Develops a method to interpolate data for efficient inversion in nonuniform geometries.
problem Efficient inversion in nonuniform geometries where not all sources see all receivers.
method Interpolates data to an ideal acquisition geometry while solving the inverse problem using simultaneous shots.
result Illustrates the flexibility and efficiency of the approach using synthetic experiments.
The Besson-Courtois-Gallot theorem is proven for noncompact finite volume Riemannian manifolds. In particular, no bounded geometry assumptions are made. This proves the minimal entropy conjecture for nonuniform rank one lattices.
New property identifies arithmetic lattices from nonuniform lattices.
problem Characterizing arithmetic lattices among nonuniform lattices.
method Introduced Bounded Clustering (B-C) property.
result B-C property uniquely identifies arithmetic lattices.
This paper studies the covolumes of nonuniform arithmetic lattices in PU(n, 1). We determine the smallest covolume nonuniform arithmetic lattices for each n, the number of minimal covolume lattices for each n, and study the growth of the minimal covolume as n varies. In particular, there is a unique lattice (up to conj…
New approach to nonuniform learnability using measure theory.
problem Nonuniform learnability of hypotheses with varying sample sizes.
method Measure theoretic approach to redefine nonuniform learnability, introducing a new algorithm (Generalize Measure Learnability).
result Achieved statistical consistency in learning countable hypothesis classes.
Nonuniform tubular neighborhoods of curves in Euclidean n-space are studied by using weighted distance functions and generalizing the normal exponential map. Different notions of injectivity radii are introduced to investigate singular but injective exponential maps. A generalization of the thickness formula is obtaine…
New geometric theory explains nonuniform origami responses.
problem Understanding nonuniform responses in origami sheets.
method Purely geometric continuum theory capturing nonuniform, nonlinear response.
result Three modes govern nonuniform response, varying smoothly across the sheet.
New method shows Hessian estimator from random samples converges to true Hessian on complex manifolds.
problem Uncertainty in Hessian estimator accuracy on complex manifolds with boundaries and nonuniform sampling.
method Locally fitting quadratic polynomials, rigorous theoretical analysis under mild conditions.
result The Hessian estimator asymptotically converges to the true Hessian, even near boundaries.
Let Γ be a nonuniform lattice acting on real hyperbolic n-space. We show that in dimension greater than or equal to 4, the volume of a representation is constant on each connected component of the representation variety of Γ in SO(n,1). Furthermore, in dimensions 2 and 3, there is a semialgebraic subset of the repr…
We study the classification of smooth toroidal compactifications of nonuniform ball quotients in the sense of Kodaira and Enriques. Moreover, several results concerning the Riemannian and complex algebraic geometry of these spaces are given. In particular we show that there are compact complex surfaces which admit Riem…
Researchers found the smallest covolume lattices in quaternionic hyperbolic groups.
problem Finding minimal covolume lattices in quaternionic hyperbolic groups.
method Explicit description of lattices using Hurwitz integers or icosian ring.
result Uniform and nonuniform lattices of minimal covolume identified.
If Gamma is a nonuniform, irreducible lattice in a semisimple Lie group whose real rank is greater than 1, we show Gamma contains a subgroup that is isomorphic to a nonuniform, irreducible lattice in either SL(3,R), SL(3,C), or a direct product SL(2,R)^m x SL(2,C)^n$, with m + n > 1. (In geometric terms, this can be in…
The paper explores the dynamics of composite symplectic Dehn twists with nonuniform hyperbolicity.
problem Understanding the dynamics and properties of composite symplectic Dehn twists.
method Analyzing the form of nonuniform hyperbolicity, growth of Floer cohomology, and classification of symplectic mapping classes.
result Composite symplectic Dehn twists exhibit positive topological entropy and exponential growth in Floer cohomology.
Proves Zimmer's conjecture for certain actions of SL(m, Z) subgroups.
problem Proving Zimmer's conjecture for actions of finite-index subgroups of SL(m, Z) with m>3.
method Combines earlier proof techniques with new ideas for non-compact spaces, using algebraic, geometric, and dynamical tools.
result Proves Zimmer's conjecture for C2 actions by finite-index subgroups of SL(m, Z) for m>3. Deep networks adapt to function regularity and data distribution.
problem Understanding deep learning's adaptability to function regularity and data distribution.
method Developed nonparametric approximation and estimation theories for a broad class of functions using deep ReLU networks.
result Deep neural networks are adaptive to different regularity of functions and nonuniform data distributions.
Improves statistical inference using machine learning predictions with imputed data.
problem Invalid statistical inference due to machine learning prediction errors.
method Bootstrap confidence intervals for nonuniform samples and arbitrary imputed features.
result Valid confidence intervals without assumptions on machine learning model quality.
New learning algorithm for real analytic functions without gradient descent.
problem Learning real analytic functions without gradient descent.
method Taylor approximation and sampling data distribution.
result Nonuniform learning result for real analytic functions.
LA-VDM accelerates VDM using landmarks to improve data analysis.
problem Efficiently analyzing complex datasets with nonuniform sampling densities.
method Landmark-constrained two-stage normalization to accelerate VDM.
result LA-VDM accurately recovers parallel transport and converges to the connection Laplacian.
We prove noncoherence of certain families of lattices in the isometry group of the hyperbolic n-space for n greater than 3. For instance, every nonuniform arithmetic lattice in SO(n,1) is noncoherent, provided that n is at least 6.
We study upper bounds for the torsion in homology of nonuniform arithmetic lattices. Together with recent results of Calegari-Venkatesh, this can be used to obtain upper bounds on K2 of the ring of integers of totally imaginary fields.
New lattices in higher dimensions have dense surface subgroups.
problem Finding dense subgroups in higher-dimensional arithmetic lattices.
method Exhibited nonuniform arithmetic lattices in SO(n,1).
result Contain Zariski-dense surface subgroups.
Study on macroeconomic model with wealth distribution constraints.
problem Modeling macroeconomics with nonuniform wealth distribution.
method Stock Flow Consistent (SFC) model, nonuniform distribution, econometric data constraints, Monte Carlo simulations.
result Reduced constraint to a single equation, relating to mass transport and random variables.
Proposes NUQSGD for efficient parallel training of large models.
problem Efficiently compressing gradients for parallel SGD training.
method Nonuniform quantization scheme for improved theoretical and empirical performance.
result NUQSGD outperforms QSGDinf and other compression methods.
New game model improves financial stylized facts reproduction.
problem Difficulty in reproducing financial stylized facts.
method Agent-based speculation game with unique features.
result Successfully reproduces 10 out of 11 stylized facts.
We determine the number of cusps of minimal Picard modular surfaces. The proof also counts cusps of other Picard modular surfaces of arithmetic interest. Consequently, for each N > 0 there are finitely many commensurability classes of nonuniform arithmetic lattices in SU(2, 1) that contain an N-cusped surface. We also …
GeoMLE improves intrinsic dimension estimation for nonlinearly embedded data.
problem Inaccurate estimation of intrinsic dimension for nonlinearly embedded data.
method GeoMLE uses geometric properties to correct the standard MLE for flat manifolds.
result GeoMLE achieves state-of-the-art performance and is computationally efficient.
ERDMD discovers sparse, nonuniformly timed DMD models from chaotic attractors.
problem Discovering high-fidelity, nonuniformly timed DMD models from chaotic data.
method Entropic regression for nonlinear information flow detection, combined with multi-step DMD.
result ERDMD produces highly efficient and robust models with minimal complexity.
Framework for designing nonlinearities in neural networks with slope constraints.
problem Designing nonlinearities with specific properties for signal processing.
method Variational framework with regularization for slope constraints and optimization of adaptive splines.
result Adaptive nonuniform linear splines achieve global optimum in constrained optimization.
T-Rex uses EM to fit robust factor models in noisy data.
problem Robustly fitting factor models in high-dimensional data with heavy tails and outliers.
method Expectation-Maximization (EM) algorithm based on Tyler's M-estimator for elliptical distributions.
result Demonstrates robustness in direction-of-arrival estimation and subspace recovery.
This paper optimizes subsampling for large datasets using Poisson distribution.
problem Efficiently subsample large datasets for quasi-likelihood estimation.
method Derives optimal Poisson subsampling probabilities and develops a distributed subsampling framework.
result Consistent and asymptotically normal estimators are obtained.
High-order financial derivative pricing method using Radial Basis Functions.
problem Pricing financial derivatives with high accuracy and efficiency.
method Radial Basis Function generated Finite Differences for non-uniform node layouts.
result Fourth-order convergence in space with non-uniform node layouts.
Improved estimation for imbalanced data using log odds correction and optimal sampling.
problem Parameter estimation with nonuniform negative sampling for imbalanced data.
method Derive asymptotic distribution of IPW estimator, derive optimal sampling probability, propose likelihood-based estimator.
result Improved estimator has the smallest asymptotic variance.
Let Γ be a lattice in a connected semisimple Lie group G with trivial center and no compact factors. We introduce a volume invariant for representations of Γ into G, which generalizes the volume invariant for representations of uniform lattices introduced by Goldman. Then, we show that the maximality of this vo…
This paper proposes BAT to balance accuracy and robustness in adversarial training.
problem Balancing accuracy and robustness in adversarial training models.
method Blind adversarial training (BAT) uses a cutoff-scale strategy to adaptively estimate a nonuniform budget for AEs.
result BAT improves the overall robustness of adversarial training models.
If Γ is any nonuniform lattice in the group PU(2,1), let Γ be the quotient of Γ obtained by filling the cusps of Γ (i.e. killing the center of parabolic subgroups). Assuming that such a lattice Γ has positive first Betti number, we prove that for any sufficiently deep subgroup of finite index…
Hierarchical GANs reduce anomaly detection costs.
problem Balancing anomaly detection accuracy and sampling costs.
method Hierarchical GANs for nonuniform sampling and buffer zones.
result Proposed GAN-based detector outperforms baseline in detection delay and average cost of error.
New summary measures reveal geometric structure in weighted measures on manifolds.
problem Lack of geometric information in standard weight-only summaries.
method Heat-kernel entropy profiles, tracking nonuniformity across scales.
result Geometric effective sample size discounts nearby or duplicate particles.
Paper tackles online task allocation in multi-attribute social sensing.
problem Optimized task allocation in dynamic, multi-attribute social sensing.
method Quality-Cost-Aware Online Task Allocation (QCO-TA) scheme using online reinforcement learning.
result Significantly outperforms state-of-the-art baselines in sensing accuracy and cost.
Optimal multiscale learning of linear operators
problem Statistical and computational limits of learning bounded linear operators between Sobolev spaces
method Reformulate as an infinite-dimensional matrix regression problem with heterogeneous multiscale structure
result Establish minimax rates and construct a finite-resolution blockwise least-squares estimator attaining these rates
We study the geometry of nonrelatively hyperbolic groups. Generalizing a result of Schwartz, any quasi-isometric image of a non-relatively hyperbolic space in a relatively hyperbolic space is contained in a bounded neighborhood of a single peripheral subgroup. This implies that a group being relatively hyperbolic with …
Perfect clustering achieved in hypergraphs with enough interactions.
problem Complexity and lack of tractable models for analyzing hypergraphs.
method Introduced an interaction hypergraph model for analyzing hypergraphs, defined latent embeddings, and analyzed spectral estimators.
result A spectral estimate of interaction latent positions can achieve perfect clustering with enough interactions.
Characterizes Martin boundaries of certain hyperbolic groups.
problem Understanding the Martin boundaries of specific groups.
method Topological characterization using Green's function and random walks.
result Martin boundary matches CAT (0) boundary in some cases.
We construct two infinite families of ball quotient compactifications birational to bielliptic surfaces. For each family, the volume spectrum of the associated noncompact finite volume ball quotient surfaces is the set of all positive integral multiples of 38π2, i.e., they attain all possible volumes of c…
In this paper we investigate the effectiveness of Alternating Direction Implicit (ADI) time discretization schemes in the numerical solution of the three-dimensional Heston-Hull-White partial differential equation, which is semidiscretized by applying finite difference schemes on nonuniform spatial grids. We consider t…
A new gradient quantization scheme improves communication efficiency in distributed training.
problem Efficiently compressing gradients for parallel training of large models.
method Proposes a new gradient quantization scheme with theoretical guarantees and empirical performance.
result The new scheme matches and exceeds the performance of existing methods.
Unified framework for PDF estimation using MDL-based binning and tensor factorization.
problem Challenges in estimating PDFs for non-uniform, multimodal data.
method MDL-based binning with quantile cuts, tensor factorization (CPD).
result Effective PDF estimation on synthetic and real data.
Algorithm balances learning and coverage for multi-robots over unknown fields.
problem Balancing learning and coverage for multi-robots over unknown, nonuniform sensory fields.
method DSLC algorithm that schedules learning and coverage epochs, using Gaussian Process modeling and coverage regret analysis.
result Upper bound on expected cumulative coverage regret provided for DSLC.
Optimizes deep neural networks using splines and adaptive knots.
problem Improving the optimization of deep neural networks.
method Integrates a second-order total-variation criterion to optimize activation functions, deriving a representer theorem.
result Optimal network configurations can be achieved with nonuniform linear splines with adaptive knots.