new framework for integrating satellite allocations in small portfolios.
problem Feasibility constraints in small portfolios, not return predictability, are the primary concerns.
method A four-layer feasibility framework: physical, economic, structural, and epistemic.
result Closed-form feasibility bounds on satellite size, turnover, and breadth without return forecasts.
Active subspaces on Riemannian manifolds generalize Euclidean principles.
problem Understanding how scalar-valued quantities change over Riemannian manifolds.
method Generalization of active subspaces from Euclidean to Riemannian spaces using parallel transport.
result The method provides a new way to study scalar-valued quantities on manifolds, differing from extrinsic approaches.
The paper analyzes cyclic Higgs bundles using elliptic systems and immersion properties.
problem Analyzing cyclic Higgs bundles and their associated immersions.
method Derive a maximum principle for elliptic systems and apply it to the Hitchin equation.
result Obtain bounds on extrinsic curvature and complete the picture for specific representations.
Connected domination numbers found for plane triangulations up to 13 vertices.
problem Finding connected domination numbers for plane triangulations.
method Analyzing triangulations of up to 13 vertices and proving the difference between connected and regular domination numbers can be arbitrarily large.
result Connected domination numbers for triangulations up to 13 vertices and upper bound for larger triangulations.
Consider the cyclic group C_2 of order two acting by complex-conjugation on the unit circle S^1. The main result is that a finitely dominated manifold W of dimension > 4 admits a cocompact, free, discontinuous action by the infinite dihedral group D_\infty if and only if W is the infinite cyclic cover of a free C_2-man…
New algorithm identifies dominant arm with high probability.
problem Identifying the arm with the highest realized reward in multi-armed bandits.
method Dominance score criterion and joint mixing and recycling mechanism.
result Identifies the best dominant arm with nearly optimal sample complexity.
Manifolds can be dominated by hypersurfaces in a sphere.
problem Dominating manifolds with hypersurfaces.
method Proving any smooth, closed, oriented manifold can be dominated by a codimension 1 submanifold of the sphere.
result Any smooth, closed, oriented manifold can be dominated by a codimension 1 submanifold of the sphere.
New framework for ranking distributions using variable fractional parameters.
problem Ordering distributions with varying steepness and local non-concavities.
method Introducing a function γ:Ro[0,1] to replace the fixed parameter in fractional SD. result Enables ranking of a broader range of distributions and incorporates dynamic greediness.
New algorithm optimizes contextual bandits with adaptive exploration.
problem Asymptotically suboptimal contextual bandit algorithms.
method Asymptotically optimal algorithm exploiting linear structure, adaptive to context distribution.
result Sub-logarithmic regret in well-behaved context distributions.
We show that non-domination results for targets that are not dominated by products are stable under Cartesian products.
A new family of stochastic dominance orders based on distortion functions.
problem Determining a continuum of dominance relations for risk assessment.
method Introducing H-distorted stochastic dominance, a generalized family of stochastic orders.
result Power-distorted stochastic dominance is particularly appealing due to its simplicity and statistical interpretations.
We analyze long-term memory properties of hourly prices of electricity in the Czech Republic between 2009 and 2012. As the dynamics of the electricity prices is dominated by cycles -- mainly intraday and daily -- we opt for the detrended fluctuation analysis, which is well suited for such specific series. We find that …
Research examines when 4-manifolds are dominated by geometric ones.
problem When is an orientable closed 4-manifold dominated by another?
method Focuses on geometric or fibred cases.
result Characterizes conditions for domination.
The study determines dominations between manifold products and semi-norm finiteness.
problem Understanding dominations between different products of manifolds.
method Analyzing the finiteness of product-associated semi-norms on fundamental classes.
result Partial answers to M. Gromov's questions on manifold product dominations and semi-norms.
New method for risk quantification using quantile processes and measure distortions.
problem Risk quantification and valuation in financial markets.
method Develops a novel stochastic valuation principle based on probability measure distortions induced by quantile processes.
result Introduces a system of subjective probability measures that indexes a stochastic valuation principle susceptible to probability measure distortions.
3-manifolds can virtually dominate others with positive simplicial volume.
problem Domination of 3-manifolds with positive simplicial volume.
method Proving existence of finite covers with degree-1 maps.
result Virtual domination of 3-manifolds with positive simplicial volume.
Modified constraint operator for localized deformation with dominant energy condition.
problem Handling localized deformation with initial data sets under the dominant energy condition.
method Introduced a modified constraint operator to absorb metric changes and established local surjectivity theorem.
result Promoted dominant energy condition to strict inequality through compactly supported variations.
Paper develops methods for analyzing forms with synchronized singularities.
problem Analyzing forms with synchronized singularities.
method Exact reduction, analytic transfer, and geometric recomposition.
result Transfer of sparse domination principle to synchronized singular forms.
Matched filters reveal optimal normalization methods for different market participants.
problem Optimizing signal extraction from order flow for market microstructure analysis.
method General matched filter principle applied to normalization strategies.
result Optimal normalization methods (e.g., SMC and STV) differ based on trader types. Study domination between non-Fuchsian surface group representations and anti-de Sitter geometry.
problem Domination problem between non-Fuchsian representations of closed surface groups.
method Analysis of branched harmonic immersions and construction of anti-de Sitter 3-manifolds.
result Found that representations admitting branched harmonic immersions dominate other representations, and constructed large families of branched anti-de Sitter 3-manifolds.
Dominant knots have isomorphic Seifert and Tait graphs.
problem Understanding knot dominance through graph isomorphism.
method Examined alternating knots and their Seifert and Tait graphs.
result Isomorphic Seifert and Tait graphs indicate dominant knots.
Modeling bank panics and financial crises with contagion channels.
problem Understanding and predicting financial crises and contagion effects.
method Develops a comprehensive model for systemic risk that includes stock-flow consistency and Asset-Liability symmetry.
result Identifies and models the dangerous spillover effects that dominate future financial crises.
New homology theory connects graph domination to subtle algebraic structures.
problem Understanding graph domination through algebraic homology.
method Interpreting überhomology as poset homology and showing its functorial properties.
result The Euler characteristic of bold homology equals the evaluation of the connected domination polynomial.
We present a probabilistic model for natural images which is based on Gaussian scale mixtures and a simple multiscale representation. In contrast to the dominant approach to modeling whole images focusing on Markov random fields, we formulate our model in terms of a directed graphical model. We show that it is able to …
3-manifolds can be virtually dominated by maps of degree 8.
problem Understanding virtual domination of 3-manifolds.
method Proving existence of finite covers with specific map properties.
result Virtual 8-dominance of 3-manifolds.
This paper shows how many samples are needed for smooth functions in high dimensions.
problem The challenge of obtaining meaningful estimates of high-order derivatives in machine learning with limited data.
method Deriving new lower bounds on the generalization error.
result Formalizes the intuition that smoothness requires enough samples close to each other.
Odd-dimensional manifolds have contact maps of non-zero degree.
problem Contact domination in odd-dimensional manifolds.
method Proving existence of maps from tight contact manifolds.
result Existence of non-zero degree maps from Liouville-fillable but not Weinstein-fillable contact manifolds.
Unified framework for efficient Frank-Wolfe optimization of Dominant Set Clustering.
problem Optimizing Dominant Set Clustering with various Frank-Wolfe algorithms.
method Unified framework for pairwise, standard, and away-steps Frank-Wolfe algorithms, with explicit convergence rates.
result Explicit convergence rates for Frank-Wolfe methods in Dominant Set Clustering.
New EI strategies using OWA and SSD for excess return.
problem Selecting EI portfolios that stochastically dominate a benchmark.
method Proposes a new OWA-based EI model and introduces a new SSD criterion.
result OWA-based EI portfolios stochastically dominate a benchmark and generate excess return.
The paper analyzes how behavioral investors make portfolio decisions using Markowitz Stochastic Dominance criteria.
problem Understanding how behavioral investors make portfolio decisions.
method Developed stochastic optimization problems and MILP models to capture subjective decision weights and probability weighting functions.
result The developed models can be used to formulate computationally tractable portfolio analysis problems.
Finite simplicial complexes dominate certain manifolds with a bounded number of simplices.
problem Understanding the finite domination of manifolds by simplicial complexes.
method Proving that a manifold can be dominated by the n-skeleton of a finite simplicial complex with a bounded number of simplices. result The total number of simplices in the n-skeleton is bounded above by a constant depending only on n and the embolic volume of the manifold. Proposes new rule for ranking investment prospects over long horizons.
problem Ranking investment prospects over long horizons considering bounded risk aversion.
method Introduces asymptotic fractional-order stochastic dominance with bounded relative risk aversion.
result Establishes equivalent conditions for the new rule under lognormal returns without mean non-negativity constraint.
Develops a new solver for optimizing with stochastic dominance constraints.
problem Optimizing with stochastic dominance constraints is computationally expensive and impractical.
method Introduces Light Stochastic Dominance Solver (light-SD) that uses Lagrangian properties and surrogate approximation.
result The light-SD solver demonstrates superior performance on various problems.