Algorithm improves search efficiency for sparse signals using region sensing.
problem Efficiently search for sparse signals in large spaces.
method Greedy maximization of information gain using noisy average region measurements.
result Requires fewer measurements to recover signal locations compared to passive methods.
AKM2D framework speeds up anomaly detection in point-based sensing.
problem Efficient anomaly detection in point-based sensing systems.
method Adaptive Kernelized Maximum-Minimum Distance (AKM2D) framework for intelligent sequential sampling. result Balances exploration and exploitation for accurate anomaly quantification.
We prove that every bounded strictly J-convex region equipped with the Kobayashi metric is hyperbolic in the sense of Gromov. We apply this result to the study of the dynamics of pseudo-holomorphic maps.
CNNs improve InSAR coherence classification.
problem Improving demarcation of InSAR imagery regions based on coherence.
method Convolutional Neural Networks (CNNs) for preprocessing and classification.
result CNNs reduce misclassifications in incoherent regions and outperform established methods.
This paper studies confidence regions for robust estimators using Wasserstein distance.
problem Developing robust estimators against model misspecification.
method Wasserstein distributionally robust optimization.
result Asymptotic normality and optimal confidence regions for distributionally robust estimators.
This work applies deep learning to bio-sensing and video data for affective computing.
problem Lack of deep learning integration in bio-sensing for affective computing.
method Novel deep-learning-based methods applied to EEG, ECG, and video data.
result Outperforms other studies in emotion/valence/arousal/liking classification.
Method evolves spatial features from satellite imagery for regional modeling.
problem Regional summaries from high-resolution satellite data for geospatial phenomena.
method Induces spatial aggregations using Genetic Programming to optimize model performance.
result Genetic Programming synthesizes effective spatial aggregations and improves model predictions.
In this paper, the `Approximate Message Passing' (AMP) algorithm, initially developed for compressed sensing of signals under i.i.d. Gaussian measurement matrices, has been extended to a multi-terminal setting (MAMP algorithm). It has been shown that similar to its single terminal counterpart, the behavior of MAMP algo…
AUCRSS detects change points in partially observed multivariate autocorrelated data.
problem Detecting change points in multivariate autocorrelated data with limited sensing resources.
method Adaptive Upper Confidence Region (AUCRSS) with state space model (SSM), adaptive sampling policy, and generalized likelihood ratio test.
result The method outperforms existing approaches in detecting change points efficiently.
We establish some a priori geometric relations on stable minimal surfaces lying inside three-manifolds with scalar curvature uniformly bounded below. The relations are based on a slight generalization of a formula due to Castillon. We apply it to prove non-local rigidity results in the particular sense that they expres…
3D Ricci flows have bounded diameter before Type I singularities.
problem Bounding the diameter of 3D Ricci flows before Type I singularities.
method Introduced a neck-region concept and proved packing measure Ahlfors regularity.
result Uniformly bounded diameter up to Type I singular time.
A cubing strategy identifies stable hyperparameter regions for uncertainty quantification in spatial deep learning.
problem Uncertainty quantification in spatial deep learning models.
method Cubing-based diagnostic framework to recursively partition hyperparameter space and evaluate regions using scoring rules.
result Our approach produces competitive or superior predictive intervals compared to a statistical baseline model.
In this thesis, we consider domino tilings of three-dimensional regions, especially those of the form D×[0,N]. In particular, we investigate the connected components of the space of tilings of such regions by flips, the local move performed by removing two adjacent dominoes and placing them back in t…
sBayFDNN bridges deep learning and functional data analysis for complex, structured data.
problem Challenges in functional data analysis, especially for complex, continuously structured data.
method Sparse Bayesian functional deep neural network (sBayFDNN) that learns adaptive functional embeddings and interpretable region selection.
result First theoretical guarantees for a Bayesian deep functional model, ensuring reliability and statistical rigor.
New concepts of barriers and black regions defined for Lorentzian manifolds.
problem Understanding causal world-lines and horizons in Lorentzian manifolds.
method Proving properties of null hypersurfaces and their causal world-lines.
result Null hypersurfaces are semi-permeable, leading to new concepts of barriers and black regions.
In this paper, we look to address the problem of estimating the dynamic direction of arrival (DOA) of a narrowband signal impinging on a sensor array from the far field. The initial estimate is made using a Bayesian compressive sensing (BCS) framework and then tracked using a Bayesian compressed sensing Kalman filter (…
Estimates Mozambique's population using remote sensing and microcensus data.
problem Lack of frequent population estimation due to censuses lacking spatio-temporal resolution.
method Combines remote sensing, microcensus data, and transfer learning with publicly available datasets.
result Population predictions improve with footprint area estimation using transfer learning.
We show that if a closed atoroidal 3-manifold M contains a genuine lamination, then it is group negatively curved in the sense of Gromov. Specifically, we exploit the structure of the non-product complementary regions of the genuine lamination and then apply the first author's Ubiquity Theorem to show that M satisfies …
Projective embedding study for surfaces with cusp singularities.
problem Understanding stability of extremal Kähler metrics on surfaces with singularities.
method Analyzing Bergman kernel behavior in three regions, focusing on the neck region.
result L^2 projective embedding asymptotically almost balanced for surfaces with cusp singularities.
DeepCodec learns to take undersampled measurements and recover signals using deep neural networks.
problem Signal recovery from undersampled data.
method Adaptive deep convolutional neural networks for sensing and recovery.
result DeepCodec outperforms traditional ℓ1-minimization in signal recovery. Study on inventory management under uncertainty using smooth ambiguity preference.
problem Managing inventory under Knightian uncertainty with smooth ambiguity preference.
method Demonstrates continuous-time smooth ambiguity as the infinitesimal limit of Kalman-Bucy filtering with recursive robust utility. Solves forward-backward stochastic differential equations with quadratic growth to determine cost function. Derives value function and optimal control policy using variational inequalities and viscosity solutions. Transforms problem into two-dimensional singular control.
result Ambiguity drives decision-makers to act earlier, reducing the continuation region.
The paper studies convexity of products of squared Euclidean distances.
problem Convexity of products of squared Euclidean distances.
method Proved a convexity principle and applied it to products of squared distances, computed Hessian-positive regions and exact convexity levels.
result Computed exact convexity and quasiconvexity truncation levels for the two-centre model.
Unified framework for high-dimensional estimating equations inference.
problem Constructing valid inference for high-dimensional constrained estimating equations.
method Influence function based on sparse direction from linear programming.
result Unified Z-estimation theory for high-dimensional problems.
Consider a convex domain B of space. We prove that there exist complete minimal surfaces which are properly immersed in B. We also demonstrate that if D and D' are convex domains with D bounded and the closure of D contained in D' then any minimal disk whose boundary lies in the boundary of D, can be approximated in an…
ViLT is a faster vision-and-language model without convolution or region supervision.
problem Efficiency and expressive power limitations in current VLP models.
method A convolution-free Vision-and-Language Transformer (ViLT) that processes visual inputs similarly to textual inputs.
result ViLT is up to tens of times faster with competitive or better performance.
Deep learning predicts infrastructure quality in Africa using satellite imagery.
problem Expensive and limited monitoring of infrastructure quality in developing regions.
method Convolutional neural network trained on Landsat 8 and Sentinel 1 satellite imagery.
result AUROC scores of 0.881 for Electricity, 0.862 for Sewerage, 0.739 for Piped Water, and 0.786 for Roads.
The period of orbits in the restricted three-body problem depends on the enclosed region.
problem Understanding the period of orbits in the restricted three-body problem.
method Analyzing the relationship between the period and the enclosed region using the Jacobian integral.
result The period of a closed orbit is determined by the enclosed region and a function of the Jacobian integral.
New algorithms allow multiple robots to search efficiently without central coordination.
problem Efficiently locating targets in an unknown environment with multiple robots.
method SPATS and LATSI algorithms for asynchronous multi-agent active search.
result Multiple robots can independently make data-collection decisions without a central coordinator.
DASC combines social media and car sensors to improve disaster response.
problem Inconsistent reliability and inconsistent availability of human sensors.
method Hybrid social-car sensing system using game theory, feedback control, and MDP.
result DASC improves detection accuracy and efficiency in disaster response.
Stability theorem for axisymmetric manifolds with nonnegative scalar curvature.
problem Stability of positive mass theorem for specific types of manifolds.
method Proved stability in W1,p sense with technical assumptions. result Derived estimates for volumes, areas, and distances.
AdaSearch improves adaptive sensing in noisy environments.
problem Adaptive source seeking in environments with variable background signals.
method Combines global trajectory planning with principled confidence intervals.
result AdaSearch outperforms uniform sampling and other methods in simulations and hardware tests.
Study improves paddy rice yield predictions in Peru using sparse regression and climatic variables.
problem Improving precision of paddy rice yield forecasts in Peru.
method Sparse regression, Elastic-Net regularization, climatic variables, dynamic transformations.
result Improved predictive performance of paddy rice yield forecasts.
Paper develops SKPD framework for signal region detection in image regression.
problem Limited research on image region detection in high-resolution image regression.
method Sparse Kronecker Product Decomposition (SKPD) framework for matrices and tensors.
result Computed solutions converge to truth with guaranteed consistency.
DiffATD efficiently discovers targets in partially observable environments using diffusion dynamics.
problem Efficiently discovering targets in partially observable environments with limited sampling.
method DiffATD uses diffusion dynamics to maintain a belief distribution over unobserved states, balancing exploration and exploitation.
result DiffATD outperforms baselines and supervised methods in diverse domains.
Study on minimizing perimeter in unbounded convex bodies without boundary regularity.
problem Minimizing perimeter under volume constraint in unbounded convex bodies.
method Introducing uniform geometry, asymptotic cylinders, approximation, and approximation argument.
result Existence of isoperimetric regions in generalized sense and strict concavity of isoperimetric profile.
Stable capillary surfaces in weighted balls are disks.
problem Finding the shape of isoperimetric regions in weighted balls.
method Stability analysis and Hsiang symmetrization.
result Interior boundaries of isoperimetric regions in weighted balls are disks.
The Complex of Curves on a Surface is a simplicial complex whose vertices are homotopy classes of simple closed curves, and whose simplices are sets of homotopy classes which can be realized disjointly. It is not hard to see that the complex is finite-dimensional, but locally infinite. It was introduced by Harvey as an…
If Γ is a discrete subgroup of PSL(3,C), it is determined the equicontinuity region Eq(Γ) of the natural action of Γ on PC2. It is also proved that the action restricted to Eq(Γ) is discontinuous, and Eq(Γ) agrees with the discontinuity set in the sense of Kulkarni whenever the limit s…
Model predicts one-year NDVI for Four Corners region.
problem Long-term forecasting of vegetation conditions using climate attributes.
method Two-phase machine learning model using historical climate data.
result Open-source tools outperform alternative methods for NDVI forecasts.
Unified model of urban consumer behavior and mobility patterns.
problem Understanding the lifestyles and infrastructure of urban regions.
method Collective matrix factorization for dual view modeling of consumer behavior and mobility.
result Unified model reveals deeper insights into consumer behavior and mobility patterns.
We study the stability of the Positive Mass Theorem using the Intrinsic Flat Distance. In particular we consider the class of complete asymptotically flat rotationally symmetric Riemannian manifolds with nonnegative scalar curvature and no interior closed minimal surfaces whose boundaries are either outermost minimal h…
Theory explains symmetry and saddle points in nonconvex optimization landscapes.
problem Understanding the optimization landscape of nonconvex matrix factorization problems.
method Characterizing stationary points and null spaces via invariant groups.
result Identifies infinitely many nonisolated strict saddle points and global minima.
New loops found in universe's timeline, challenging traditional time direction.
problem Signature changing spacetimes and time origins.
method Developed framework for signature changing manifolds, adapted Lorentzian tools.
result Pseudo-timelike loops exist in every point on the time origin hypersurface.
A hybrid network improves MRI reconstruction from undersampled data.
problem Reducing MRI acquisition time while maintaining image quality.
method Hybrid architecture combining k-space and image domains using complex-valued and real-valued U-nets.
result Hybrid approach outperformed image-only deep learning methods in hard-to-reconstruct regions.
Proves existence and uniqueness of weak solutions for specific equations.
problem Existence and uniqueness of solutions for generalized Monge-Ampère and deformed Hermitian-Yang-Mills equations.
method Combines viscosity-theoretic and pluripotential-theoretic techniques.
result Existence and uniqueness of weak solutions in boundary cases.
Bayesian method finds robust optima in expensive black-box functions.
problem Optimizing expensive black-box functions with sensitivity to inputs.
method Bayesian optimisation using Gaussian process prior and evolutionary algorithm for sampling and evaluation.
result Locating a region of design space with relatively insensitive performance to inputs.
Nuclear norm minimization (NNM) has recently gained significant attention for its use in rank minimization problems. Similar to compressed sensing, using null space characterizations, recovery thresholds for NNM have been studied in \cite{arxiv,Recht_Xu_Hassibi}. However simulations show that the thresholds are far fro…
Active learning method for high-dimensional data using diffusion processes.
problem High-dimensional data labeling with limited labels.
method Learning intrinsic data geometries through diffusion processes on graphs, using diffusion distances to parametrize low-dimensional structures.
result The method achieves high-accuracy labelings with only a small number of carefully chosen labels.