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conftrace_

mixture of gaussian

36 papers

MOG

Papers

PRISM: Probabilistic Reward Model with Inherent Structural Modeling ACL 2026 Test-Time Retrieval-Augmented Adaptation for Vision-Language Models ICCV 2025 Deep Variational Incomplete Multi-View Clustering: Exploring Shared Clustering Structures AAAI 2024 Mixtures of Gaussians are Privately Learnable with a Polynomial Number of Samples ALT 2024 Sample-Efficient Private Learning of Mixtures of Gaussians NeurIPS 2024 Theoretical Guarantees for Variational Inference with Fixed-Variance Mixture of Gaussians ICML 2024 Bypassing spike sorting: Density-based decoding using spike localization from dense multielectrode probes NeurIPS 2023 Graph Attention Retrospective JMLR 2023 Learning Mixtures of Gaussians with Censored Data ICML 2023 Lower Bounds for the Convergence of Tensor Power Iteration on Random Overcomplete Models COLT 2023 A Fourier Approach to Mixture Learning NeurIPS 2022 Neural-based Mixture Probabilistic Query Embedding for Answering FOL queries on Knowledge Graphs EMNLP 2022 Probabilistic Representations for Video Contrastive Learning CVPR 2022 NeoNav: Improving the Generalization of Visual Navigation via Generating Next Expected Observations AAAI 2020 Recovery of a Mixture of Gaussians by Sum-of-Norms Clustering JMLR 2020 On the Dynamics of Gradient Descent for Autoencoders AISTATS 2019 Semi-Supervised Transfer Learning for Image Rain Removal CVPR 2019 The Relative Complexity of Maximum Likelihood Estimation, MAP Estimation, and Sampling COLT 2019 Variational Smoothing in Recurrent Neural Network Language Models ICLR 2019 Maximum Likelihood Estimation for Mixtures of Spherical Gaussians is NP-hard JMLR 2018 Nearly tight sample complexity bounds for learning mixtures of Gaussians via sample compression schemes NeurIPS 2018 Open problem: Improper learning of mixtures of Gaussians COLT 2018 Learning Mixture of Gaussians with Streaming Data NeurIPS 2017 Robust and Proper Learning for Mixtures of Gaussians via Systems of Polynomial Inequalities COLT 2017 From Noise Modeling to Blind Image Denoising CVPR 2016