importance weight

ChulaNLP at SemEval-2026 Task 4: Neural Aspect Composition for Narrative Story Embeddings SemEval 2026 Data Retrieval with Importance Weights for Few-Shot Imitation Learning CoRL 2025 Importance Corrected Neural JKO Sampling ICML 2025 LEAPS: A discrete neural sampler via locally equivariant networks ICML 2025 One-step Label Shift Adaptation via Robust Weight Estimation IJCAI 2025 TIS-DPO: Token-level Importance Sampling for Direct Preference Optimization With Estimated Weights ICLR 2025 PAC Prediction Sets Under Label Shift ICLR 2024 Pareto Smoothed Importance Sampling JMLR 2024 Doubly Robust Augmented Transfer for Meta-Reinforcement Learning NeurIPS 2023 Infinite Action Contextual Bandits with Reusable Data Exhaust ICML 2023 Transfer Knowledge From Head to Tail: Uncertainty Calibration Under Long-Tailed Distribution CVPR 2023 Experience Replay with Likelihood-free Importance Weights L4DC 2022 Multicalibrated Partitions for Importance Weights ALT 2022 Are Adversarial Examples Created Equal? A Learnable Weighted Minimax Risk for Robustness under Non-uniform Attacks AAAI 2021 Learning Task Sampling Policy for Multitask Learning EMNLP 2021 Subgaussian and Differentiable Importance Sampling for Off-Policy Evaluation and Learning NeurIPS 2021 Bridging the Gap Between f-GANs and Wasserstein GANs ICML 2020 Doubly robust off-policy evaluation with shrinkage ICML 2020 Minimax Value Interval for Off-Policy Evaluation and Policy Optimization NeurIPS 2020 Training Variational Autoencoders with Buffered Stochastic Variational Inference AISTATS 2019 Boundary Seeking GANs ICLR 2018 Variational Inference with Tail-adaptive f-Divergence NeurIPS 2018 Black-box Importance Sampling AISTATS 2017