importance sampling

Kernel Metric Learning for In-Sample Off-Policy Evaluation of Deterministic RL Policies ICLR 2024 LISA: Layerwise Importance Sampling for Memory-Efficient Large Language Model Fine-Tuning NeurIPS 2024 Local and Adaptive Mirror Descents in Extensive-Form Games NeurIPS 2024 Logarithmic Smoothing for Pessimistic Off-Policy Evaluation, Selection and Learning NeurIPS 2024 On the connection between Noise-Contrastive Estimation and Contrastive Divergence AISTATS 2024 Pareto Smoothed Importance Sampling JMLR 2024 Probabilistic Modeling for Sequences of Sets in Continuous-Time AISTATS 2024 Reparameterized Importance Sampling for Robust Variational Bayesian Neural Networks ICML 2024 Revealing Distribution Discrepancy by Sampling Transfer in Unlabeled Data NeurIPS 2024 SAPG: Split and Aggregate Policy Gradients ICML 2024 Skill or Luck? Return Decomposition via Advantage Functions ICLR 2024 Submodular Minimax Optimization: Finding Effective Sets AISTATS 2024 Target-Aware Language Modeling via Granular Data Sampling EMNLP 2024 Test Where Decisions Matter: Importance-driven Testing for Deep Reinforcement Learning NeurIPS 2024 Unified PAC-Bayesian Study of Pessimism for Offline Policy Learning with Regularized Importance Sampling UAI 2024 Using Autodiff to Estimate Posterior Moments, Marginals and Samples UAI 2024 Value-Based Abstraction Functions for Abstraction Sampling UAI 2024 VISA: Variational Inference with Sequential Sample-Average Approximations NeurIPS 2024 Adaptation Augmented Model-based Policy Optimization JMLR 2023 A Faster Practical Approximation Scheme for the Permanent AAAI 2023 Beyond Uniform Sampling: Offline Reinforcement Learning with Imbalanced Datasets NeurIPS 2023 Building Persona Consistent Dialogue Agents with Offline Reinforcement Learning EMNLP 2023 Computing Approximate ℓ_p Sensitivities NeurIPS 2023 Contextual Image Masking Modeling via Synergized Contrasting without View Augmentation for Faster and Better Visual Pretraining ICLR 2023 Cooperation in the Latent Space: The Benefits of Adding Mixture Components in Variational Autoencoders ICML 2023