distribution learning

Learning with Stochastic Orders ICLR 2023 Leave No Stone Unturned: Mine Extra Knowledge for Imbalanced Facial Expression Recognition NeurIPS 2023 Neural networks trained with SGD learn distributions of increasing complexity ICML 2023 OPT-GAN: A Broad-Spectrum Global Optimizer for Black-Box Problems by Learning Distribution AAAI 2023 Private Distribution Learning with Public Data: The View from Sample Compression NeurIPS 2023 Sample Complexity of Forecast Aggregation NeurIPS 2023 Tight Bounds on the Hardness of Learning Simple Nonparametric Mixtures COLT 2023 An Error Analysis of Generative Adversarial Networks for Learning Distributions JMLR 2022 A Novel Differentiable Mixed-Precision Quantization Search Framework for Alleviating the Matthew Effect and Improving Robustness ACML 2022 Distribution Aware VoteNet for 3D Object Detection AAAI 2022 Efficient interventional distribution learning in the PAC framework AISTATS 2022 Learning to Communicate Effectively Between Battery-free Devices NSDI 2022 Learning with Distributional Inverters ALT 2022 Minimax Optimality (Probably) Doesn't Imply Distribution Learning for GANs ICLR 2022 Non-Gaussian Component Analysis via Lattice Basis Reduction COLT 2022 On Deep Generative Models for Approximation and Estimation of Distributions on Manifolds NeurIPS 2022 Optimal SQ Lower Bounds for Robustly Learning Discrete Product Distributions and Ising Models COLT 2022 PAC Mode Estimation using PPR Martingale Confidence Sequences AISTATS 2022 Prompt Distribution Learning CVPR 2022 TURF: Two-Factor, Universal, Robust, Fast Distribution Learning Algorithm ICML 2022 Deep Latent Graph Matching ICML 2021 Differentially Private Sampling from Distributions NeurIPS 2021 GAN Ensemble for Anomaly Detection AAAI 2021 Generalized Focal Loss V2: Learning Reliable Localization Quality Estimation for Dense Object Detection CVPR 2021 How Well Generative Adversarial Networks Learn Distributions JMLR 2021