Telecomunicaciones, información y comunicación

PIKS: Universal Physics-Informed Kernel Methods

- Physics-informed machine learning incorporates physical principles --often expressed via differential operators-- into data-driven models. While physics-informed neural networks (PINNs) dominate...

Combinatorial Bounds for Codes over Metric Spaces: Ramsey-Sidorenko Thresholds and Subgraph Counts

- This paper investigates the relationship between coding theory and extremal combinatorics by representing codes in general metric spaces as independent sets in proximity graphs. We provide a...

Detecting seizure onset and offset times using human intelligence: A critical-transitions-based approach

- Most existing seizure detection algorithms require extensive pre-processing of the data and rely on heuristic or currently unexplainable machine learning approaches. These approaches often struggle...

The Keyl-Werner algorithm is not optimal for spectrum estimation

- We give an algorithm which, given $n = O(d^2 \cdot (\log\log(d)/\log(d))^2)$ copies of $\rho$, estimates the eigenvalues of $\rho$ to constant error in total variation distance. Thus, we can learn...

Classical and Quantum MacWilliams Transforms as Spin Kinematics

- Spin is the hidden engine behind the zoo of MacWilliams transforms in weight enumerator theories - not only for qubits and qudits, but even for classical codes. From nothing more than a split into...

On the robustness of noisy solutions in non-convex neural networks

- Optimization in non-convex neural network models is strongly influenced by the geometry of the solution space: sparse, isolated, point-like clusters are typically algorithmically inaccessible,...

Reliability Functions of Quantum Soft Covering and Privacy Amplification via a Mixed-Order Rényi Divergence

- In this paper, we introduce a novel mixed-order Rényi divergence and investigate its fundamental properties. Using this divergence, we define a family of mixed-order order-two Rényi mutual...

Reselection in the game of best choice

- We investigate a remarkable probability distribution on the symmetric group, due to Steck from the early 1970's, arising from a natural process that intertwines continuous and discrete selections...

Breaking the Curse with BAND: Nonparametric Distribution Estimation in High Dimensions

- Minimax-optimal rates for multivariate distribution estimation are known to suffer from the curse of dimensionality. We propose a sparse Bayesian network approach in which each conditional...

Using large language models to probe the limits of atom-centered structural descriptors

- Mapping an atomic structure to a compact set of geometric descriptors is an essential step in any machine-learning application to atomic-scale modeling. A powerful and widely-used approach can be...

No Data Is Not No Risk: Visibility Aware Graph-Based Inference of Business Conduct Risk

- The monitoring of business conduct risk is hindered by sparse, uneven, and visibility-biased data. Prior studies show that business conduct risk information and media coverage propagate through...

Calibrated Pressure-Observable Born and Hessian Actions for Quantum-Assisted Waveform Inversion

- We construct a pressure-consistent operator-and-readout interface for Born, adjoint, and Gauss--Newton actions in constant-density acoustic full-waveform inversion (FWI) using Schrödingerised...

Stabilizability of neural fields from thick subsets

- An important problem in neuro-engineering is the stabilization of neural fields. In applications, it is often assumed that the actuator placement can be chosen arbitrarily. In this work, we...

Conformalized Rate-Adaptive Sensing

- Many high-resolution imaging systems face the same fundamental question: when have enough measurements been collected to reconstruct an image accurately? We develop Conformalized Rate-Adaptive...

Stability in stochastic hypergraph matching II: weighted matching, routing, and batch arrivals

- Many real-life systems can be found as examples of stochastic matching on hypergraphs, such as production lines or assemble-to-order systems. Two common features are the number of items required may...

Sparse Quantum Voxel Encoding for Readout-Efficient Molecular Geometry Reconstruction on NISQ Devices

- We propose a sparse computational-basis encoding of voxelized molecular geometries that converts molecular reconstruction from full-state tomography into support recovery by computational-basis...

Early Failure Prediction from Near-Anomaly Detection: A Proactive Approach

- Anomaly detection methods often have uncertain behavior with respect to samples near the distribution boundary, limiting their ability to anticipate future anomalies. This work introduces the concept...

An Attention-Based Framework for Alzheimers Disease Classification Using Resting-State fMRI

- Accurate identification of Alzheimers disease (AD) using resting-state functional magnetic resonance imaging (rs-fMRI) remains challenging due to the high dimensionality, noise, and complex...

An Informativeness-based Clustered Federated Learning Method for Reliable Traffic Prediction in Managed Wi-Fi Networks

- Centrally-managed Wi-Fi solutions are increasingly leveraging Distributed Artificial Intelligence (AI) to predict key operational statistics of Access Points (APs) and proactively optimize network...

A Receding Horizon Control For General Assembly Line Balancing Problems

- This paper introduces a novel approach to the General Assembly Line Balancing Problem (GALBP) by utilizing a receding horizon optimal control framework. The proposed discrete model for the assembly...

A new theorem of alternatives leading to sufficient conditions for the superiorization guarantee question of Dynamic String-Averaging in the inconsistent case

- We study the Superiorization Methodology (SM) in the context of the General Dynamic String-Averaging (GDSA) method in the inconsistent case (that is, where the input operators don't have a common...