Cover Image

Vector preference-based contextual bandits under distributional shifts

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Shukla, Apurv, Kumar, P. R.
Format:	Preprint
Published:	2025
Subjects:	Machine Learning Systems and Control Probability
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Differentially Private High Dimensional Bandits
by: Shukla, Apurv
Published: (2024)

Rates of Convergence in the Central Limit Theorem for Markov Chains, with an Application to TD Learning
by: Srikant, R.
Published: (2024)

Set Invariance with Probability One for Controlled Diffusion: Score-based Approach
by: Wang, Wenqing, et al.
Published: (2025)

Differentiable Filtering for Learning Hidden Markov Models
by: Chen, Reginald Zhiyan, et al.
Published: (2025)

Dual Filter: A Transformer-like Inference Architecture for Hidden Markov Models
by: Chang, Heng-Sheng, et al.
Published: (2025)

What can we learn from signals and systems in a transformer? Insights for probabilistic modeling and inference architecture
by: Chang, Heng-Sheng, et al.
Published: (2025)

Change Detection of Markov Kernels with Unknown Pre and Post Change Kernel
by: Chen, Hao, et al.
Published: (2022)

Causal Optimal Coupling for Gaussian Input-Output Distributional Data
by: Xu, Daran, et al.
Published: (2026)

Schrödinger Bridge Over A Compact Connected Lie Group
by: Mahmood, Hamza, et al.
Published: (2026)

Evaluating the design space of diffusion-based generative models
by: Wang, Yuqing, et al.
Published: (2024)

Multi-hop Upstream Anticipatory Traffic Signal Control with Deep Reinforcement Learning
by: Li, Xiaocan, et al.
Published: (2024)

Dynamical Measure Transport and Neural PDE Solvers for Sampling
by: Sun, Jingtong, et al.
Published: (2024)

Markov Kernels, Distances and Optimal Control: A Parable of Linear Quadratic Non-Gaussian Distribution Steering
by: Teter, Alexis M. H., et al.
Published: (2025)

Wasserstein Convergence of Score-based Generative Models under Semiconvexity and Discontinuous Gradients
by: Bruno, Stefano, et al.
Published: (2025)

FraPPE: Fast and Efficient Preference-based Pure Exploration
by: Das, Udvas, et al.
Published: (2025)

Performance-bounded Online Ensemble Learning Method Based on Multi-armed bandits and Its Applications in Real-time Safety Assessment
by: Hu, Songqiao, et al.
Published: (2025)

Sample Complexity of Chance Constrained Optimization in Dynamic Environment
by: Shukla, Apurv, et al.
Published: (2024)

Efficient Scenario Generation for Chance-constrained Economic Dispatch Considering Ambient Wind Conditions
by: Zhang, Qian, et al.
Published: (2023)

Decentralized Online Learning for Random Inverse Problems Over Graphs
by: Zhang, Xiwei, et al.
Published: (2023)

Algorithmic Stability of Stochastic Gradient Descent with Momentum under Heavy-Tailed Noise
by: Dang, Thanh, et al.
Published: (2025)

Scenario approach for minmax optimization with emphasis on the nonconvex case: positive results and caveats
by: K, Mishal Assif P, et al.
Published: (2019)

Typical models of the distribution system restoration process
by: Ahmad, Arslan, et al.
Published: (2026)

Measuring outage resilience in a distribution system with the number of outages in large events
by: Ahmad, Arslan, et al.
Published: (2026)

On diffusion-based generative models and their error bounds: The log-concave case with full convergence estimates
by: Bruno, Stefano, et al.
Published: (2023)

Integrating Fuzzy Set Theory with Pandora Temporal Fault Trees for Dynamic Failure Analysis of Complex Systems
by: Khungla, Hitesh, et al.
Published: (2024)

Time series forecasting with high stakes: A field study of the air cargo industry
by: Garg, Abhinav, et al.
Published: (2024)

Environmental management and restoration under unified risk and uncertainty using robustified dynamic Orlicz risk
by: Yoshioka, Hidekazu, et al.
Published: (2023)

Q-Learning under Finite Model Uncertainty
by: Sester, Julian, et al.
Published: (2024)

Fair Incentives for Repeated Engagement
by: Freund, Daniel, et al.
Published: (2021)

Learning based Modelling of Throttleable Engine Dynamics for Lunar Landing Mission
by: Kumar, Suraj, et al.
Published: (2025)

SIS epidemics on open networks: A replacement-based approximation
by: Vizuete, Renato, et al.
Published: (2024)

Robust Neural IDA-PBC: passivity-based stabilization under approximations
by: Sanchez-Escalonilla, Santiago, et al.
Published: (2024)

Robust $Q$-learning Algorithm for Markov Decision Processes under Wasserstein Uncertainty
by: Neufeld, Ariel, et al.
Published: (2022)

Probabilistic Reduced-Dimensional Vector Autoregressive Modeling with Oblique Projections
by: Mo, Yanfang, et al.
Published: (2024)

HOPS: High-order Polynomials with Self-supervised Dimension Reduction for Load Forecasting
by: Song, Pengyang, et al.
Published: (2025)

A Theory of the Risk for Optimization with Relaxation and its Application to Support Vector Machines
by: Campi, Marco C., et al.
Published: (2020)

Preference-based Pure Exploration
by: Shukla, Apurv, et al.
Published: (2024)

Koopman Subspace Pruning in Reproducing Kernel Hilbert Spaces via Principal Vectors
by: Shah, Dhruv, et al.
Published: (2026)

Model Predictive Control is almost Optimal for Heterogeneous Restless Multi-armed Bandits
by: Narasimha, Dheeraj, et al.
Published: (2025)

Non-convex entropic mean-field optimization via Best Response flow
by: Lascu, Razvan-Andrei, et al.
Published: (2025)