nonparametric learning

Interpretable Image Classification via Non-parametric Part Prototype Learning CVPR 2025 NUDGE: Lightweight Non-Parametric Fine-Tuning of Embeddings for Retrieval ICLR 2025 A Kernel Perspective on Distillation-based Collaborative Learning NeurIPS 2024 Enhancing Transfer Learning with Flexible Nonparametric Posterior Sampling ICLR 2024 One-Layer Transformer Provably Learns One-Nearest Neighbor In Context NeurIPS 2024 Efficient Hyperparameter Tuning for Large Scale Kernel Ridge Regression AISTATS 2022 Few-Shot Non-Parametric Learning with Deep Latent Variable Model NeurIPS 2022 Non-Parametric Word Sense Disambiguation for Historical Languages AACL 2022 Single Trajectory Nonparametric Learning of Nonlinear Dynamics COLT 2022 Active Covering ICML 2021 Non-Parametric Few-Shot Learning for Word Sense Disambiguation NAACL 2021 A polynomial-time algorithm for learning nonparametric causal graphs NeurIPS 2020 Discriminative Non-Parametric Learning of Arithmetic Circuits PGM 2020 Generalized Policy Elimination: an efficient algorithm for Nonparametric Contextual Bandits UAI 2020 Kernel Methods Through the Roof: Handling Billions of Points Efficiently NeurIPS 2020 Learning Data-adaptive Non-parametric Kernels JMLR 2020 On Convergence of Nearest Neighbor Classifiers over Feature Transformations NeurIPS 2020 Optimal Non-parametric Learning in Repeated Contextual Auctions with Strategic Buyer ICML 2020 Beating SGD Saturation with Tail-Averaging and Minibatching NeurIPS 2019 LabelForest: Non-Parametric Semi-Supervised Learning for Activity Recognition AAAI 2019 Scalable Nonparametric Sampling from Multimodal Posteriors with the Posterior Bootstrap ICML 2019 Learning with SGD and Random Features NeurIPS 2018 Solving lp-norm regularization with tensor kernels AISTATS 2018 FALKON: An Optimal Large Scale Kernel Method NeurIPS 2017 Hierarchically Compositional Kernels for Scalable Nonparametric Learning JMLR 2017