3 citations · 4 across the 17 of their papers we have counts for
6 papers · 1 filter
Practical Quantum-Classical Feature Fusion for complex data Classification
Azadeh Alavi, Fatemeh Kouchmeshki, Abdolrahman Alavi
Hybrid quantum and classical learning aims to couple quantum feature maps with the robustness of classical neural networks, yet most architectures treat the quantum circuit as an i…
Hybrid Action Reinforcement Learning for Quantum Architecture Search
Jiayang Niu, Yan Wang, Jie Li +4
Reinforcement learning-based Quantum Architecture Search (QAS) offers a promising avenue for automating the design of variational quantum circuits, but existing methods typically d…
A Unified Contrastive-Generative Framework for Time Series Classification
Ziyu Liu, Azadeh Alavi, Minyi Li +1
Self-supervised learning (SSL) for multivariate time series mainly includes two paradigms: contrastive methods that excel at instance discrimination and generative approaches that…
Quantum Semi-Random Forests for Qubit-Efficient Recommender Systems
Azadeh Alavi, Fatemeh Kouchmeshki, Abdolrahman Alavi +2
Modern recommenders describe each item with hundreds of sparse semantic tags, yet most quantum pipelines still map one qubit per tag, demanding well beyond one hundred qubits, far…
A Geometric-Aware Perspective and Beyond: Hybrid Quantum-Classical Machine Learning Methods
Azadeh Alavia, Hossein Akhoundib, Fatemeh Kouchmeshkib +4
Geometric Machine Learning (GML) has shown that respecting non-Euclidean geometry in data spaces can significantly improve performance over naive Euclidean assumptions. In parallel…
Analyzing Advanced AI Systems Against Definitions of Life and Consciousness
Azadeh Alavi, Hossein Akhoundi, Fatemeh Kouchmeshki
Could artificial intelligence ever become truly conscious in a functional sense; this paper explores that open-ended question through the lens of Life, a concept unifying classical…