In this paper, we study the large time behavior of the heat kernel on complete Riemannian manifolds with nonnegative Ricci curvature, which was studied by P. Li with additional maximum volume growth assumption. Following Y. Ding's original strategy, by blowing down the metric, using Cheeger and Colding's theory about l…
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48 results for “limiting behavior”
Study shows flow convergence to smooth K-Ricci outside a divisor with cusp singularity.
problem Behavior of conical Kähler-Ricci flow as cone angle approaches zero.
method Analysis of limit behavior of conical Kähler-Ricci flow as cone angle tends to zero.
result Flow converges to a unique Kähler-Ricci flow with cusp singularity along the divisor.
We analyze multi-layer neural networks in the asymptotic regime of simultaneously (A) large network sizes and (B) large numbers of stochastic gradient descent training iterations. We rigorously establish the limiting behavior of the multi-layer neural network output. The limit procedure is valid for any number of hidde…
We characterize sequences of Kleinian surface groups with convergent subsequences in terms of the asymptotic behavior of the ending invariants of the associated hyperbolic 3-manifolds. Asymptotic behavior of end invariants in a convergent sequence predicts the parabolic locus of the algebraic limit as well as how the a…
We use a generalization of the Gibbons-Hawking ansatz to study the behavior of certain non-compact Calabi-Yau manifolds in the large complex structure limit. This analysis provides an intermediate step toward proving the metric collapse conjecture for toric hypersurfaces and complete intersections.
The paper examines the behavior of Weierstrass measures on stable curves as they approach a nodal stable curve.
problem Understanding the behavior of Weierstrass measures on stable curves as they approach a nodal stable curve.
method Analyzing the limiting behavior of Weierstrass measures on a smooth curve of genus as it approaches a nodal stable curve in the Deligne-Mumford compactification.
result The Weierstrass measures on a stable rational curve at the boundary of are completely determined.
The study examines the asymptotic behavior of extremal length in Teichmüller space.
problem Understanding the asymptotic behavior of extremal length along Teichmüller rays.
method Analyzing the limit of extremal length and deriving formulas for limiting Teichmüller distance and detour metric.
result An explicit formula for the limiting Teichmüller distance and a necessary and sufficient condition for Teichmüller rays to be asymptotic.
KFAtt improves CTR prediction by modeling user behavior with Kalman filtering attention.
problem Improving CTR prediction in personalized e-commerce search engines.
method KFAtt combines Kalman filtering with attention mechanisms to model user behavior.
result KFAtt outperforms existing methods in CTR prediction, achieving better performance in both offline and online settings.
On the limit behavior of metrics in continuity method to Kahler-Einstein problem in toric Fano casemath.DG
This is a continuation of paper \cite{Li}. On any toric Fano manifold, we discuss the behavior of limit metric of a sequence of metrics, which are solutions to a continuity family of complex Monge-Ampere equations in Kahler-Einstein problem. We show that the limit metric satisfies a singular complex Monge-Ampere equati…
Study explores factors influencing saving behavior among Dhaka employees.
problem Factors influencing saving behavior among Dhaka employees.
method Quantitative approach with cross-sectional survey design, structured questionnaire, descriptive statistics, reliability analysis, regression analysis.
result Only financial management practices had a significant positive relationship with saving behavior.
Study models human investors' sub-rational behavior in financial markets.
problem Lack of a comprehensive model for human sub-rationality in financial markets.
method Flexible reinforcement learning model incorporating five human sub-rational aspects.
result Model accurately reproduces human behavior and reveals insights into market dynamics.
In order-driven markets, limit-order book (LOB) resiliency is an important microscopic indicator of market quality when the order book is hit by a liquidity shock and plays an essential role in the design of optimal submission strategies of large orders. However, the evolutionary behavior of LOB resilience around liqui…
We develop a theory of "minimal -graphs" and characterize the behavior of limit laminations of such surfaces, including an understanding of their limit leaves and their curvature blow-up sets. We use this to prove that it is possible to realize families of catenoids in euclidean space as limit leaves of sequences of…
In this paper, we will study the limiting behavior of the Brown-York mass of the coordinate spheres in an asymptotically flat manifold. Limiting behaviors of volumes of regions related to coordinate spheres are also obtained, including a discussion on the isoperimetric mass introduced by Huisken \cite{Huisken}. We will…
Study boundary behavior of limit interfaces in Riemannian manifolds without convexity assumptions.
problem Boundary behavior of limit interfaces in Riemannian manifolds.
method Proves limit-interface is a free boundary varifold, integer rectifiable up to boundary.
result No convexity assumption required; valid even when limit-interface clusters near boundary.
New solutions for soft materials' nonlinear behavior in growing spheroidal inclusions.
problem Understanding soft materials' behavior under microstructure effects.
method Presented an accurate semi-inverse solution for isotropically growing spheroidal inclusions.
result Existence of a non-spherical asymptotic shape and associated asymptotic pressure (isomorphic pressure).
Study long-term asset liquidation behavior with external flows.
problem Investigate optimal liquidation in presence of external flows.
method Convergence analysis of BSDEs for value function and strategy.
result Long-term liquidation may not occur due to external flows.
On the Disconnect Between Theory and Practice of Neural Networks: Limits of the NTK Perspectivecs.LG
NTK theory fails to predict practical behavior of large-width neural networks.
problem Theoretical limits of NTK do not match practical neural network architectures.
method Empirical investigation of NTK's applicability to large-width architectures.
result Practically relevant behavior of large-width architectures differs from NTK theory.
We study some asymptotic behavior of the first nonzero eigenvalue of the Lalacian along the normalized Ricci flow and give a direct short proof for an asymptotic upper limit estimate.
Riemannian groupoids and solitons for three-dimensional homogeneous Ricci and cross curvature flowsmath.DG
In this paper we investigate the behavior of three-dimensional homogeneous solutions of the cross curvature flow using Riemannian groupoids. The Riemannian groupoid technique, introduced by John Lott, allows us to investigate the long term behavior of collapsing solutions of the flow, producing soliton solutions in the…
Agent-based modeling is a paradigm of modeling dynamic systems of interacting agents that are individually governed by specified behavioral rules. Training a model of such agents to produce an emergent behavior by specification of the emergent (as opposed to agent) behavior is easier from a demonstration perspective. W…
Infinitesimal boosting converges to a deterministic process in large sample limit.
problem Characterizing the asymptotic behavior of infinitesimal gradient boosting in large sample sizes.
method Proving convergence to a deterministic process using large sample theory and differential equations.
result The test error decreases over time in the population limit.
Understanding Kernel Ridge Regression: Common behaviors from simple functions to density functionalsphysics.comp-ph
Accurate approximations to density functionals have recently been obtained via machine learning (ML). By applying ML to a simple function of one variable without any random sampling, we extract the qualitative dependence of errors on hyperparameters. We find universal features of the behavior in extreme limits, includi…
Study the limiting shape of solutions to the L_p-Minkowski problem as p approaches negative infinity.
problem Understanding the limiting shape of solutions to the L_p-Minkowski problem as p → -∞.
method Group-invariant method to study the asymptotic shape of solutions.
result Existence of a solution Ω^(p) to the L_p-Minkowski problem that converges to a regular polytope T as p → -∞.
Framework analyzes RL agents' behavior to explain their strengths and weaknesses.
problem Understanding and explaining RL agents' capabilities and limitations.
method Data analysis and visualization of interaction history to extract interestingness elements.
result Visual summaries help humans correctly perceive agents' strengths and weaknesses.
Stochastic gradient descent (SGD) has been widely used in machine learning due to its computational efficiency and favorable generalization properties. Recently, it has been empirically demonstrated that the gradient noise in several deep learning settings admits a non-Gaussian, heavy-tailed behavior. This suggests tha…
Can multilayer neural networks -- typically constructed as highly complex structures with many nonlinearly activated neurons across layers -- behave in a non-trivial way that yet simplifies away a major part of their complexities? In this work, we uncover a phenomenon in which the behavior of these complex networks -- …
Order positions are key variables in algorithmic trading. This paper studies the limiting behavior of order positions and related queues in a limit order book. In addition to the fluid and diffusion limits for the processes, fluctuations of order positions and related queues around their fluid limits are analyzed. As a…
This paper investigates asymptotic behaviors of gradient descent algorithms (particularly accelerated gradient descent and stochastic gradient descent) in the context of stochastic optimization arising in statistics and machine learning where objective functions are estimated from available data. We show that these alg…
Study on manifolds with kinks and Gaussian kernel behavior.
problem Understanding the asymptotic behavior of graph Laplacian on manifolds with singularities.
method Introduced manifolds with kinks, derived asymptotic behavior of Graph Laplacian with Gaussian kernel, and validated results numerically.
result Asymptotic behavior of the Graph Laplacian is determined by the inward sector of the tangent space.
Financial markets can be described on several time scales. We use data from the limit order book of the London Stock Exchange (LSE) to compare how the fluctuation dominated microstructure crosses over to a more systematic global behavior.
The study reveals a transition in neural network performance from infinite-width to variance-limited behavior as dataset size increases.
problem Understanding the transition from infinite-width to variance-limited behavior in neural networks.
method Empirical study of the transition from infinite-width to variance-limited behavior as a function of sample size and network width.
result The critical sample size \( P^* \) is approximately \( \sqrt{N} \) for polynomial regression with ReLU networks.
Study on L2-boosting behavior as learning rate approaches zero.
problem Understanding the asymptotic behavior of L2-boosting algorithms with vanishing learning rates.
method Analyzes L2-boosting for regression with linear base learners, proving a deterministic limit and characterizing it as a solution to a linear differential equation.
result Proves the existence of a unique solution to the limit problem and analyzes the training and test error.
We determine the long-time asymptotic behavior of a relativistic diffusion taking values in the unitary tangent bundle of a Robertson-Walker space-time. We prove in particular that when approaching the explosion time of the diffusion, its projection on the base manifold almost surely converges to a random point of the …
We propose a method to model multi-agent behaviors with limited observation and mechanical constraints.
problem Modeling real-world multi-agent behaviors with limited observation and mechanical constraints.
method Decentralized generative models with partial observation and mechanical constraints based on hierarchical variational recurrent neural networks.
result Our method effectively models and predicts biologically plausible behaviors with minimal constraint violations.
Study examines Wang-Yau quasi-local energy in strong fields near apparent horizons.
problem Examining the behavior of Wang-Yau quasi-local energy near apparent horizons in strong fields.
method Analyzing the limit of the Wang-Yau quasi-local energy as a spacelike surface approaches an apparent horizon, considering bounded coordinate functions and spacelike mean curvature.
result The limit of the Wang-Yau quasi-local energy falls into two cases: it blows up or remains finite, depending on whether the horizon can be isometrically embedded into .
This paper analyzes DRL strategies in finance, revealing unique trading patterns and performance differences.
problem Limited research on DRL behavior in finance applications.
method Analysis of trading behaviors and purchase diversity of DRL algorithms (A2C, PPO, SAC, DDPG, TD3).
result DRL algorithms exhibit distinct trading patterns and performance differences, with A2C outperforming others in terms of cumulative rewards.
We study the asymptotic behavior of convex Cauchy hypersurfaces on maximal globally hyperbolic spatially compact space-times of constant curvature. We generalise the result of [11] to the (2+1) de Sitter and anti de Sitter cases. We prove that in these cases the level sets of quasi-concave times converge in the Gromov …
We will study the asymptotic behaviors of the colored Jones polynomials of the figure-eight knot. In particular we will show that for certain limits we obtain the volumes of the cone manifolds with singularities along the knot.
Stochastic stability is a popular solution concept for stochastic learning dynamics in games. However, a critical limitation of this solution concept is its inability to distinguish between different learning rules that lead to the same steady-state behavior. We address this limitation for the first time and develop a …
New framework for understanding infinite-width neural networks.
problem Understanding the infinite-width limit behavior of neural networks.
method General framework to study limit behavior of neural models based on hyperparameter scaling.
result Derives scaling for existing mean-field and neural tangent kernel limits and introduces new dynamically stable limits.
We describe the asymptotic behavior of Palais-Smale sequences associated to certain Yamabe-type equations on manifolds with boundary. We prove that each of those sequences converges to a solution of the limit equation plus a finite number of "bubbles" which are obtained by rescaling fundamental solutions of the corresp…
We present some recent results on the behavior of the spectrum of the differential form Laplacian on a Riemannian foliated manifold when the metric on the ambient manifold is blown up in directions normal to the leaves (in the adiabatic limit).
The study examines Hawkes processes and their long-term behavior.
problem Understanding the long-term behavior of Hawkes processes.
method Proving functional limit theorems under various conditions on the dispersion of child events.
result Functional limit theorems hold for Hawkes processes with different levels of child event dispersion.
Study of linear classifiers in infinite imbalance scenarios.
problem Behavior of linear discriminant functions in extreme imbalance conditions.
method Analysis of linear classifiers under infinite imbalance, focusing on weight function properties and limit behavior.
result Limiting coefficient vectors reflect robustness or conservatism, optimizing against worst-case alternatives.
A combination of a priority queueing model and mean field theory shows the emergence of traders' swarm behavior, even when each has a subjective prediction of the market driven by a limit order book. Using a nonlinear Markov model, we analyze the dynamics of traders who select a favorable order price taking into accoun…
Quantum spaces associated to mixed polarizations and their limiting behavior on toric varietiesmath.SG
Study explores quantum spaces on toric varieties and their limiting behavior.
problem Understanding quantum spaces on toric varieties and their limiting behavior.
method Established quantum spaces for mixed polarizations and examined one-parameter families of Kähler polarizations.
result Quantum spaces converge to as .
New flow expands hypersurfaces in hyperbolic space, showing round limiting shape for certain powers.
problem Understanding the limiting shape of hypersurfaces expanding in hyperbolic space.
method Introduced shifted inverse curvature flow with positive power for a smooth curvature function.
result For , limiting shape is always round as maximal existence time is approached.