Telecomunicaciones, información y comunicación

Projection Methods for Operator Learning and Universal Approximation

- We obtain a new universal approximation theorem for continuous (possibly nonlinear) operators on arbitrary Banach spaces using the Leray-Schauder mapping. Moreover, we introduce and study a method...

Accelerating Large Language Model Inference with Self-Supervised Early Exits

- This paper presents a modular approach to accelerate inference in large language models (LLMs) by adding early exit heads at intermediate transformer layers. Each head is trained in a self-supervised...

Greedy Heuristics for Sampling-Based Motion Planning in High-Dimensional State Spaces

- Informed sampling techniques accelerate the convergence of sampling-based motion planners by biasing sampling toward regions of the state space that are most likely to yield better solutions....

BFS versus DFS for fixed-level targets in ordered trees

- We find the average time complexity of the breadth-first search (BFS) and the depth-first search (DFS) algorithms, when one searches for a target node selected uniformly at random among all nodes at...

Construction of orientable sequences in $O(1)$-amortized time per bit

- An orientable sequence of order $n$ is a cyclic binary sequence such that each length-$n$ substring appears at most once \emph{in either direction}. Maximal length orientable sequences are known only...

Topic model based on co-occurrence word networks for unbalanced short text datasets

- We propose a straightforward solution for detecting scarce topics in unbalanced short-text datasets. Our approach, named CWUTM (Topic model based on co-occurrence word networks for unbalanced short...

ProSGNeRF: Progressive Dynamic Neural Scene Graph with Frequency Modulated Foundation Model in Urban Scenes

- Implicit neural representation has demonstrated promising results in 3D reconstruction on various scenes. However, existing approaches either struggle to model fast-moving objects or are incapable of...

Relation Extraction Model Based on Semantic Enhancement Mechanism

- Relational extraction is one of the basic tasks related to information extraction in the field of natural language processing, and is an important link and core task in the fields of information...

Ruby: Unmasking Unsafe Rust in Stripped Binaries via Machine Learning

- Rust, as an emerging system programming language, introduces $\texttt{unsafe}$ to allow developers to bypass safety checks during compilation. As a result, memory safety bugs are typically confined...

Entity Alignment Method of Science and Technology Patent based on Graph Convolution Network and Information Fusion

- The entity alignment of science and technology patents aims to link the equivalent entities in the knowledge graph of different science and technology patent data sources. Most entity alignment...

Mining and searching association relation of scientific papers based on deep learning

- There is a complex correlation among the data of scientific papers. The phenomenon reveals the data characteristics, laws, and correlations contained in the data of scientific and technological...

A Fourier analytique approach to Gaussian mixture learning

- Suppose that we are given independent, identically distributed random samples $x_1,\cdots,x_n$ from a mixture at most $k$ many $d$-dimensional spherical Gaussian distributions...

Size-varying reversible causal graph dynamics

- Consider a network that evolves according to a reversible, nearest neighbours dynamics. Is the dynamics allowed to vary the size of the network? On the one hand it seems that, being the principal...

PHINN-EEG: Topological Time-Series Analysis of Dream-State EEG -- Dynamic Betti Curves for Dream Content Classification and Topology-Conditioned Neural Signal Synthesis

- Current electroencephalography (EEG)-based dream detection relies on power spectral density (PSD) and statistical moment features, achieving a state-of-the-art area under the receiver operating...

Deep Gaussian Processes on Directed Acyclic Graphs

- Many real-world processes can be represented as compositions of functions along a directed acyclic graph (DAG). In causal modelling, these correspond to the underlying mechanisms; in engineering, to...

Forbidding anticomplete planar minors: Induced Erdős--Pósa property and Maximum Independent Set in QP

- The Erdős--Pósa theorem asserts that every graph $G$ with no $k$ disjoint cycles contains a set $X$ of $f(k)$ vertices such that $G\setminus X$ has no cycle. Robertson and Seymour showed that this...

A Quantum Path to Partial Differential Equations

- Partial differential equations are a promising application area for fault-tolerant quantum algorithms, but the subject lies between two communities with different languages: numerical analysis and...

Lean-QIT: Towards a Formal Infrastructure for Quantum Information Theory

- Quantum information theory (QIT) characterizes the capabilities and fundamental limits of quantum information processing, underpinning quantum communication, computation, and error correction....

Convex Relaxations for the Optimization of Markov Processes

- In this paper, we study the problem of optimizing Markov processes that interpolate between two prescribed probability distributions while minimizing a given cost. The main computational challenge is...

Entropy-Constrained Machine Learning with Residual Data Augmentation for Modeling Chemical Kinetics

- We present a physics-constrained machine learning framework for accelerating the direct numerical simulation (DNS) of turbulent reacting flows. The model replaces the direct evaluation of detailed...

Characterization of the basin of convexity for multi-snapshot spike deconvolution via variable projection

- We study the problem of multi-snapshot spike deconvolution, where the goal is to recover the locations of sparse impulses from their noisy convolution with a known point spread function (PSF) across...