Improved curvature estimation for digital objects.
problem Estimating curvature profiles in digital images.
method Extending MDCA curvature estimator to λ-MDCA, proving convergence, and evaluating performance.
result λ-MDCA curvature estimator converges with order $\mathcal{O}(h^{ rac13})$ and performs better near corners.
The paper constructs graph models for n-dimensional manifolds.
problem Creating digital models of n-dimensional manifolds.
method Constructing graph models using LCL collections of n-cells.
result Digital models retain topological properties of continuous manifolds.
Proposes a method for modeling random objects in metric spaces using random effects.
problem Modeling random objects in non-Euclidean spaces with random effects.
method Nonlinear Fréchet-based algorithm for M-estimation.
result Consistent estimation of prediction target under random-effects formulation.
This paper explores IT governance for CBDC adoption in financial markets.
problem Adopting CBDC requires new IT governance models in financial markets.
method Systematic Literature Review (SLR) of 14 studies on IT resources and governance models.
result Many IT resources and preliminary IT designs for CBDC governance identified.
EHR-MPC optimizes sepsis treatment using digital twins and inference-time control.
problem Optimal sepsis treatment policies are contested and difficult to adapt during inference.
method EHR-MPC decouples learning patient dynamics from treatment optimization, enabling inference-time control over learned digital twins.
result EHR-MPC achieves comparable off-policy performance and improved simulation performance compared to RL baselines.
ShapeShifter attacks physical object detectors with robust adversarial perturbations.
problem Crafting physical adversarial perturbations to fool object detectors.
method Adapted Expectation over Transformation technique for object detection.
result Successfully generated adversarial perturbations that fool Faster R-CNN.
Study optimal bidding strategies for digital ads targeting purchases and health campaigns.
problem Optimizing advertising strategies in digital channels.
method Continuous-time models encoding user behavior and auction mechanisms, semi-explicit formulas for optimal bidding.
result Semi-explicit formulas for optimal value and bidding policy for different types of advertising.
CitySim dataset captures vehicle trajectories for safety research.
problem Lack of fine-grain vehicle trajectories for safety-oriented research.
method Five-step procedure: video stabilization, object filtering, stitching, detection, and error filtering.
result CitySim dataset improves safety evaluations and facilitates digital-twin research.
Mathematical advances needed for Digital Twins, differing from traditional models.
problem Foundational mathematical advances required for Digital Twins.
method Multi-scale, multi-physics modeling and coupling, different reliability criteria and uncertainty assessments.
result AI/ML methods can perform well in biomedical problems but fail in simple engineering systems.
Study develops smart contract framework for procurement under demand variability.
problem Operational and economic implications of smart contract adoption under moderate uncertainty.
method Multi-supplier model with endogenized adoption costs, supplier readiness, and inventory penalties; analytical and numerical results.
result Partial adoption strategies support moderate demand variability, while excessive digital investment reduces profitability.
Framework for discovering treatment benefits in user segments.
problem Discovering differential impacts of treatments across user subgroups.
method Combines causal inference and machine learning for user segment discovery.
result Unified approach for treatment benefit discovery and assignment.
Proposes a general deep neural network method for digital watermarking.
problem Protecting intellectual content in a massive, IoT-acquired image dataset.
method Train a neural network on an image set and use it to protect distinct test images in bulk.
result Demonstrates the robustness and practicality of the proposed method.
Two methods using low-discrepancy points improve data compression for neural networks.
problem Efficiently compress large datasets for neural network training.
method Two methods based on low-discrepancy points: digital nets with averaging and clustering.
result Second method outperforms supercompress in compression error and neural network accuracy.
New algorithm trains living neural networks for machine learning tasks.
problem Training living neural networks for machine learning applications.
method Supervised STDP-based learning algorithm considering neuron engineering constraints.
result 74.7% accuracy on MNIST handwritten digit recognition benchmark.
InfoGAN learns disentangled representations without supervision.
problem Learning interpretable representations without labeled data.
method Generative adversarial network with mutual information maximization.
result InfoGAN successfully disentangles various latent variables from observations.
Paper tackles domain shift in unsupervised transductive learning.
problem Domain shift between training and test data distribution.
method Jointly solves for an asymmetric similarity metric and optimal transductive target label assignment.
result Significantly outperforms state-of-the-art algorithms in object recognition and digit classification.
Improves AI system's understanding of human inputs by creating better examples.
problem AI systems misinterpret human inputs, leading to inefficiencies.
method Developed a conditional convolutional autoencoder (CCAE) to generate better examples.
result Generated examples lead to lower error rates and require less effort to create.
LaRP framework improves object classification using random projections.
problem Efficiently approximating nonlinear kernels in high-dimensional spaces.
method Separates linear kernels and nonlinearity using a layered random projection approach.
result Notable improvement in object classification performance.
Digital money could reduce germ spread during coronavirus.
problem Spreading of germs via paper money during coronavirus.
method Policy recommendations for mobile wallets, digital currencies, and data protection.
result Adopting digital money can help reduce germ spread.
Paper addresses FL over MAC with DP constraints, proposing a novel consensus scheme.
problem Federated learning over a multiple access channel with differential privacy constraints.
method Proposes a novel consensus scheme using digital distributed stochastic gradient descent (D-DSGD) with artificial noise to preserve DP.
result Demonstrates improved convergence rate and DP level for a given MAC capacity.
Study of digital topology concepts like hyperspaces and function graphs.
problem Adapting classical topology concepts to digital topology.
method Define digital hyperspaces and function graphs, study their properties.
result Some relationships and graphical properties of digital hyperspaces and function graphs.
Corrects a false claim about a digital sphere model's contractibility.
problem Incorrect claim about MSS_18's 18-contractibility.
method Analyzes digital image MSS_18 as a digital model of S^2.
result Shows MSS_18 is 18-contractible.
Paper proposes an efficient method for bounding box annotation in object detection.
problem Manual annotation of bounding boxes is tedious and resource-intensive.
method Iterative training of object detector on small batches of labeled images, with human annotator correcting errors.
result Significant reduction in human annotation effort, up to 75%.
Study shy maps in digital topology.
problem Properties of shy maps in digital topology.
method Study properties of shy maps.
result Properties of shy maps in digital topology.
The paper highlights issues with fixed point claims in digital images.
problem Flaws in published assertions about fixed points in digital images.
method Continues a series of studies examining digital topology.
result Identifies and discusses problems with fixed point claims.
Find limiting sets for digital cones and suspensions.
problem Digital topology cone and suspension constructions.
method Identify (m, n)-limiting sets, especially (0, 0)-freezing sets.
result Discover (0, 0)-limiting sets for digital cones and suspensions.
Motivated by a geometric problem, we introduce a new non-convex graph partitioning objective where the optimality criterion is given by the sum of the Dirichlet eigenvalues of the partition components. A relaxed formulation is identified and a novel rearrangement algorithm is proposed, which we show is strictly decreas…
Corrects incorrect assertions about fixed points in digital topology.
problem Incorrect or incorrectly proven assertions about fixed points in digital metric spaces.
method Analysis of existing assertions and proofs.
result Identifies and corrects errors in published assertions.
Study AFPP of unions of convex digital disks in 2D.
problem Conditions for AFPP of union of convex disks in digital plane.
method Use results from [6] to analyze AFPP.
result Conditions for AFPP of union of convex disks.
The paper addresses flaws in fixed point assertions for digital images.
problem Deficiencies in previously published works on fixed point assertions for digital images.
method Continues a series of studies to identify and rectify issues in fixed point assertions.
result Identifies and corrects flaws in fixed point assertions for digital images.
Study minimal freezing sets in convex digital disks.
problem Finding minimal freezing sets in convex digital disks.
method Showed how to find minimal freezing sets for convex disks in digital plane.
result Found minimal freezing sets for convex disks in digital plane.
Study on cold and freezing sets in digital images.
problem Properties of cold sets in digital images.
method Analysis of properties and relationships between cold and freezing sets.
result Examined relationships between cold and freezing sets.
Incorrect fixed point assertions in digital topology are discussed.
problem Incorrect or poorly stated fixed point assertions in digital topology.
method Discussion of problematic publications in digital metric spaces.
result Clarification of incorrect fixed point assertions.
Incorrect fixed point assertions in digital topology are discussed.
problem Incorrect, incorrectly proven, or trivial fixed point assertions in digital topology.
method Continues earlier work on identifying and critiquing bad fixed point assertions.
result Clarifies the nature and extent of incorrect fixed point assertions in digital topology.
This study examines how hidden layers affect CNN performance on handwritten digit recognition.
problem Impact of hidden layers on CNN performance in handwritten digit recognition.
method Applied CNN with varying hidden layers on MNIST dataset, trained with stochastic gradient and backpropagation, tested with feedforward.
result Variations in accuracies for different hidden layers and epochs.
New algorithm localizes spoofing attackers using tropical geometry.
problem Localizing spoofing attackers in digital systems.
method Adaptive pruning algorithm based on tropical geometry.
result Adaptive pruning improves localisation accuracy.
Digital trees have approximate fixed point property, and conditions for products are explored.
problem Conditions for the approximate fixed point property in digital tree products.
method Analyzes digital trees and their products, explores conditions for the AFPP.
result Conditions are found for the AFPP in digital tree products.
Study convexity and AFPP in digital images.
problem Relationship between convexity and AFPP in digital images.
method Examined in Z^2 digital images.
result Relationship between convexity and AFPP in digital images.
Motivated by vision tasks such as robust face and object recognition, we consider the following general problem: given a collection of low-dimensional linear subspaces in a high-dimensional ambient (image) space and a query point (image), efficiently determine the nearest subspace to the query in ℓ1 distance. We …
The study examines properties of digital images using various adjacencies.
problem Properties of Cartesian products of digital images.
method Various adjacencies used to study digital images.
result Properties of digital images studied using adjacencies.
The paper highlights issues in fixed point claims in digital topology.
problem Flaws in published assertions about fixed points in digital metric spaces.
method Continues a series of studies examining these flaws.
result Identifies and discusses problems in fixed point claims.
Han discusses variants of digital covering maps and their equivalences.
problem Han's paper lacks thorough discussion on variants and their equivalences.
method Examined several variants of digital covering maps and compared their equivalences.
result Found several equivalences among the variants of digital covering maps.
SNPL learns safe policies for multi-objective interventions with high confidence.
problem Designing effective digital interventions balancing multiple objectives with noisy data.
method Leverages algorithmic stability to learn policies with high-confidence guarantees.
result Offers dramatic improvements in safety and policy gains with smaller sample sizes.
Critiques incorrect fixed point assertions in digital topology.
problem Incorrect or incorrectly proven fixed point assertions in digital topology.
method Critical review of existing assertions.
result Identifies and critiques incorrect fixed point assertions.
Examines how irreducibility and rigidity affect digital images.
problem Understanding interactions between irreducibility and rigidity in digital images.
method Analyzes Cartesian products, wedges, and cold and freezing sets.
result Interactions between irreducibility and rigidity in digital images.
Deep learning diagnoses MS from smartphone data.
problem Diagnosing MS with complex clinical assessments and tests.
method Deep-learning approach using smartphone-derived digital biomarkers.
result Deep-learning models distinguish MS with 88% accuracy.
A new method streamlines digital payment programming using smart contracts.
problem High costs and security challenges in programming smart contracts for digital payments.
method Transforming digital currencies into token streams and using configurable templates to generate specialized smart contracts.
result Reduces payment programming costs and enhances security, self-enforcement, adaptability, and controllability.
Fixed point assertions in digital topology are often incorrect or poorly stated.
problem Fixed points in digital metric spaces
method Discussing publications with bad assertions
result Identifying and correcting errors in fixed point assertions