New model outperforms Neural ODEs while being more efficient.
problem Stable convergence and existence guarantees for implicit-depth models.
method Developed Monotone Operator Equilibrium Network (monDEQ) based on monotone operator theory.
result MonDEQ models outperform Neural ODEs and are more computationally efficient.
New algorithm solves composite optimization problems with unknown expectations.
problem Solving composite optimization problems with unknown statistical expectations.
method Proposes a new stochastic primal-dual algorithm for composite optimization problems with unknown statistical expectations.
result Converges to a saddle point of the Lagrangian function.
Proves monotonicity of parabolic frequency on all manifolds without curvature assumptions.
problem Monotonicity of parabolic frequency on manifolds.
method Analyzes parabolic frequency function on manifolds, proving monotonicity without curvature assumptions.
result Monotonicity of parabolic frequency on all manifolds, no curvature assumption needed.
New methods solve MI problems with locally Lipschitz operators, improving solution efficiency.
problem Solving monotone inclusions with locally Lipschitz continuous operators.
method Primal-dual extrapolation methods using backtracking line search.
result Improved operation complexity for solving MI problems.
In this expository article, we discuss various monotonicity formulas for parabolic and elliptic operators and explain how the analysis of the function spaces and the geometry of the underlining spaces are intertwined. After briefly discussing some of the well-known analytical applications of monotonicity for parabolic …
Study solves optimal portfolio selection using HJB equation.
problem Optimal portfolio selection problem.
method Maximal monotone operator method, Banach fixed-point theorem, Fourier transform, monotone operators technique.
result Existence and uniqueness of solution to HJB equation.
Unified framework for variance reduction to solve monotone operator problems.
problem Large-scale monotone inclusion problems with finite sum structure.
method Developed a general framework for variance-reduced forward-backward splitting algorithms.
result Linear convergence rate under mild assumptions, with Catalyst acceleration and asynchronous implementation.
Study on optimal rates for learning algorithms with polynomial eigenvalue decay.
problem Understanding convergence rates of learning algorithms under general source conditions.
method Analyzes Tikhonov regularization and operator monotone index functions in minimax setting.
result Establishes upper convergence rates and minimum possible error for learning algorithms.
New surgery operation preserves monotonicity of Lagrangians.
problem Preserving monotonicity of Lagrangians in surgery operations.
method BSP surgery, wall-crossing formula for disk-potentials.
result BSP surgery can preserve monotonicity of Lagrangians.
For free boundary problems on Euclidean spaces, the monotonicity formulas of Alt-Caffarelli-Friedman and Caffarelli-Jerison-Kenig are cornerstones for the regularity theory as well as the existence theory. In this article we establish the analogs of these results for the Laplace-Beltrami operator on Riemannian manifold…
In this paper, we study monotonicity of eigenvalues of Laplacian-type operator −Δ+cR, where c is a constant, along the Ricci-Bourguignon flow. For c=0, We derive monotonicity of the lowest eigenvalue of Laplacian-type operator −Δ+cR which generalizes some results of Cao \cite{Cao2007}. For c=0, We derive m…
New algorithms solve monotone inclusions and convex-concave minimax problems.
problem Solving maximally monotone equations and inclusions.
method Developed new accelerated algorithms based on Halpern-type fixed-point iteration and Popov's past extra-gradient method.
result Achieved O(1/k) convergence rates for various problems. Study eigenvalues of Witten-Laplacian during mean curvature flow.
problem Eigenvalues of Witten-Laplacian and their behavior over time.
method Evolution equation for first eigenvalue derived, monotonic quantities shown.
result Interesting monotonic quantities of eigenvalues under mean curvature flow.
Monotonic differentiable sorting networks improve upon previous methods.
problem Non-monotonicity in differentiable sorting networks.
method Relaxation of conditional swap operations using sigmoid functions to ensure monotonicity.
result Monotonic differentiable sorting networks improve upon previous methods.
The paper generalizes eigenvalue evolution under geometric flows.
problem Eigenvalue evolution under geometric flows.
method Defined and analyzed geometric flows on Riemannian manifolds.
result Derivation of formulas and monotonicity results for eigenvalues.
Non-affine aggregation rules cannot preserve monotonicity in convex learning.
problem Designing non-affine aggregation rules that maintain monotonicity in convex learning.
method Proving that monotonicity of aggregated gradients is preserved only if the aggregation rule is positively affine.
result Non-affine aggregation prevents steady convergence and substantially degrades algorithmic stability.
In this paper, we mainly investigate continuity, monotonicity and differentiability for the first eigenvalue of the p-Laplace operator along the Ricci flow on closed manifolds. We show that the first p-eigenvalue is strictly increasing and differentiable almost everywhere along the Ricci flow under some curvature a…
The extragradient method fails for hypomonotone variational inequalities.
problem The convergence of the extragradient method for hypomonotone variational inequalities.
method Application of the extragradient method to hypomonotone linear operators.
result The extragradient method diverges for hypomonotone variational inequalities.
New method learns text generation orders without pre-specification.
problem Generating text in arbitrary orders without manual specification.
method Generates text in non-monotonic orders using a binary tree structure and imitation learning.
result Models can generate text without pre-specifying an order, achieving competitive performance.
Study on MMV in jump-diffusion models resolves MV's non-monotonicity issues.
problem Non-monotonicity and free cash flow stream problems in MV preferences.
method Explicit solution for MMV preferences in jump-diffusion models, proving non-negative potential measures.
result MMV resolves MV's non-monotonicity and free cash flow stream issues.
Geometrically studies Moore-Penrose inverse and polar decomposition continuity.
problem Continuity of Moore-Penrose inverse for perturbations by operator ideals.
method Geometric construction using essential codimension and Banach-Lie group action.
result Moore-Penrose inverse is a real analytic map between manifolds.
The paper solves a complex financial optimization problem using a novel mathematical technique.
problem Optimizing portfolio selection in financial markets.
method Maximal monotone operator method and Riccati transformation.
result Existence and uniqueness of a solution to the transformed parabolic equation in a Sobolev space.
This is a revised version of our short note [arxiv.math.DG/0403065] where we discuss the monotonicity of the eigen-values of the Laplacian operator to the Ricci-Hamilton flow on a compact or a complete non-compact Riemannian manifold. We show that the eigenvalue of the Lapacian operator on a compact domain associated w…
New positive mass theorem for hyperbolic 3-manifolds using Green functions.
problem Proving a positive mass theorem for asymptotically hyperbolic 3-manifolds.
method Using a monotonicity formula for the Green function of the Laplace operator.
result Established a new positive mass theorem for three-dimensional manifolds.
In this paper, under the generalized curvature-dimension inequality recently introduced by F. Baudoin and N. Garofalo, we obtain differential Harnack inequalities for the positive solutions to the Schödinger equation associated to subelliptic operator with potential. As applications of the differential Harnack inequali…
New method estimates GGLM parameters, overcoming non-convexity.
problem Estimating parameters in GGLM with dependencies.
method Monotone operator-based variational inequality method.
result Guarantees for parameter recovery in GLM and GGLM.
A new method solves variational inequality problems with multiple constraints without needing optimal Lagrange multipliers.
problem Solving variational inequality problems with multiple functional constraints efficiently.
method Constrained Gradient Method (CGM) for Minty variational inequality problems.
result The Constrained Gradient Method achieves complexity similar to projection-based methods but with cheaper oracles.
In this paper, we would like to give an answer to \textbf{Problem 1} below issued firstly in [J. Mao, Eigenvalue estimation and some results on finite topological type, Ph.D. thesis, IST-UTL, 2013]. In fact, by imposing some conditions on the mean curvature of the initial hypersurface and the coefficient function of th…
This paper shows how to learn variational inequalities fast with strong monotonicity.
problem Learning variational inequalities efficiently.
method Extending convex optimization techniques to variational inequalities with strong monotonicity.
result Fast generalization rates of Θ(1/ε) for learning variational inequalities. The paper proves an inequality for symmetric polynomials under a fixed point measure.
problem An inequality for elementary symmetric polynomials under a fixed point measure of permutations.
method Constructing differential operators to set up a monotone flow.
result The inequality is proven and is sharp.
In this paper, we prove that the first eigenvalues of −Δ+cR (c≥41) is nondecreasing under the Ricci flow. We also prove the monotonicity under the normalized flow for the case c=1/4, and r≤0.
Differentiable sorting and rank normalization are incompatible, with specific conditions for admissibility.
problem Incompatibility between differentiable sorting and rank normalization.
method Formalized admissibility through monotone invariance, batch independence, and rank-space stability conditions.
result Different gap-sensitive and batchwise relaxations of rank normalization violate the conditions for admissibility.
By studying the monotonicity of the first nonzero eigenvalues of Laplace and p-Laplace operators on a closed convex hypersurface Mn which evolves under inverse mean curvature flow in Rn+1, the isoperimetric lower bounds for both eigenvalues were founded.
Develops a first-order interior-point method for solving constrained variational inequalities.
problem Solving constrained variational inequalities with nontrivial constraints.
method ADMM-based interior-point method for constrained VIs (ACVI).
result First-order interior-point method with global convergence guarantees for general cVI problems.
The paper studies how the first eigenvalue of a weighted p-Laplacian changes over time on Riemannian manifolds.
problem Evolution of the first eigenvalue of weighted p-Laplacian.
method Investigates monotonicity of the first eigenvalue problem along the Ricci-Bourguignon flow.
result First variation formula for eigenvalues and various monotonic quantities are derived.
Paper proposes DSBA, a stochastic algorithm for decentralized learning that converges faster and uses sparse communication.
problem Efficient decentralized learning with sparse communication for complex problems.
method Generalizes decentralized optimization to monotone operator root finding, proposes DSBA algorithm.
result DSBA converges geometrically with a rate linearly depending on problem condition number and uses sparse communication.
Mathematical analysis shows Brexit affects EU voting power in unexpected ways.
problem Effects of Brexit on EU voting power and distribution of power.
method Mathematical analysis using Penrose--Banzhaf Index and normal approximation.
result Non-monotonic effects of Brexit on EU voting power, exacerbated by EU population vector.
We prove general reflection positivity results for both scalar fields and Dirac fields on a Riemannian manifold, and comment on applications to quantum field theory. As another application, we prove the inequality CD≤CN between Dirichlet and Neumann covariance operators on a manifold with a reflection.
The paper studies inequalities for fractional GJMS operators on conformal infinity.
problem Deriving comparison inequalities for fractional Yamabe constants.
method Using Poincaré-Einstein manifolds and fractional GJMS operators.
result Two comparison inequalities for fractional Yamabe constants are derived.
Gradient descent on neural nets often operates at the Edge of Stability, where loss behavior is complex but loss decreases over time.
problem Understanding the optimization dynamics of neural networks at the Edge of Stability.
method Empirical demonstration of gradient descent behavior in neural network training.
result Gradient descent on neural networks typically occurs at the Edge of Stability, where loss behavior is non-monotonic but loss decreases over time.
Let (M,g) be an n-dimensional compact Riemannian manifold (n>1) whose metric g(t) evolves by the generalized abstract geometric flow. This paper discusses the evolution, monotonicity and differentiability for the first eigenvalue of the p-Laplacian on (M,g(t)) with respect to time evolution. We prove that t…
New adaptive stepsizes improve Douglas-Rachford and ADMM convergence.
problem Finding zeros of the sum of two maximal monotone operators.
method Developed adaptive stepsize rules for non-stationary DR and ADMM methods.
result Proved convergence of non-stationary DR and ADMM methods with adaptive stepsizes.
Unified algorithms for structured sparsity problems with optimal convergence rates.
problem Solving minimization problems with structured sparsity assumptions.
method Unified continuum of preconditioned forward-backward operator splitting algorithms and accelerated algorithms.
result The continuum of algorithms attains the theoretically optimal rate of convergence.
Solves capillary curvature problems for specific p values.
problem Capillary curvature problems for −n<p<1 and θ∈(0,2π). method Iterative scheme based on capillary Minkowski problem and capillary curvature image operators.
result Fixed points of capillary curvature image operators correspond to solutions of capillary Lp-Minkowski problem. Insider trading is reduced when penalized, affecting expected penalties in a non-monotone way.
problem Reducing insider trading behavior when insiders face legal penalties.
method Characterized via a backward stochastic differential equation (BSDE) with a non-linear operator.
result The insider's expected penalties are non-monotone in the fee structure and determined by relative entropy.
In this paper, we study the evolving behaviors of the first eigenvalue of Laplace-Beltrami operator under the normalized Ricci flow of model geometries. In every Bianchi class, we estimate the derivative of the eigenvalue. Then we construct monotonic quantities under the Ricci flow and obtain upper and lower bounds for…
We prove trace identities for commutators of operators, which are used to derive sum rules and sharp universal bounds for the eigenvalues of periodic Schroedinger operators and Schroedinger operators on immersed manifolds. In particular, we prove bounds on the eigenvalue lambda_{N+1} in terms of the lower spectrum, bou…
Universal algorithm for variational inequalities adapts to smoothness and noise.
problem Variational inequalities from monotone operators, including convex minimization and saddle-point problems.
method Mirror-Prox algorithm with adaptive step-size.
result Achieves optimal rates for smooth/non-smooth, noisy/noiseless settings without prior knowledge.