Quantum Natural Stochastic Pairwise Coordinate Descent
Fuente:
arXiv
Saved in:
| Main Authors: | Sohail, Mohammad Aamir, Heidari, Mohsen, Pradhan, S. Sandeep |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Quantum Optimization via Gradient-Based Hamiltonian Descent
by: Leng, Jiaqi, et al.
Published: (2025)
by: Leng, Jiaqi, et al.
Published: (2025)
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)
Fast Minimization of Expected Logarithmic Loss via Stochastic Dual Averaging
by: Tsai, Chung-En, et al.
Published: (2023)
by: Tsai, Chung-En, et al.
Published: (2023)
Stochastic Security as a Performance Metric for Quantum-enhanced Generative AI
by: Crum, Noah A., et al.
Published: (2023)
by: Crum, Noah A., et al.
Published: (2023)
Quantum Algorithms for the Pathwise Lasso
by: Doriguello, Joao F., et al.
Published: (2023)
by: Doriguello, Joao F., et al.
Published: (2023)
Stochastic Adaptive Gradient Descent Without Descent
by: Aujol, Jean-François, et al.
Published: (2025)
by: Aujol, Jean-François, et al.
Published: (2025)
Accelerating Feedback-based Algorithms for Quantum Optimization Using Gradient Descent
by: Mozakka, Masih, et al.
Published: (2026)
by: Mozakka, Masih, et al.
Published: (2026)
Operator-Level Quantum Acceleration of Non-Logconcave Sampling
by: Leng, Jiaqi, et al.
Published: (2025)
by: Leng, Jiaqi, et al.
Published: (2025)
Variational Optimization for Quantum Problems using Deep Generative Networks
by: Zhang, Lingxia, et al.
Published: (2024)
by: Zhang, Lingxia, et al.
Published: (2024)
Logarithmic-Regret Quantum Learning Algorithms for Zero-Sum Games
by: Gao, Minbo, et al.
Published: (2023)
by: Gao, Minbo, et al.
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)
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)
Parity Cross-Resonance: A Multiqubit Gate
by: Xu, Xuexin, et al.
Published: (2025)
by: Xu, Xuexin, et al.
Published: (2025)
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)
More Optimal Fractional-Order Stochastic Gradient Descent for Non-Convex Optimization Problems
by: Partohaghighi, Mohammad, et al.
Published: (2025)
by: Partohaghighi, Mohammad, et al.
Published: (2025)
Effective Dimension Aware Fractional-Order Stochastic Gradient Descent for Convex Optimization Problems
by: Partohaghighi, Mohammad, et al.
Published: (2025)
by: Partohaghighi, Mohammad, et al.
Published: (2025)
Quantum open system identification via global optimization: Optimally accurate Markovian models of open systems from time-series data
by: Popovych, Zakhar, et al.
Published: (2022)
by: Popovych, Zakhar, et al.
Published: (2022)
Variational Quantum Brushes
by: Lu, Jui-Ting, et al.
Published: (2025)
by: Lu, Jui-Ting, et al.
Published: (2025)
Stochastic Gradient Descent with Adaptive Data
by: Che, Ethan, et al.
Published: (2024)
by: Che, Ethan, et al.
Published: (2024)
Stochastic Gradient Descent with Strategic Querying
by: Jiang, Nanfei, et al.
Published: (2025)
by: Jiang, Nanfei, et al.
Published: (2025)
Learning AC Power Flow Solutions using a Data-Dependent Variational Quantum Circuit
by: Le, Thinh Viet, et al.
Published: (2025)
by: Le, Thinh Viet, et al.
Published: (2025)
Momentum Does Not Reduce Stochastic Noise in Stochastic Gradient Descent
by: Sato, Naoki, et al.
Published: (2024)
by: Sato, Naoki, et al.
Published: (2024)
Solving Conic Programs over Sparse Graphs using a Variational Quantum Approach: The Case of the Optimal Power Flow
by: Le, Thinh Viet, et al.
Published: (2025)
by: Le, Thinh Viet, et al.
Published: (2025)
Random Coordinate Descent on the Wasserstein Space of Probability Measures
by: Xu, Yewei, et al.
Published: (2026)
by: Xu, Yewei, et al.
Published: (2026)
Derivatives of Stochastic Gradient Descent in parametric optimization
by: Iutzeler, Franck, et al.
Published: (2024)
by: Iutzeler, Franck, et al.
Published: (2024)
Stochastic Zeroth order Descent with Structured Directions
by: Rando, Marco, et al.
Published: (2022)
by: Rando, Marco, et al.
Published: (2022)
Natural gradient and parameter estimation for quantum Boltzmann machines
by: Patel, Dhrumil, et al.
Published: (2024)
by: Patel, Dhrumil, et al.
Published: (2024)
Rapid Overfitting of Multi-Pass Stochastic Gradient Descent in Stochastic Convex Optimization
by: Vansover-Hager, Shira, et al.
Published: (2025)
by: Vansover-Hager, Shira, et al.
Published: (2025)
Quantum Hamiltonian Descent for Non-smooth Optimization
by: Leng, Jiaqi, et al.
Published: (2025)
by: Leng, Jiaqi, et al.
Published: (2025)
The Sample Complexity of Gradient Descent in Stochastic Convex Optimization
by: Livni, Roi
Published: (2024)
by: Livni, Roi
Published: (2024)
Parameter Symmetry and Noise Equilibrium of Stochastic Gradient Descent
by: Ziyin, Liu, et al.
Published: (2024)
by: Ziyin, Liu, et al.
Published: (2024)
Convergence Analysis of Stochastic Gradient Descent with MCMC Estimators
by: Li, Tianyou, et al.
Published: (2023)
by: Li, Tianyou, et al.
Published: (2023)
Adaptive Step Sizes for Preconditioned Stochastic Gradient Descent
by: Köhne, Frederik, et al.
Published: (2023)
by: Köhne, Frederik, et al.
Published: (2023)
Implicit Bias and Convergence of Matrix Stochastic Mirror Descent
by: Akhtiamov, Danil, et al.
Published: (2026)
by: Akhtiamov, Danil, et al.
Published: (2026)
Functional Central Limit Theorem for Stochastic Gradient Descent
by: Flamand, Kessang, et al.
Published: (2026)
by: Flamand, Kessang, et al.
Published: (2026)
Faster Convergence of Stochastic Accelerated Gradient Descent under Interpolation
by: Mishkin, Aaron, et al.
Published: (2024)
by: Mishkin, Aaron, et al.
Published: (2024)
Exponential Convergence of (Stochastic) Gradient Descent for Separable Logistic Regression
by: Kale, Sacchit, et al.
Published: (2026)
by: Kale, Sacchit, et al.
Published: (2026)
On the Convergence of Stochastic Gradient Descent with Perturbed Forward-Backward Passes
by: Kong, Boao, et al.
Published: (2026)
by: Kong, Boao, et al.
Published: (2026)
Gauss-Newton Natural Gradient Descent for Shape Learning
by: King, James, et al.
Published: (2026)
by: King, James, et al.
Published: (2026)
Learning quantum Hamiltonians at any temperature in polynomial time with Chebyshev and bit complexity
by: Wodecki, Ales, et al.
Published: (2024)
by: Wodecki, Ales, et al.
Published: (2024)
Similar Items
-
Quantum Optimization via Gradient-Based Hamiltonian Descent
by: Leng, Jiaqi, et al.
Published: (2025) -
Classical and Quantum Speedups for Non-Convex Optimization via Energy Conserving Descent
by: Sun, Yihang, et al.
Published: (2026) -
Fast Minimization of Expected Logarithmic Loss via Stochastic Dual Averaging
by: Tsai, Chung-En, et al.
Published: (2023) -
Stochastic Security as a Performance Metric for Quantum-enhanced Generative AI
by: Crum, Noah A., et al.
Published: (2023) -
Quantum Algorithms for the Pathwise Lasso
by: Doriguello, Joao F., et al.
Published: (2023)