The regular genus of certain 4-manifolds is determined, providing new insights.
problem Determining the regular genus of higher-dimensional closed PL manifolds.
method Using crystallization graphs and combinatorial topology, the regular genus is calculated for specific manifolds.
result The regular genus of S2imesS1imesS1 is 6, and S1imesS1imesS1imesS1 is 16. Paper analyzes Nyström regularization for time series forecasting with sequential sub-sampling.
problem Learning rate analysis of Nyström regularization for τ-mixing time series. method Banach-valued Bernstein inequality and integral operator approach for τ-mixing sequences. result Almost optimal learning rates for Nyström regularization with sequential sub-sampling.
Curve shortening flow's regularity depends on initial conditions after a certain time.
problem Understanding the regularity of evolving curves under curve shortening flow.
method Proposing and proving principles of controllable regularity based on initial conditions.
result No regularity estimate holds before a specific time, A/π. Paper solves a complex stopping problem using regularization and HJB equations.
problem Time-inconsistent mean-variance optimal stopping problem
method Vanishing regularization method to derive HJB equations and prove existence of solutions
result Formally recovers variational inequalities for original problem
Alternative approach to regularize time-dependent singular Lagrangian systems.
problem Regularizing time-dependent singular Lagrangian systems.
method Employing the coisotropic embedding theorem and the Tulczyjew isomorphism.
result Uniqueness of the Lagrangian regularization to first order.
Improved prediction of hierarchical time series using structured regularization.
problem Making coherent forecasts for hierarchical time series.
method Structured regularization method for bottom-level time series predictions.
result Superior prediction accuracy and computational efficiency compared to previous methods.
A simple regularization technique speeds up training of Neural ODEs.
problem Training Neural ODEs is computationally expensive.
method Randomly sampling the end time of the ODE during training.
result Significantly decreases training time and improves performance.
Sharp Hölder regularity found for complex Frobenius theorem coordinates.
problem Finding optimal Hölder-Zygmund regularity for complex Frobenius theorem coordinates.
method Analyzing necessary and sufficient conditions for coordinate charts achieving the theorem's structure.
result The optimal Hölder-Zygmund regularity for coordinate charts is shown to be α. Adversarial regularization helps learn interpretable shapelets for time series classification.
problem Difficult to interpret learned shapelets in time series classification.
method Use of adversarial regularization to constrain model to learn more interpretable shapelets.
result Adversarially regularized method learns interpretable shapelets.
Regularization timing affects deep network performance, not just its presence.
problem The timing of regularization in deep networks impacts their performance.
method Analysis of different datasets, architectures, regularization methods, and learning rate schedules.
result The critical period for regularization in deep networks is decisive of final performance.
Paper studies heat flow for maps on manifolds, avoiding singularities.
problem Avoiding singularities in heat flow for maps on manifolds.
method Introduces regularized conformal heat flow for n-harmonic maps. result Regularized n-conformal heat flow does not develop finite time singularities. RSAC improves lightweight continuous learning efficiency.
problem Excessive training time and memory usage in continuous learning.
method Regularized subspace approximation classifier with feature reduction and regularization.
result RSAC achieves more efficient continuous learning than prior methods.
In this article, we construct a crystallization of the mapping torus of some (PL) homeomorphisms f:M→M for a certain class of PL-manifolds M. These yield upper bounds for gem-complexity and regular genus of a large class of PL-manifolds. The bound for the regular genus is sharp for the mapping torus of some (PL…
Proposes tPARAFAC2 for tracking evolving patterns in time-evolving data.
problem Lack of temporal regularization in tensor factorizations for capturing evolving patterns.
method Temporal PARAFAC2 (tPARAFAC2) with temporal regularization.
result tPARAFAC2 accurately captures evolving patterns better than existing methods.
A new algorithm speeds up EEG source localization using ℓ1 regularization.
problem Challenging inverse problem in mapping EEG readings to brain activity.
method Formulated as a graphical generalized elastic net inverse problem, solved with a variable projected algorithm (VPAL).
result VPAL provides faster and more accurate EEG source localization compared to existing methods.
MGD with early stopping tends to ridge regularization in least squares regression.
problem Characterizing the implicit regularization of MGD with early stopping.
method Continuous-time view of MGD (momentum gradient flow) and comparison with explicit ridge regularization.
result Under optimal tuning, the risk of MGF is no more than 1.54 times that of ridge.
Sparse Tucker decomposition with graph regularization improves time series forecasting accuracy.
problem High-dimensional time series forecasting with over-parameterization issue.
method Sparse Tucker decomposition and graph regularization for tensor-based model.
result Non-asymptotic error bound and superior performance in numerical experiments.
Entropy regularization improves MFG learning efficiency and stability.
problem Improving Mean Field Game learning efficiency and stability.
method Entropy regularization applied to MFG with learning.
result Entropy regularization yields time-dependent policies and stabilizes convergence.
New method speeds up solving L0-regularized least-squares problems.
problem Solving L0-regularized least-squares problems efficiently.
method Safe peeling for Branch-and-Bound algorithm.
result Significant gains in solving time and node exploration.
New algorithm speeds up path computation for optimal models.
problem Finding the exact path of optimal models from a finite set.
method Dynamic programming approach for linear time computation.
result Dynamic programming achieves linear time for breakpoints computation.
Paper uses replica method to study overfitting in Cox model.
problem Overfitting in Cox model when p ~ N.
method Replica method from statistical physics.
result Established relationship between optimal regularization and p/N.
The paper proves smoothness of Brakke flows up to the end-time.
problem Smoothness of Brakke flows up to the end-time.
method Local regularity theorem for Brakke flows, extending White's theorem.
result Smooth extension of Brakke flows up to the end-time.
Regularizes RNNs to handle long-range dependencies and multiple time scales.
problem Identifying nonlinear dynamical systems with varying time scales and long-range dependencies.
method A simple regularization scheme for vanilla RNNs with ReLU activation.
result Regularized RNNs can solve long-range dependency problems and express slow time scales.
We show that #8(S^2 times S^3) admits two 8-dimensional complex families of inequivalent non-regular Sasakian-Einstein structures. These are the first known non-regular Sasakian-Einstein metrics on this 5-manifold.
We establish continuous maximal regularity results for parabolic differential operators acting on sections of tensor bundles on Riemannian manifolds. As an application, we show that solutions to the Yamabe flow instantaneously regularize and become real analytic in space and time. The regularity result is obtained by i…
Smoothness of graphs evolving by fractional mean curvature is proven.
problem Evolution of graphs by fractional mean curvature.
method Analytic semigroup approach to nonlocal quasilinear evolution equation.
result Short time existence, uniqueness, and optimal Hölder regularity of classical solutions.
Study shows continuity and geometric regularity of Kähler-Ricci flow blow-up limits.
problem Geometric regularity of blow-up limits of the Kähler-Ricci flow.
method Established geometric regularity for Type I blow-up limits based on sequences of Ricci vertices.
result The limiting flow is continuous in time in Gromov-Hausdorff and Gromov-W1 distance. Regular shrinkers describe blow-up limits of a finite-time singularity of the motion by curvature of planar network of curves. This follows from Huisken's monotonicity formula. In this paper, we show that there is only one regular shrinker with 2 closed regions. This regular shrinker is the Cisgeminate eye. Moreover, w…
Consider an integral Brakke flow (μt), t∈[0,T], inside some ball in Euclidean space. If μ0 has small height, its measure does not deviate too much from that of a plane and if μT is non-empty, then Brakke's local regularity theorem yields that (μt) is actually smooth and graphical inside a smaller b…
The paper studies regularity of spinor flow and its implications for long-time existence.
problem Analyzing the regularity of solutions to the spinor flow.
method Relating the spinor flow to a modified Ricci flow and using diffeomorphisms.
result The norm of the second order covariant derivative of the spinor field is the only obstruction for long-time existence.
Brakke flow support is parabolically rectifiable
problem Support of Brakke flow is parabolically rectifiable
method Developed approach to Brakke flow as space-time-Grassmann measure
result Standard convergence of Brakke flows is equivalent to space-time-Grassmann Radon measures
Proves and tests methods for learning time-series with breaks.
problem Learning time-series with structural breaks.
method Complete proofs and experimental validation of a regularized loss function.
result Experimental results support the validity of the techniques.
Proves long-term smoothness of curved surfaces evolving under specific curvature rules.
problem Long-term regularity of curved surfaces evolving under p-Gauss curvature flow. method Transformed the curvature flow into a Monge-Ampère equation and studied its asymptotic cone.
result Proved regularity of the interface in all dimensions for $p> rac1n$.
Study proves smooth solutions for fractional mean curvature flow within short time.
problem Short-time existence of smooth solutions for fractional mean curvature flow.
method Established using short-time existence theorem for bounded, C^{1,1}-regular initial sets.
result Smooth solutions exist for both fractional mean curvature flow and volume preserving flow.
Regularized SB process speeds up generative modeling.
problem Slow sampling and training times in SB-based models.
method Regularization terms to reduce timesteps and training time.
result Faster sampling speed for generative modeling.
Survey discusses recent advances on Brakke flows and their properties.
problem Existence and regularity of Brakke flows.
method Analyzes recent progress including new theorems and proofs.
result Proof that branching singularities trigger dynamical instability.
Flow adjusts curvature to avoid a fixed region, proving bounds and regularity.
problem Adjusting curvature flow to avoid a fixed region.
method Flow by powers of Gauss curvature, proving optimal curvature bounds and regularity.
result Proves optimal curvature bounds and long time existence for all dimensions and powers.
We prove regularity results up to the boundary for time independent generalized Maxwell equations on Riemannian manifolds with boundary using the calculus of alternating differential forms. We discuss homogeneous and inhomogeneous boundary data and show 'polynomially weighted' regularity in exterior domains as well.
The paper introduces a novel method for training neural network Stein critics with staged L2-regularization.
problem Learning to differentiate model distributions from observed data in high-dimensional settings.
method Developed a novel staging procedure for L2 regularization over training time, leveraging the advantages of highly-regularized training at early times. result Theoretical guarantees and empirical validation show that the method improves the approximation of the training dynamic by the kernel optimization, leading to faster convergence and better performance.
We show that $\scriptstyle{#9(S^2\times S^3)}$ admits an 8-dimensional complex family of inequivalent non-regular Sasakian-Einstein structures. These are the first known Einstein metrics on this 5-manifold. In particular, the bound b2(M)≤8 which holds for any regular Sasakian-Einstein $\scriptstyle{…
We recast the Calabi flow in DeGiorgi's language of minimizing movements. We establish the long time existence of minimizing movements for K-energy with arbitrary initial condition. Furthermore we establish some a priori regularity of these solutions, and that sufficiently regular minimizing movements are smooth soluti…
Paper proposes a new sparsity scheme for high-dimensional VAR models.
problem Estimation of high-dimensional VAR models with sparsity assumptions.
method Regularized estimation procedures for sparse VAR models.
result Threholding extends consistency properties of regularized estimators.
Wave-U-Net with MHE regularization improves singing voice separation.
problem Singing voice separation from mixed music recordings.
method Wave-U-Net architecture with MHE regularization applied to 1D filters.
result Adding MHE regularization to the loss function consistently improves singing voice separation.
We call a value y=f(x) of a map f:X→Y dimensionally regular if dimX≤dim(Y×f−1(y)). It was shown in \cite{first-exotic} that if a map f:X→Y between compact metric spaces does not have dimensionally regular values, then X is a Boltyanskii compactum, i.e. a compactum satisfying the equality …
Enhances neural network regularization with no extra cost.
problem Improving neural network robustness and generalization.
method Train an ensemble of weight matrices with stochastic regularization and explicitly average outputs.
result Consistent improvement on various image classification tasks.
A complex vector space V is a prehomogeneous G-module if G acts rationally on V with a Zariski-open orbit. The module is called etale if dimV=dimG. We study etale modules for reductive algebraic groups G with one-dimensional center. For such G, even though every etale module is a regular prehomogeneou…
Choquet regularization improves exploration in RL.
problem Improving exploration in reinforcement learning.
method Introducing Choquet regularizers to measure and manage exploration, reformulating RL problems and deriving explicit solutions.
result Explicit optimal distributions and Choquet regularizers for various exploratory samplers.
Paper tackles regularization and sparsification for quaternion neural networks.
problem Regularizing and sparsifying quaternion neural networks for compactness and real-time applications.
method Developed targeted regularization strategies for quaternion neural networks, extending l1 and structured regularization.
result Tailored strategies significantly reduce the number of connections and neurons, resulting in smaller, more compact networks.