Hybrid Quantum-Classical Ridgelet Neural Networks for Portfolio Optimization
Fuente:
arXiv
Saved in:
| Main Authors: | Yadav, Bahadur, Mohanty, Sanjay Kumar |
|---|---|
| Format: | Preprint |
| Published: |
2026
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Hybrid Ridgelet Deep Neural Networks for Data-Driven Arbitrage Strategies
by: Yadav, Bahadur, et al.
Published: (2025)
by: Yadav, Bahadur, et al.
Published: (2025)
Encoder Decoder Generative Adversarial Network Model for Stock Market Prediction
by: Yadav, Bahadur, et al.
Published: (2025)
by: Yadav, Bahadur, et al.
Published: (2025)
A Systematic Review of Recent Advancements in PINN Augmented Deep Learning and Mathematical Modeling for Efficient Portfolio Management
by: Yadav, Bahadur, et al.
Published: (2026)
by: Yadav, Bahadur, et al.
Published: (2026)
A hybrid wavelet-based physics-informed neural network for portfolio management
by: Yadav, Bahadur, et al.
Published: (2026)
by: Yadav, Bahadur, et al.
Published: (2026)
Classical and Quantum Speedups for Non-Convex Optimization via Energy Conserving Descent
by: Sun, Yihang, et al.
Published: (2026)
by: Sun, Yihang, et al.
Published: (2026)
Quantum Global Minimum Finder based on Variational Quantum Search
by: Soltaninia, Mohammadreza, et al.
Published: (2024)
by: Soltaninia, Mohammadreza, et al.
Published: (2024)
Variational Optimization for Quantum Problems using Deep Generative Networks
by: Zhang, Lingxia, et al.
Published: (2024)
by: Zhang, Lingxia, et al.
Published: (2024)
Quantum Optimization via Gradient-Based Hamiltonian Descent
by: Leng, Jiaqi, et al.
Published: (2025)
by: Leng, Jiaqi, et al.
Published: (2025)
Quantum Feasibility Labeling for NP-complete Vertex Coloring Problem
by: Zhan, Junpeng
Published: (2023)
by: Zhan, Junpeng
Published: (2023)
Quantum Speedups for Markov Chain Monte Carlo Methods with Application to Optimization
by: Ozgul, Guneykan, et al.
Published: (2025)
by: Ozgul, Guneykan, et al.
Published: (2025)
Quantum Neural Networks for Solving Power System Transient Simulation Problem
by: Soltaninia, Mohammadreza, et al.
Published: (2024)
by: Soltaninia, Mohammadreza, et al.
Published: (2024)
Tensor Network Generator-Enhanced Optimization for Traveling Salesman Problem
by: Sakai, Ryo, et al.
Published: (2026)
by: Sakai, Ryo, et al.
Published: (2026)
Explainable Artificial Intelligence for Financial Integral Equations: A Fixed-Point Neural Operator Approach
by: Mohanty, Sanjay Kumar
Published: (2026)
by: Mohanty, Sanjay Kumar
Published: (2026)
Variational Quantum Eigensolver with Constraints (VQEC): Solving Constrained Optimization Problems via VQE
by: Le, Thinh Viet, et al.
Published: (2023)
by: Le, Thinh Viet, et al.
Published: (2023)
Adversarial Training of Two-Layer Polynomial and ReLU Activation Networks via Convex Optimization
by: Kuelbs, Daniel, et al.
Published: (2024)
by: Kuelbs, Daniel, et al.
Published: (2024)
Where the Quantum Lives in D-Wave Hybrid Portfolio Optimization
by: Lozano, Luis
Published: (2026)
by: Lozano, Luis
Published: (2026)
Hybrid Quantum-Classical Optimization for Multi-Objective Supply Chain Logistics
by: Heese, Raoul, et al.
Published: (2026)
by: Heese, Raoul, et al.
Published: (2026)
Curse of Dimensionality in Neural Network Optimization
by: Na, Sanghoon, et al.
Published: (2025)
by: Na, Sanghoon, et al.
Published: (2025)
Learning Neural Networks by Neuron Pursuit
by: Kumar, Akshay, et al.
Published: (2025)
by: Kumar, Akshay, et al.
Published: (2025)
A Bit of Freedom Goes a Long Way: Classical and Quantum Algorithms for Reinforcement Learning under a Generative Model
by: Ambainis, Andris, et al.
Published: (2025)
by: Ambainis, Andris, et al.
Published: (2025)
Quantum Algorithms for the Pathwise Lasso
by: Doriguello, Joao F., et al.
Published: (2023)
by: Doriguello, Joao F., et al.
Published: (2023)
Hybrid Quantum-Classical Algorithm For Robust Optimization via Stochastic-Gradient Online Learning
by: Lim, Debbie, et al.
Published: (2023)
by: Lim, Debbie, et al.
Published: (2023)
Exploring the Potential of Bilevel Optimization for Calibrating Neural Networks
by: Sanguin, Gabriele, et al.
Published: (2025)
by: Sanguin, Gabriele, et al.
Published: (2025)
SGD with Partial Hessian for Deep Neural Networks Optimization
by: Sun, Ying, et al.
Published: (2024)
by: Sun, Ying, et al.
Published: (2024)
Regularized Gauss-Newton for Optimizing Overparameterized Neural Networks
by: Adeoye, Adeyemi D., et al.
Published: (2024)
by: Adeoye, Adeyemi D., et al.
Published: (2024)
Data-Driven Performance Guarantees for Classical and Learned Optimizers
by: Sambharya, Rajiv, et al.
Published: (2024)
by: Sambharya, Rajiv, et al.
Published: (2024)
Quantum Natural Stochastic Pairwise Coordinate Descent
by: Sohail, Mohammad Aamir, et al.
Published: (2024)
by: Sohail, Mohammad Aamir, et al.
Published: (2024)
Efficient Reachability Analysis for Convolutional Neural Networks Using Hybrid Zonotopes
by: Zhang, Yuhao, et al.
Published: (2025)
by: Zhang, Yuhao, et al.
Published: (2025)
Operator-Level Quantum Acceleration of Non-Logconcave Sampling
by: Leng, Jiaqi, et al.
Published: (2025)
by: Leng, Jiaqi, et al.
Published: (2025)
Logarithmic-Regret Quantum Learning Algorithms for Zero-Sum Games
by: Gao, Minbo, et al.
Published: (2023)
by: Gao, Minbo, et al.
Published: (2023)
Optimality-Informed Neural Networks for Solving Parametric Optimization Problems
by: Hoffmann, Matthias K., et al.
Published: (2025)
by: Hoffmann, Matthias K., et al.
Published: (2025)
FSNet: Feasibility-Seeking Neural Network for Constrained Optimization with Guarantees
by: Nguyen, Hoang T., et al.
Published: (2025)
by: Nguyen, Hoang T., et al.
Published: (2025)
Early Directional Convergence in Deep Homogeneous Neural Networks for Small Initializations
by: Kumar, Akshay, et al.
Published: (2024)
by: Kumar, Akshay, et al.
Published: (2024)
Online Learning Quantum States with the Logarithmic Loss via VB-FTRL
by: Tseng, Wei-Fu, et al.
Published: (2023)
by: Tseng, Wei-Fu, et al.
Published: (2023)
Quantum Langevin Dynamics for Optimization
by: Chen, Zherui, et al.
Published: (2023)
by: Chen, Zherui, et al.
Published: (2023)
Quantum Portfolio Optimization: An Extensive Benchmark
by: Stopfer, Eric, et al.
Published: (2025)
by: Stopfer, Eric, et al.
Published: (2025)
Directional Convergence Near Small Initializations and Saddles in Two-Homogeneous Neural Networks
by: Kumar, Akshay, et al.
Published: (2024)
by: Kumar, Akshay, et al.
Published: (2024)
Towards Understanding Gradient Flow Dynamics of Homogeneous Neural Networks Beyond the Origin
by: Kumar, Akshay, et al.
Published: (2025)
by: Kumar, Akshay, et al.
Published: (2025)
Reinforcement Learning applied to Insurance Portfolio Pursuit
by: Young, Edward James, et al.
Published: (2024)
by: Young, Edward James, et al.
Published: (2024)
Autonomous Sparse Mean-CVaR Portfolio Optimization
by: Lin, Yizun, et al.
Published: (2024)
by: Lin, Yizun, et al.
Published: (2024)
Similar Items
-
Hybrid Ridgelet Deep Neural Networks for Data-Driven Arbitrage Strategies
by: Yadav, Bahadur, et al.
Published: (2025) -
Encoder Decoder Generative Adversarial Network Model for Stock Market Prediction
by: Yadav, Bahadur, et al.
Published: (2025) -
A Systematic Review of Recent Advancements in PINN Augmented Deep Learning and Mathematical Modeling for Efficient Portfolio Management
by: Yadav, Bahadur, et al.
Published: (2026) -
A hybrid wavelet-based physics-informed neural network for portfolio management
by: Yadav, Bahadur, et al.
Published: (2026) -
Classical and Quantum Speedups for Non-Convex Optimization via Energy Conserving Descent
by: Sun, Yihang, et al.
Published: (2026)