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method of moment

29 papers

Papers

Generalized Resubstitution for Regression Error Estimation JMLR 2026 ReliableEval: A Recipe for Stochastic LLM Evaluation via Method of Moments EMNLP 2025 Estimating Shape Distances on Neural Representations with Limited Samples ICLR 2024 Distributed Statistical Inference under Heterogeneity JMLR 2023 Estimation Beyond Data Reweighting: Kernel Method of Moments ICML 2023 Identification and Estimation of the Probabilities of Potential Outcome Types Using Covariate Information in Studies with Non-compliance AAAI 2023 Tractable Optimality in Episodic Latent MABs NeurIPS 2022 Comparing the Value of Labeled and Unlabeled Data in Method-of-Moments Latent Variable Estimation AISTATS 2021 Method of Moments for Topic Models with Mixed Discrete and Continuous Features IJCAI 2021 Anchored Causal Inference in the Presence of Measurement Error UAI 2020 Fast and Consistent Learning of Hidden Markov Models by Incorporating Non-Consecutive Correlations ICML 2020 Guaranteed Scalable Learning of Latent Tree Models UAI 2019 Learning Mixtures of Plackett-Luce Models from Structured Partial Orders NeurIPS 2019 Learning Two-layer Neural Networks with Symmetric Inputs ICLR 2019 Learning Implicit Generative Models with the Method of Learned Moments ICML 2018 Learning Signed Determinantal Point Processes through the Principal Minor Assignment Problem NeurIPS 2018 Learning Determinantal Point Processes with Moments and Cycles ICML 2017 Partitioned Tensor Factorizations for Learning Mixed Membership Models ICML 2017 Consistently Estimating Markov Chains with Noisy Aggregate Data AISTATS 2016 Fast Collaborative Filtering from Implicit Feedback with Provable Guarantees ACML 2016 PAC learning of Probabilistic Automaton based on the Method of Moments ICML 2016 Spectral M-estimation with Applications to Hidden Markov Models AISTATS 2016 Unsupervised Risk Estimation Using Only Conditional Independence Structure NeurIPS 2016 Estimating Mixture Models via Mixtures of Polynomials NeurIPS 2015 Estimating Latent-Variable Graphical Models using Moments and Likelihoods ICML 2014