Telecomunicaciones, información y comunicación

Regret of exploratory policy improvement and $q$-learning

- We study the convergence of $q$-learning and related algorithms introduced by Jia and Zhou (J. Mach. Learn. Res., 24 (2023), 161) for controlled diffusion processes. For exploratory policy...

Motion-Aware Animatable Gaussian Avatars Deblurring

- The creation of 3D human avatars from multi-view videos is a significant yet challenging task in computer vision. However, existing techniques rely on high-quality, sharp images as input, which are...

Sparsity-Preserving Structured Backward Error Analysis for Double Saddle Point Problems

- Backward error (BE) analysis emerges as a powerful tool for assessing the backward stability and strong backward stability of numerical algorithms. In this paper, we explore structured BEs for a...

Unsupervised Point Cloud Registration with Self-Distillation

- Rigid point cloud registration is a fundamental problem and highly relevant in robotics and autonomous driving. Nowadays deep learning methods can be trained to match a pair of point clouds, given...

Attention-Guided Perturbation Network for Industrial Anomaly Detection

- In unsupervised image anomaly detection, reconstruction-based methods learn normal patterns for data reconstruction, but often undesirably reconstruct anomalous regions at inference, resulting in...

An Improved Phase Coding Audio Steganography Algorithm

- Advances in speech synthesis have made voice cloning inexpensive and convincing, and fraud built on synthetic audio is now a practical concern. Embedding verifiable information directly in an audio...

A Communication-Efficient Digital Twin Framework for PSO-Based Swarm Navigation and Obstacle Avoidance

- Swarm-based target localization in industrial environments faces two major challenges: navigating obstacle-rich spaces and managing intensive communication among agents. This paper proposes a...

Ethical Framework for Responsible Foundational Models in Medical Imaging

- The emergence of foundational models represents a paradigm shift in medical imaging, offering extraordinary capabilities in disease detection, diagnosis, and treatment planning. These large-scale...

Artificial Leviathan: Exploring Social Evolution of LLM Agents Through the Lens of Hobbesian Social Contract Theory

- The emergence of Large Language Models (LLMs) and advancements in Artificial Intelligence (AI) offer an opportunity for computational social science research at scale. Building upon prior...

Machine Learning and Data Analysis Using Posets: A Survey

- Partially ordered sets (posets) are discrete mathematical structures that formalize the notion of comparison without forcing every pair of objects to be comparable. This makes them a natural...

Explainable Machine Learning-Based Security and Privacy Protection Framework for Internet of Medical Things Systems

- The Internet of Medical Things transcends traditional medical boundaries, enabling a transition from reactive treatment to proactive prevention. This innovative method revolutionizes healthcare by...

Matrix Completion via Nonsmooth Regularization of Fully Connected Neural Networks

- Conventional matrix completion methods approximate the missing values by assuming the matrix to be low-rank, which leads to a linear approximation of missing values. It has been shown that enhanced...

Weak Correlations as the Underlying Principle for Linearization of Gradient-Based Learning Systems

- Deep learning models, such as wide neural networks, can be conceptualized as nonlinear dynamical physical systems characterized by a multitude of interacting degrees of freedom. Such systems in the...

URLLC-Aware Proactive UAV Placement in Internet of Vehicles

- Unmanned aerial vehicles (UAVs) are envisioned to provide diverse services from the air. The service quality may rely on the wireless performance which is affected by the UAV's position. In this...

Axiomatizations of causal reasoning under indeterministic causal laws

- We investigate the generalization of causal models to the case of indeterministic causal laws that was suggested in Halpern (2000). We give an overview of what differences in modeling are enforced by...

Function approximation and nonparametric regression with binary and ternary ReLU networks

- We show that deep binary ReLU networks and deep sparse ternary ReLU networks can approximate $\beta$-Hölder functions on $[0,1]^d$. We also show that deep sparse ternary ReLU networks can achieve,...

Coded Data Rebalancing for Distributed Data Storage Systems with Cyclic Storage

- We consider replication-based distributed storage systems in which each node stores the same quantum of data and each data bit stored has the same replication factor across the nodes. Such systems...

On the Structure of Unique Shortest Paths in Graphs

- We study the combinatorial structure of systems of unique shortest paths in real-weighted graphs. We say that such a path system is \emph{strongly metrizable}.A folklore fact is that every...

Understanding Alternating Minimization for Matrix Completion

- Alternating Minimization is a widely used and empirically successful heuristic for matrix completion and related low-rank optimization problems. Theoretical guarantees for Alternating Minimization...

Learning Clifford-structured quantum unitaries and Hamiltonians

- Learning algorithms for structured quantum unitaries and Hamiltonians have primarily considered classes of processes that are local or sparse in the Pauli basis. We turn our attention to learning...

Vehicle Platooning

- Vehicle platooning offers significant benefits, including reduced energy consumption, lower emissions, improved road utilization, enhanced safety, and reduced driver fatigue. As intelligent driving...