Copertina

Bandit Algorithms for Deep Brain Stimulation

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Gupta, Arkaprava, Carter, Nicholas, Zellers, William, Ganguli, Prateek, Dietrich, Benedikt, Krishna, Vibhor, Duggirala, Parasara Sridhar, Chakraborty, Samarjit
Natura:	Preprint
Pubblicazione:	2026
Soggetti:	Machine Learning Systems and Control
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

In-Vivo Training for Deep Brain Stimulation
di: Carter, Nicholas, et al.
Pubblicazione: (2025)

LPrL: An Asynchronous Linear Time Hyper Logic
di: Duggirala, Parasara Sridhar, et al.
Pubblicazione: (2025)

Faster Q-Learning Algorithms for Restless Bandits
di: Kakarapalli, Parvish, et al.
Pubblicazione: (2024)

Whittle Index Learning Algorithms for Restless Bandits with Constant Stepsizes
di: Mittal, Vishesh, et al.
Pubblicazione: (2024)

Sample-Efficient Reinforcement Learning Controller for Deep Brain Stimulation in Parkinson's Disease
di: Ravivarapu, Harsh, et al.
Pubblicazione: (2025)

Fiber Activation by Bipolar Stimulation in Deep Brain Stimulation: A Patient Case Study
di: Frigge, Anna Franziska, et al.
Pubblicazione: (2024)

Risk-Aware Decision Making in Restless Bandits: Theory and Algorithms for Planning and Learning
di: Akbarzadeh, Nima, et al.
Pubblicazione: (2024)

Decentralized Upper Confidence Bound Algorithms for Homogeneous Multi-Agent Multi-Armed Bandits
di: Zhu, Jingxuan, et al.
Pubblicazione: (2021)

Tissue Activation Calculation in Dual-lead Deep Brain Stimulation
di: Frigge, Anna Franziska, et al.
Pubblicazione: (2025)

To Balance or to Not? Battery Aging-Aware Active Cell Balancing for Electric Vehicles
di: Fraccaroli, Enrico, et al.
Pubblicazione: (2024)

Why Most Optimism Bandit Algorithms Have the Same Regret Analysis: A Simple Unifying Theorem
di: Krishnamurthy, Vikram
Pubblicazione: (2025)

Learning to Sparsify Stochastic Linear Bandits
di: Wang, Zhengmiao, et al.
Pubblicazione: (2026)

Mixed Integer Linear Programming for Active Contact Selection in Deep Brain Stimulation
di: Frigge, Anna Franziska, et al.
Pubblicazione: (2025)

Explore-then-Commit for Nonstationary Linear Bandits with Latent Dynamics
di: Choi, Sunmook, et al.
Pubblicazione: (2025)

Byzantine-Resilient Decentralized Multi-Armed Bandits
di: Zhu, Jingxuan, et al.
Pubblicazione: (2023)

Multi-Agent Stage-wise Conservative Linear Bandits
di: Afsharrad, Amirhossein, et al.
Pubblicazione: (2025)

Differentially Private High Dimensional Bandits
di: Shukla, Apurv
Pubblicazione: (2024)

Leveraging Offline Data from Similar Systems for Online Linear Quadratic Control
di: Bajaj, Shivam, et al.
Pubblicazione: (2025)

Configuring Safe Spiking Neural Controllers for Cyber-Physical Systems through Formal Verification
di: Gupta, Arkaprava, et al.
Pubblicazione: (2024)

Cost-Ordered Feasibility for Multi-Armed Bandits with Cost Subsidy
di: Juneja, Ishank, et al.
Pubblicazione: (2026)

Cell Balancing Paradigms: Advanced Types, Algorithms, and Optimization Frameworks
di: Itagi, Anupama R, et al.
Pubblicazione: (2024)

Multi-agent Multi-armed Bandits with Minimum Reward Guarantee Fairness
di: Manupriya, Piyushi, et al.
Pubblicazione: (2025)

Finite-Time Guarantees for Multi-Agent Combinatorial Bandits with Nonstationary Rewards
di: Adams, Katherine B., et al.
Pubblicazione: (2025)

Restless Bandit Problem with Rewards Generated by a Linear Gaussian Dynamical System
di: Gornet, Jonathan, et al.
Pubblicazione: (2024)

Tangential Randomization in Linear Bandits (TRAiL): Guaranteed Inference and Regret Bounds
di: Güçlü, Arda, et al.
Pubblicazione: (2024)

R2DN: Scalable Parameterization of Contracting and Lipschitz Recurrent Deep Networks
di: Barbara, Nicholas H., et al.
Pubblicazione: (2025)

Multi-User mmWave Beam and Rate Adaptation via Combinatorial Satisficing Bandits
di: Özyıldırım, Emre, et al.
Pubblicazione: (2026)

Lagrangian Relaxation for Multi-Action Partially Observable Restless Bandits: Heuristic Policies and Indexability
di: Meshram, Rahul, et al.
Pubblicazione: (2025)

An LP-based Sampling Policy for Multi-Armed Bandits with Side-Observations and Stochastic Availability
di: Soni, Ashutosh, et al.
Pubblicazione: (2026)

Koopman operator for time-dependent reliability analysis
di: N., Navaneeth, et al.
Pubblicazione: (2022)

An Exploration-free Method for a Linear Stochastic Bandit Driven by a Linear Gaussian Dynamical System
di: Gornet, Jonathan, et al.
Pubblicazione: (2025)

The Nah Bandit: Modeling User Non-compliance in Recommendation Systems
di: Zhou, Tianyue, et al.
Pubblicazione: (2024)

Adversarial Network Optimization under Bandit Feedback: Maximizing Utility in Non-Stationary Multi-Hop Networks
di: Dai, Yan, et al.
Pubblicazione: (2024)

Mitigating Timing-Based Attacks in Real-Time Cyber-Physical Systems
di: Sain, Arkaprava, et al.
Pubblicazione: (2026)

HPC Application Parameter Autotuning on Edge Devices: A Bandit Learning Approach
di: Hossain, Abrar, et al.
Pubblicazione: (2025)

Deep Learning Model Predictive Control for Deep Brain Stimulation in Parkinson's Disease
di: Steffen, Sebastian, et al.
Pubblicazione: (2025)

Detecting and Mitigating System-Level Anomalies of Vision-Based Controllers
di: Gupta, Aryaman, et al.
Pubblicazione: (2023)

A Generalized Sinkhorn Algorithm for Mean-Field Schrödinger Bridge
di: Eldesoukey, Asmaa, et al.
Pubblicazione: (2026)

Towards a Systems Theory of Algorithms
di: Dörfler, Florian, et al.
Pubblicazione: (2024)

Strategic Electric Distribution Network Sensing via Spectral Bandits
di: Talkington, Samuel, et al.
Pubblicazione: (2024)