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Sequential Decision Making

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Showing 651–700 of 1210 papers

TitleStatusHype
A Survey on Large-Population Systems and Scalable Multi-Agent Reinforcement Learning—0
Sequential Information Design: Learning to Persuade in the Dark—0
MetaTrader: An Reinforcement Learning Approach Integrating Diverse Policies for Portfolio Optimization—0
Federated Online Clustering of BanditsCode0
JARVIS: A Neuro-Symbolic Commonsense Reasoning Framework for Conversational Embodied Agents—0
Entropy Regularization for Population Estimation—0
Sampling Through the Lens of Sequential Decision Making—0
Streaming Adaptive Submodular Maximization—0
Understanding the stochastic dynamics of sequential decision-making processes: A path-integral analysis of multi-armed bandits—0
Deep VULMAN: A Deep Reinforcement Learning-Enabled Cyber Vulnerability Management Framework—0
A Bayesian Approach to Learning Bandit Structure in Markov Decision Processes—0
Sample-efficient Safe Learning for Online Nonlinear Control with Control Barrier Functions—0
Branch Ranking for Efficient Mixed-Integer Programming via Offline Ranking-based Policy Learning—0
Partial-Monotone Adaptive Submodular Maximization—0
Adaptive Asynchronous Control Using Meta-learned Neural Ordinary Differential Equations—0
Learn Continuously, Act Discretely: Hybrid Action-Space Reinforcement Learning For Optimal Execution—0
High dimensional stochastic linear contextual bandit with missing covariates—0
Strategising template-guided needle placement for MR-targeted prostate biopsy—0
Delayed Feedback in Generalised Linear Bandits Revisited—0
Online Learning with Off-Policy Feedback—0
Guaranteed Discovery of Control-Endogenous Latent States with Multi-Step Inverse Models—0
Hindsight Learning for MDPs with Exogenous InputsCode0
Contextual Bandits with Large Action Spaces: Made PracticalCode0
Scaling up ML-based Black-box Planning with Partial STRIPS Models—0
Improving saliency models' predictions of the next fixation with humans' intrinsic cost of gaze shifts—0
Learning Optimal Solutions via an LSTM-Optimization Framework—0
Reinforcement Learning Approaches for the Orienteering Problem with Stochastic and Dynamic Release Dates—0
Reinforcement Learning Based Dynamic Model Combination for Time Series Forecasting—0
Utility Theory for Sequential Decision Making—0
Estimating Link Flows in Road Networks with Synthetic Trajectory Data Generation: Reinforcement Learning-based Approaches—0
A Survey on Model-based Reinforcement Learning—0
Federated Learning with Uncertainty via Distilled Predictive Distributions—0
Interactively Learning Preference Constraints in Linear BanditsCode0
Convergence and sample complexity of natural policy gradient primal-dual methods for constrained MDPs—0
Adaptive Rollout Length for Model-Based RL Using Model-Free Deep RL—0
Deciding What to Model: Value-Equivalent Sampling for Reinforcement Learning—0
Interpolating Between Softmax Policy Gradient and Neural Replicator Dynamics with Capped Implicit Exploration—0
Between Rate-Distortion Theory & Value Equivalence in Model-Based Reinforcement Learning—0
A Deep Reinforcement Learning Framework For Column GenerationCode0
Adaptive Robust Online Portfolio Selection—0
A Near-Optimal Best-of-Both-Worlds Algorithm for Online Learning with Feedback Graphs—0
Robust Anytime Learning of Markov Decision ProcessesCode0
Multi-Agent Learning of Numerical Methods for Hyperbolic PDEs with Factored Dec-MDP—0
Adaptive Sampling for Discovery—0
Causal Explanations for Sequential Decision Making Under Uncertainty—0
Temporal Latent Bottleneck: Synthesis of Fast and Slow Processing Mechanisms in Sequence LearningCode0
Efficient Deviation Types and Learning for Hindsight Rationality in Extensive-Form Games: CorrectionsCode0
Flow-based Recurrent Belief State Learning for POMDPs—0
Survey on Fair Reinforcement Learning: Theory and Practice—0
Marginal and Joint Cross-Entropies & Predictives for Online Bayesian Inference, Active Learning, and Active Sampling—0
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