Study critical points of Laplace eigenfunctions in polygons.
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We give a necessary condition for a closed subset of to be the set of critical points of some smooth function. In particular we obtain that for example neither the Whitehead continuum nor the p-adic solenoid are such a critical sets.
Study finds critical points in perimeter functional for fixed volume sets.
A classical result due to Blaschke states that for every analytic self-map of the open unit disk of the complex plane there exists a Blaschke product such that the zero sets of and agree. In this paper we show that there is an analogue statement for critical sets, i.e. for every analytic self-map of…
Soft Actor-Critic is a state-of-the-art reinforcement learning algorithm for continuous action settings that is not applicable to discrete action settings. Many important settings involve discrete actions, however, and so here we derive an alternative version of the Soft Actor-Critic algorithm that is applicable to dis…
Distance function to a finite set is a topological Morse function.
New framework for studying eigenvalue functionals of metrics.
Despite the empirical success of the actor-critic algorithm, its theoretical understanding lags behind. In a broader context, actor-critic can be viewed as an online alternating update algorithm for bilevel optimization, whose convergence is known to be fragile. To understand the instability of actor-critic, we focus o…
Proves critical points of ADM mass correspond to specific initial data sets.
We give an alternative proof of that a critical knot of a Morse-Bott function is a graph knot where the critical set of is a link in . Our proof inducts on the number of index-1 critical knots of .
We give an upper bound for the -dimensional Hausdorff measure of the critical set of eigenfunctions of the Laplacian on compact analytic Riemannian manifolds. This is the analog of H. Donnely and C. Fefferman result on nodal set of eigenfunctions.
The paper characterizes potential functions whose level sets are orbits in mechanical systems.
We present an actor-critic framework for MDPs where the objective is the variance-adjusted expected return. Our critic uses linear function approximation, and we extend the concept of compatible features to the variance-adjusted setting. We present an episodic actor-critic algorithm and show that it converges almost su…
Single-timescale actor-critic finds globally optimal policy.
New analysis shows actor-critic method converges efficiently in practical settings.
We study the level sets of the distance function from a boundary point of a convex set in Euclidean space. We provide a lower bound for the range of connectivity of the level sets, in terms of the critical points of the distance function in the sense of Grove-Shiohama-Gromov-Cheeger.
Random subgroups in hyperbolic spaces have full limit sets and bounded critical exponents.
We study the set of critical exponents of discrete groups acting on regular trees. We prove that for every real number between and , there is a discrete subgroup acting without inversion on a -regular tree whose critical exponent is equal to . Explicit construction of edge-index…
CARL safely adapts RL agents for safety-critical tasks.
For a finite-dimensional (but possibly noncompact) symplectic manifold with a compact group acting with a proper moment map, we show that the square of the moment map is an equivariantly perfect Morse function in the sense of Kirwan, and that the set of critical points of the square of the moment map is a countable dis…
Jakobson and Nadirashvili \cite{JN} constructed a sequence of eigenfunctions on with a bounded number of critical points, answering in the negative the question raised by Yau \cite{Yau1} which asks that whether the number of the critical points of eigenfunctions for the Laplacian increases with the corresponding …
The study counts critical points in knot cobordisms using abelian and metacyclic invariants.
The paper calculates critical points of systole function on Teichmüller space.
Enhanced Sampling Scheme improves masked generative modeling.
New algorithm solves mean-field control problems using actor-critic learning with moment neural networks.
Anosov groups' measures on limit sets are uniquely determined by their dimension.
We study the relation between critical exponents and Hausdorff dimensions of limit sets for projective Anosov representations. We prove that the Hausdorff dimension of the symmetric limit set in is bounded between two critical exponents associated respe…
Introduces Grassmann Distance Complexity to measure algebraic set nearest point problems.
Reinforcement learning in multi-agent scenarios is important for real-world applications but presents challenges beyond those seen in single-agent settings. We present an actor-critic algorithm that trains decentralized policies in multi-agent settings, using centrally computed critics that share an attention mechanism…
Critical hypersurfaces with boundary have unique shapes and properties.
Study proves rigidity of critical points in hydrophobic capillary systems.
We reformulate the option framework as two parallel augmented MDPs. Under this novel formulation, all policy optimization algorithms can be used off the shelf to learn intra-option policies, option termination conditions, and a master policy over options. We apply an actor-critic algorithm on each augmented MDP, yieldi…
Hard to approximate critical points for simple nonconvex functions.
Given an elliptic integrand of class , we prove that finite unions of disjoint open Wulff shapes with equal radii are the only volume-constrained critical points of the anisotropic surface energy among all sets with finite perimeter and reduced boundary almost equal to its closure.
The aim here is to study the concept of pairing multifractality between time series possessing non-Gaussian distributions. The increasing number of rare events creates "criticality". We show how the pairing between two series is affected by rare events, which we call "coupled criticality". A method is proposed for stud…
We define a new notion---the sub-index of a critical point of a distance function. We show how sub-index affects the homotopy type of sublevel sets of distance functions.
The paper analyzes an actor-critic algorithm with target networks for deep reinforcement learning.
This paper bounds the volume of singular and critical sets for elliptic equations with Hölder coefficients.
Given a solution to a linear homogeneous second order elliptic equation with Lipschitz coefficients, we introduce techniques for giving improved estimates of the critical set $\Cr(u)\equiv \{x:|\nabla u|(x)=0\}$. The results are new even for harmonic functions on $\dR^n$. Given such a , the standard {\it first o…
Smooth manifolds have functions with exactly two critical values.
Often noisy point clouds are given as an approximation of a particular compact set of interest. A finite point cloud is a compact set. This paper proves a reconstruction theorem which gives a sufficient condition, as a bound on the Hausdorff distance between two compact sets, for when certain offsets of these two sets …
Develops an actor-critic algorithm for risk-sensitive Markov decision processes.
The paper studies the smoothness of critical points of variational integrals on Hessian spaces.
We prove that the relative homological dimension of a Kleinian group G does not exceed 1 + the critical exponent of G. As an application of this result we show that for a geometrically finite Kleinian group G, if the topological dimension of the limit set of G equals its Hausdorff dimension, then the limit set is a rou…
Constructs foliations of critical surfaces for Hawking energy in asymptotically flat initial data sets.
In this paper we study solutions to elliptic linear equations , either on or a Riemannian manifold, under the assumption of Lipschitz control on the coefficients . We focus our attention on the critical set $Cr(u)\equiv\{x:|\nabla u|…
Paper proves Łojasiewicz inequalities near simple bubble trees on surfaces.
We develop an off-policy actor-critic algorithm for learning an optimal policy from a training set composed of data from multiple individuals. This algorithm is developed with a view towards its use in mobile health.