New stability thresholds detect K-stability in Fano manifolds.
problem Detecting K-stability in Fano manifolds.
method Introducing new stability thresholds and studying geodesic rays in Kähler potentials.
result New entropy functional relates to radial entropy functional.
Introduces new weighted floating functions and affine surface areas.
problem Developing new mathematical concepts for convex bodies.
method Introducing weighted floating functions and weighted functional affine surface areas.
result New relations to traditional and classical affine surface areas.
New geometric proof of convex function differentiability and approximation.
problem Second-order differentiability of convex functions and their approximations.
method Elementary geometric approach to prove classical and recent results.
result New proofs of Lusin approximation of convex functions and bodies by C1,1 functions. As the dynamic structure of the financial markets is subject to dramatic changes, a model capable of providing consistently accurate volatility estimates must not make strong assumptions on how prices change over time. Most volatility models impose a particular parametric functional form that relates an observed price …
We give a new formula for the energy functionals E_k defined by Chen-Tian, and discuss the relations between these functionals. We also apply our formula to give a new proof of the fact that the holomorphic invariants corresponding to the E_k functionals are equal to the Futaki invariant.
In this paper, a new approach of defining Steiner symmetrization of coercive convex functions is proposed and some fundamental properties of the new Steiner symmetrization are proved. Further, using the new Steiner symmetrization, we give a different approach to prove a functional version of the Blaschke-Santalo inequa…
New integer-valued functions for Legendrian knots.
problem Understanding Legendrian knots better.
method Using Legendrian fronts to derive integer-valued linear functions.
result Introduced new invariants similar to Arnold's basic invariant.
The paper develops inequalities for log-concave functions and related surface areas.
problem Understanding log-concave functions and their inequalities.
method Establishing new inequalities through f-divergences and functional affine surface areas.
result New inequalities on functional affine surface area and bounds for Kullback-Leibler divergence.
This paper deals with some simple results about spherical functions of type δ, namely new integral formulas, new results about behavior at infinity and some facts about the related Cσ functions.
New proof of Yamabe invariant for RP^3 using harmonic functions.
problem Yamabe invariant of RP3 method Using harmonic functions
result New proof of Yamabe invariant for RP3 New proof of Positive Mass Theorem using Green's function and monotonicity formula.
problem Proving the Positive Mass Theorem in Riemannian geometry.
method Established through a newly discovered monotonicity formula for Green's function.
result New proof of the Positive Mass Theorem and Riemannian Penrose Inequality.
In this note, we construct families of functionals of the type of F-functional and W-functional of Perelman. We prove that these new functionals are nondecreasing under the Ricci flow. As applications, we give a proof of the theorem that compact steady Ricci breathers must be Ricci-flat. Using t…
Boosts Q-learning by using value function bounds.
problem Efficiently solving new tasks using past experience.
method Derives double-sided bounds on optimal value function and uses them to update Q-function.
result Boosted training performance through alternative Q-function update method.
New neural networks learn distribution functions using quantiles and moments.
problem Approximating functions of distributions in probability spaces.
method Quantile and moment neural networks, mixing quantile and moment features.
result Moment neural network outperforms others for bivariate distributions.
Researchers found new functions for spherical clothoids using special functions.
problem Developing new mathematical functions for spherical clothoids.
method Used confluent hypergeometric functions and Meixner-Pollaczek polynomials.
result Presented Cartesian coordinate functions and stereographic projections.
New characterization of geodesic currents via curve functionals.
problem Characterize geodesic currents using curve functionals.
method Purely axiomatic and combinatorial approach.
result Characterization of curve functionals dual to geodesic currents.
Introduces a new G2-Hilbert functional in G2-geometry.
problem None explicitly stated; focuses on introducing a new functional.
method Inspired by the Einstein-Hilbert functional, defines a new G2-Hilbert functional on G2-structures. result Torsion-free and nearly G2-structures are saddle critical points of the volume-normalized G2-Hilbert functional. New spectral functionals for Dirac operators with inner fluctuations computed.
problem Spectral functionals and Dirac operators with inner fluctuations.
method Extension of spectral functionals for Dirac operators with inner fluctuations.
result Computed spectral Einstein functional for Dirac operator with inner fluctuations on even-dimensional spin manifolds.
Improved understanding of translating solitons using new techniques.
problem Understanding translating solitons in geometry.
method Using a new test function and gradient estimate technique.
result Better Bernstein type result of translating solitons.
We construct new proper biharmonic functions defined on open and dense subsets of the special unitary group SU(2). Then we employ a duality principle to obtain new proper biharmonic functions from the non-compact 3-dimensional hyperbolic space H^3.
In this paper, we introduce a new functional for the conformal spectrum of the conformal laplacian on a closed manifold M of dimension at least 3. For this new functional we provide a Korevaar type result. The main body of the paper deals with the case of the sphere but a section is devoted to more general closed manif…
The Bregman divergence (Bregman distance, Bregman measure of distance) is a certain useful substitute for a distance, obtained from a well-chosen function (the "Bregman function"). Bregman functions and divergences have been extensively investigated during the last decades and have found applications in optimization, o…
New method groups similar functional covariates for better modeling.
problem Analyzing functional covariates with similar shapes.
method Coefficient shape alignment regularization approach.
result True grouping structure can be accurately identified under certain conditions.
New method uses DC functions for piecewise linear regression.
problem Regression with piecewise linear constraints.
method Estimates piecewise linear convex functions using a difference of convex functions.
result Method achieves close to minimax statistical risk and comparable performance to existing methods.
New method constructs complex-valued r-harmonic functions on Riemannian manifolds.
problem Constructing complex-valued r-harmonic functions on Riemannian manifolds.
method Introducing a new method for constructing complex-valued r-harmonic functions on Riemannian manifolds and applying it to specific semisimple Lie groups.
result The method successfully constructs complex-valued r-harmonic functions on various Riemannian manifolds, including specific Lie groups.
Constructs new explicit proper r-harmonic functions on Thurston geometries.
problem Developing proper r-harmonic functions on specific 3D geometries.
method Explicit construction of new functions for Thurston geometries.
result Explicit construction of new proper r-harmonic functions on various Thurston geometries.
New invariants study Morse functions' equivalence classes in persistent homology.
problem Understanding equivalence classes of Morse functions on spheres for persistent homology.
method Graph-equivalent and height-equivalent Morse functions, with fundamental moves.
result Established new invariants to discern Morse functions more effectively.
New loss function equivalence reveals PER's uniform sampling can be improved.
problem Improving Prioritized Experience Replay (PER) for better learning efficiency.
method Transforming non-uniformly sampled data loss functions into uniformly sampled ones.
result Some environments can replace PER with a new loss function without performance loss.
New benchmark for EEG-eye movement reconstruction from functional data.
problem Reconstructing eye movements from EEG data.
method Functional neural networks and open challenges for evaluation.
result Baseline results for consumer-grade and research-grade hardware.
New stable HOIF estimators for statistical functionals.
problem Constructing numerically stable HOIF estimators for statistical functionals.
method Developed new sHOIF estimators with provable guarantees.
result 2nd order sHOIF estimators were validated in synthetic experiments.
New CFNN architecture approximates functions with machine accuracy.
problem Function approximation with high precision.
method Chebyshev Feature Neural Network (CFNN) with learnable frequencies.
result Achieves machine accuracy in function approximation.
Greedy method adds neurons one by one for better function approximation.
problem Function approximation in neural networks.
method Growing deep neural network by adding one neuron at a time with non-linear activation.
result Accurate approximants for model problems in function approximation.
New neural network models for complex functional data analysis.
problem Complex relations between functional predictors and responses.
method Function-on-Function regression models using neural networks with continuous hidden layers.
result Demonstrated power and flexibility in handling complex functional models.
New RBF networks can approximate any continuous function.
problem Approximating any continuous function on a compact subset.
method Replacing smoothing factors with shifts in RBF networks and proving approximation under certain conditions.
result RBF networks can approximate any continuous function on any compact subset.
Explains connections between free groups and positive definite functions.
problem Understanding positive definite functions on free groups.
method Expository survey of known results and new perspectives.
result New relationships between free groups and positive definite functions.
A new method converts neural networks to function space for scalable sequential learning.
problem Challenges in gradient-based deep learning for sequential data.
method Dual parameterization of neural networks from weight to function space.
result Efficient scaling, knowledge retention, and new data incorporation.
New bound on partition function proves Kähler-Einstein stability.
problem Proving Kähler-Einstein metrics on complex manifolds.
method Quantitative bound on partition function, connecting probabilistic and quantization approaches.
result Direct analytic proof of Kähler-Einstein stability for uniformly Gibbs stable manifolds.
New results on plane graphs linked to rational functions.
problem Existence problems for plane graphs with specific degree conditions.
method Recent results on the Hurwitz existence problem.
result Description of Belyi functions corresponding to such graphs.
Bayesian optimization improves multi-start global optimization.
problem Global optimization challenges in real-world applications.
method Bayesian optimization framework to determine local search starting points.
result Bayesian optimization enhances the efficiency of multi-start local searches.
Researchers extend monotonicity formulas for harmonic functions in RCD(0,N) spaces.
problem Generalizing monotonicity formulas for harmonic functions in mRCD(0,N) spaces. method New estimates for harmonic functions and a functional version of the outer volume cone theorem.
result Proven rigidity and almost rigidity statements for harmonic functions in mRCD(0,N) spaces. Introduces new performance measures using scaled utility functions.
problem Performance measurement in financial contexts.
method Certainty equivalents defined via scaled utility functions, well-posed portfolio optimization problem under generic conditions.
result Link between portfolio dynamics, benchmark process, and utility function choice in the long-run setting.
New method prevents deep learning forgetting past by remembering key examples.
problem Catastrophic forgetting in continual learning.
method Functional regularisation using Gaussian Process formulation.
result Achieves state-of-the-art performance on benchmarks.
We introduce a new functional measure of tail dependence for weakly dependent (asymptotically independent) random vectors, termed weak tail dependence function. The new measure is defined at the level of copulas and we compute it for several copula families such as the Gaussian copula, copulas of a class of Gaussian mi…
New theory of distributions on spaces with singular submanifolds.
problem Defining distributions on spaces with singular submanifolds.
method Construction of thick distributions, operations, and special distributions.
result Clarified connection between thick and classical distributions.
New method finds better loss functions for neural nets.
problem Finding effective loss functions for deep neural networks.
method Optimizes multivariate Taylor polynomial parameterizations using CMA-ES.
result TaylorGLO finds loss functions that outperform existing methods.
New algorithms solve complex function optimization problems.
problem Optimizing unknown functions in competitive learning models.
method Proposed F-LCB algorithm based on UCB-type methods for nonlinear optimization.
result Regret upper bounds for the F-LCB algorithm derived from base algorithms' convergence rates.
New method optimizes unknown functions adaptively.
problem Tuning hyperparameters in machine learning.
method Gradually and adaptively optimizing an unknown function using estimated gradients.
result Advantages for tuning high dimensional hyperparameters in machine learning.
New results on the convexity of geodesic-length functions on Teichmüller space are presented. A formula for the Hessian of geodesic-length is presented. New bounds for the gradient and Hessian of geodesic-length are described. A relationship of geodesic-length functions to Weil-Petersson distance is described. Applicat…