1 citations · 1 across the 8 of their papers we have counts for
11 papers
Observational Indistinguishability and Integrity Blind Regions in Hybrid Quantum-Classical Workflows
Roberto Fernández-Barrios, Iker Pastor-López, Amaia Pikatza-Huerga +1
We present a claim-relative evidence/reference framework for hybrid quantum-classical workflow integrity. Observational indistinguishability yields structural blind regions, distin…
Sharp Target-Domain Certificates for Quantum-Kernel Advantage under Distribution Shift
Roberto Fernández-Barrios, Iker Pastor-López, Asier González-Santocildes +1
Quantum predictive advantage under shift usually requires known target labels. We derive the assumption-free sharp identified interval for the finite-batch advantage of a fixed can…
Candidate Comparability Before Promotion: Conditional Validation in Adaptive Network Intrusion Detection
Roberto Fernández-Barrios, Iker Pastor-López, Amaia Pikatza-Huerga +1
Adaptive network intrusion detection systems retrain classifiers after drift alarms, but an alarm detects change; it does not establish that a challenger should replace the deploye…
Conditional validity of quantum event classifiers under collider systematics and quantum estimation uncertainty
Roberto Fernández-Barrios, Iker Pastor-López, Asier González-Santocildes +1
Claims about a deployed quantum machine-learning classifier can fail when target data shift or when finite-shot quantum evaluation randomizes the model itself. We develop an inform…
Dissecting Quantum Reinforcement Learning: A Systematic Evaluation of Key Components
Javier Lazaro, Juan-Ignacio Vazquez, Pablo Garcia-Bringas
Parameterised quantum circuit (PQC) based Quantum Reinforcement Learning (QRL) has emerged as a promising paradigm at the intersection of quantum computing and reinforcement learni…
Creating, Using and Assessing a Generative-AI-Based Human-Chatbot-Dialogue Dataset with User-Interaction Learning Capabilities
Alfredo Cuzzocrea, Giovanni Pilato, Pablo Garcia Bringas
The study illustrates a first step towards an ongoing work aimed at developing a dataset of dialogues potentially useful for customer service conversation management between humans…
On the Inherent Robustness of One-Stage Object Detection against Out-of-Distribution Data
Aitor Martinez-Seras, Javier Del Ser, Aitzol Olivares-Rad +2
Robustness is a fundamental aspect for developing safe and trustworthy models, particularly when they are deployed in the open world. In this work we analyze the inherent capabilit…
Resilience to the Flowing Unknown: an Open Set Recognition Framework for Data Streams
Marcos Barcina-Blanco, Jesus L. Lobo, Pablo Garcia-Bringas +1
Modern digital applications extensively integrate Artificial Intelligence models into their core systems, offering significant advantages for automated decision-making. However, th…
Machine Learning Methods as Robust Quantum Noise Estimators
Jon Gardeazabal-Gutierrez, Erik B. Terres-Escudero, Pablo García Bringas
Access to quantum computing is steadily increasing each year as the speed advantage of quantum computers solidifies with the growing number of usable qubits. However, the inherent…
On the Improvement of Generalization and Stability of Forward-Only Learning via Neural Polarization
Erik B. Terres-Escudero, Javier Del Ser, Pablo Garcia-Bringas
Forward-only learning algorithms have recently gained attention as alternatives to gradient backpropagation, replacing the backward step of this latter solver with an additional co…
Emerging NeoHebbian Dynamics in Forward-Forward Learning: Implications for Neuromorphic Computing
Erik B. Terres-Escudero, Javier Del Ser, Pablo García-Bringas
Advances in neural computation have predominantly relied on the gradient backpropagation algorithm (BP). However, the recent shift towards non-stationary data modeling has highligh…