theoretical guarantee

Unsupervised Object Detection with Theoretical Guarantees NeurIPS 2024 AC-Band: A Combinatorial Bandit-Based Approach to Algorithm Configuration AAAI 2023 Provable Detection of Propagating Sampling Bias in Prediction Models AAAI 2023 Rethinking Backdoor Attacks ICML 2023 Revisiting Pseudo-Label for Single-Positive Multi-Label Learning ICML 2023 Sampling is as easy as learning the score: theory for diffusion models with minimal data assumptions ICLR 2023 Structured Prediction with Stronger Consistency Guarantees NeurIPS 2023 Convolutional and Residual Networks Provably Contain Lottery Tickets ICML 2022 Domain Adaptation via Maximizing Surrogate Mutual Information IJCAI 2022 Iterative Feature Matching: Toward Provable Domain Generalization with Logarithmic Environments NeurIPS 2022 Nearly Optimal Policy Optimization with Stable at Any Time Guarantee ICML 2022 Provable Guarantees for Understanding Out-of-Distribution Detection AAAI 2022 When to Update Your Model: Constrained Model-based Reinforcement Learning NeurIPS 2022 Mixture Proportion Estimation and PU Learning:A Modern Approach NeurIPS 2021 Multi-Objective Submodular Maximization by Regret Ratio Minimization with Theoretical Guarantee AAAI 2021 On the Intrinsic Differential Privacy of Bagging IJCAI 2021 Uncertainty Principles of Encoding GANs ICML 2021 Error-Bounded Correction of Noisy Labels ICML 2020 Algorithmic Framework for Model-based Deep Reinforcement Learning with Theoretical Guarantees ICLR 2019 Are adversarial examples inevitable? ICLR 2019 Provable Gradient Variance Guarantees for Black-Box Variational Inference NeurIPS 2019 Safe Policy Improvement with Baseline Bootstrapping ICML 2019 Statistical Analysis of Nearest Neighbor Methods for Anomaly Detection NeurIPS 2019 Achieving Non-Discrimination in Prediction IJCAI 2018 Algorithms and Theory for Multiple-Source Adaptation NeurIPS 2018