Bayesian Exponential Family PCA

No abstract is available for this paper.

• Publication year

  2008

• Venue

  Neural Information Processing Systems

• Publication date

  2008-12-08

• Fields of study

  Mathematics, Computer Science

• Identifiers

  No identifiers available.

• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar

• No claims are published for this paper.

• No concepts are published for this paper.

• Deterministic Latent Variable Models and Their Pitfalls

  2008cited by this paper
• Pattern Recognition and Machine Learning

  2006cited by this paper
• An Introduction to MCMC for Machine Learning

  2004cited by this paper
• Semi-parametric Exponential Family PCA

  2004cited by this paper
• Information Theory, Inference, and Learning Algorithms

  2004cited by this paper
• A Generalization of Principal Components Analysis to the Exponential Family

  2001cited by this paper
• Algorithms for Non-negative Matrix Factorization

  2000cited by this paper
• Probabilistic Visualisation of High-Dimensional Binary Data

  1998influential reference

• Identifiable factor analysis for mixed continuous and binary variables based on the Gaussian-Grassmann distribution

  2025influential citation
• Simple Imputation Rules for Prediction with Missing Data: Theoretical Guarantees vs. Empirical Performance

  2024cites this paper
• Amortized Variational Inference: When and Why?

  2023cites this paper
• Debiasing Sample Loadings and Scores in Exponential Family PCA for Sparse Count Data

  2023cites this paper
• Stochastic gradient updates yield deep equilibrium kernels

  2023cites this paper
• eRPCA: Robust Principal Component Analysis for Exponential Family Distributions

  2023cites this paper
• A Graphical Model for Fusing Diverse Microbiome Data

  2022cites this paper
• A Literature Review of (Sparse) Exponential Family PCA

  2022cites this paper
• Deep equilibrium models as estimators for continuous latent variables

  2022influential citation
• Dimension reduction for high-dimensional small counts with KL divergence

  2022cites this paper
• Metode Bayesian untuk Estimasi Parameter Distribusi Eksponensial pada Data Tersensor

  2022cites this paper
• Enhancing imputation techniques performance utilizing uncertainty aware predictors and adversarial learning

  2022cites this paper
• Multimodal Data Fusion in High-Dimensional Heterogeneous Datasets Via Generative Models

  2021cites this paper
• Prediction with Missing Data

  2021cites this paper
• Low-dimensional encoding of decisions in parietal cortex reflects long-term training history

  2021cites this paper
• The Deep Generative Decoder: MAP estimation of representations improves modelling of single-cell RNA data

  2021cites this paper
• Pólya‐gamma data augmentation and latent variable models for multivariate binomial data

  2021cites this paper
• Deviance Matrix Factorization

  2021cites this paper
• Overcoming the Cold Start Problem of Customer Relationship Management Using a Probabilistic Machine Learning Approach

  2021cites this paper
• Inference and Learning in a Latent Variable Model for Beta Distributed Interval Data

  2021cites this paper
• A Data Imputation Model based on an Ensemble Scheme

  2020cites this paper
• Distributed Bayesian Matrix Decomposition for Big Data Mining and Clustering

  2020cites this paper
• Rapid Model Comparison by Amortizing Across Models

  2020cites this paper
• Learning from Crowds via Joint Probabilistic Matrix Factorization and Clustering in Latent Space

  2020cites this paper
• Ensemble based Data Imputation at the Edge

  2020cites this paper
• A Continuous Data Imputation Mechanism based on Streams Correlation

  2020cites this paper
• Repulsive Mixture Models of Exponential Family PCA for Clustering

  2020cites this paper
• Low-rank model with covariates for count data with missing values

  2019cites this paper
• ImputeNet: Missing Data Imputation with Graph Neural Networks

  2019cites this paper
• Generalized Principal Component Analysis: Projection of Saturated Model Parameters

  2019cites this paper
• Uncertainty-Aware Variational-Recurrent Imputation Network for Clinical Time Series

  2019cites this paper
• Machine learning for problems with missing and uncertain data with applications to personalized medicine

  2019cites this paper
• A Spatio-Temporal Data Imputation Model for Supporting Analytics at the Edge

  2019cites this paper
• Simple Poisson PCA: an algorithm for (sparse) feature extraction with simultaneous dimension determination

  2019cites this paper
• Discretize and Conquer: Scalable Agglomerative Clustering in Hamming Space

  2019cites this paper
• Content Popularity Estimation in Edge-Caching Networks from Bayesian Inference Perspective

  2019cites this paper
• New algorithms in machine learning with applications in personalized medicine

  2018cites this paper
• The Blessings of Multiple Causes

  2018cites this paper
• Sum Conditioned Poisson Factorization

  2018cites this paper
• Bayesian Inference over Stiefel Manifold 3 Bayesian Inference of Constrained Parameters Using Transformations

  2018cites this paper
• Laplace Exponential Family PCA

  2018cites this paper
• Principals about principal components in statistical genetics

  2018cites this paper
• Use and Development of Matrix Factorisation Techniques in the Field of Brain Imaging

  2018cites this paper
• Heteroskedastic PCA: Algorithm, optimality, and applications

  2018cites this paper
• Modelling strategies to improve genetic evaluation for the New Zealand sheep industry

  2018influential citation
• Low-rank Interaction Contingency Tables

  2017cites this paper
• Variational inference for probabilistic Poisson PCA

  2017cites this paper
• Unifying the Stochastic Spectral Descent for Restricted Boltzmann Machines with Bernoulli or Gaussian Inputs

  2017cites this paper
• General Bayesian Inference over the Stiefel Manifold via the Givens Transform

  2017cites this paper
• General Latent Feature Models for Heterogeneous Datasets

  2017cites this paper
• Applications of Approximate Learning and Inference for Probabilistic Models

  2017influential citation
• From Predictive Methods to Missing Data Imputation: An Optimization Approach

  2017cites this paper
• Explaining and Generalizing Skip-Gram through Exponential Family Principal Component Analysis

  2017cites this paper
• Black Box Variational Inference: Scalable, Generic Bayesian Computation and its Applications

  2017cites this paper
• Probabilistic inference for dynamic networks and complex event processes

  2017cites this paper
• Conjugate-Computation Variational Inference: Converting Variational Inference in Non-Conjugate Models to Inferences in Conjugate Models

  2017influential citation
• Low-rank model with covariates for count data analysis

  2017cites this paper
• Bayesian Inference on Matrix Manifolds for Linear Dimensionality Reduction

  2016influential citation
• A Survey of Multi-View Representation Learning

  2016cites this paper
• Advanced Bayesian Models for High-Dimensional Biomedical Data

  2016cites this paper
• Predictive coarse-graining

  2016cites this paper
• Voting, Speechmaking, and the Dimensions of Conict in the US Senate

  2015cites this paper
• Generalized Principal Component Analysis: Dimensionality Reduction through the Projection of Natural Parameters

  2015cites this paper
• On the Structure of Neuronal Population Activity under Fluctuations in Attentional State

  2015cites this paper
• MCODE: Multivariate Conditional Outlier Detection

  2015cites this paper
• Voting, Speechmaking, and the Dimensions of Conflict in the US Senate ˚

  2014cites this paper
• Linear dimensionality reduction: survey, insights, and generalizations

  2014cites this paper
• Generalized Dynamic Factor Models for Mixed-Measurement Time Series

  2014cites this paper
• Variational Gaussian Inference for Bilinear Models of Count Data

  2014cites this paper
• Bayesian Sparse Unsupervised Learning for Probit Models of Binary Data

  2014influential citation
• Build, Compute, Critique, Repeat: Data Analysis with Latent Variable Models

  2014cites this paper
• Polya-gamma augmentations for factor models

  2014influential citation
• Exponential Family Matrix Completion under Structural Constraints

  2014cites this paper
• Bayesian latent variable models for learning dependencies between multiple data sources

  2014cites this paper
• Interpretability of Mixed Membership Models

  2014influential citation
• Deep Exponential Families

  2014cites this paper
• Unifying linear dimensionality reduction

  2014cites this paper
• Adaptive Hamiltonian and Riemann manifold Monte Carlo samplers

  2013cites this paper
• Probabilistic archetypal analysis

  2013influential citation
• Prediction and recommendation in online media

  2013cites this paper
• Exponential Family Factors for Bayesian Factor Analysis

  2013cites this paper
• Samplers 2 . Hamiltonian-based Monte Carlo Sampling

  2013cites this paper
• Exploiting compositionality to explore a large space of model structures

  2012cites this paper
• Exponential family tensor factorization: an online extension and applications

  2012cites this paper
• Variational learning for latent Gaussian model of discrete data

  2012influential citation
• Computational Methods of Information Geometry with Real-Time Applications in Audio Signal Processing. (Méthodes Computationnelles en Géométrie de l'Information et Applications Temps Réel au Traitement du Signal Audio)

  2012cites this paper
• A Stick-Breaking Likelihood for Categorical Data Analysis with Latent Gaussian Models

  2012cites this paper
• Bayesian Modeling and Computation for Mixed Data

  2012cites this paper
• Bayesian and L1 Approaches to Sparse Unsupervised Learning

  2011influential citation
• Online maximum-likelihood estimation for latent factor models

  2011cites this paper
• Generalised Bayesian matrix factorisation models

  2011cites this paper
• MAXIMUM-LIKELIHOOD ESTIMATION FOR LATENT FACTORMODELS

  2011cites this paper
• Piecewise Bounds for Estimating Bernoulli-Logistic Latent Gaussian Models

  2011cites this paper
• Evaluating Bayesian and L1 Approaches for Sparse Unsupervised Learning

  2011cites this paper
• Exponential Family Tensor Factorization for Missing-Values Prediction and Anomaly Detection

  2010cites this paper
• A Bayesian Matrix Factorization Model for Relational Data

  2010cites this paper
• Simple Exponential Family PCA

  2010influential citation
• Variational bounds for mixed-data factor analysis

  2010influential citation
• Bayesian exponential family projections for coupled data sources

  2010influential citation
• Transformations in variational Bayesian factor analysis to speed up learning

  2010cites this paper