conftrace_

importance sampling

318 papers

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Also known as

IS

Co-occurring keywords

off-policy evaluation (144) variational inference (2069) variance reduction (523) reinforcement learning (4352) markov chain monte carlo (725) bayesian inference (1907) stochastic optimization (1060) off-policy learning (228) monte carlo method (126) policy optimization (657)

Papers

Scaling Marginalized Importance Sampling to High-Dimensional State-Spaces via State Abstraction AAAI 2023
PA&DA: Jointly Sampling Path and Data for Consistent NAS CVPR 2023
RL-based Stateful Neural Adaptive Sampling and Denoising for Real-Time Path Tracing NIPS 2023
Multiple-policy High-confidence Policy Evaluation AISTATS 2023
Imitation Learning from Imperfection: Theoretical Justifications and Algorithms NIPS 2023
Refined Regret for Adversarial MDPs with Linear Function Approximation ICML 2023
KAKURENBO: Adaptively Hiding Samples in Deep Neural Network Training NIPS 2023
Adaptation Augmented Model-based Policy Optimization JMLR 2023
Fast Offline Policy Optimization for Large Scale Recommendation AAAI 2023
Optimization and Bayes: A Trade-off for Overparameterized Neural Networks NIPS 2023
The Sample Complexity of Approximate Rejection Sampling With Applications to Smoothed Online Learning COLT 2023
Building Persona Consistent Dialogue Agents with Offline Reinforcement Learning EMNLP 2023
Probabilistic Querying of Continuous-Time Event Sequences AISTATS 2023
Beyond Uniform Sampling: Offline Reinforcement Learning with Imbalanced Datasets NIPS 2023
Counterfactual-Augmented Importance Sampling for Semi-Offline Policy Evaluation NIPS 2023
Truncating Trajectories in Monte Carlo Reinforcement Learning ICML 2023
On the Reuse Bias in Off-Policy Reinforcement Learning IJCAI 2023
SE(3) Equivariant Augmented Coupling Flows NIPS 2023
Supported Value Regularization for Offline Reinforcement Learning NIPS 2023
Trajectory-Aware Eligibility Traces for Off-Policy Reinforcement Learning ICML 2023
HeteRSGD: Tackling Heterogeneous Sampling Costs via Optimal Reweighted Stochastic Gradient Descent AISTATS 2023
DMIS: Dynamic Mesh-Based Importance Sampling for Training Physics-Informed Neural Networks AAAI 2023
Computing Approximate $\ell_p$ Sensitivities NIPS 2023
SMCP3: Sequential Monte Carlo with Probabilistic Program Proposals AISTATS 2023
Doubly Robust Stein-Kernelized Monte Carlo Estimator: Simultaneous Bias-Variance Reduction and Supercanonical Convergence JMLR 2023