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TitleStatusHype
Noise Benefits in Expectation-Maximization Algorithms—0
Robust Kernel Density Estimation by Scaling and Projection in Hilbert Space—0
Statistical Models for Degree Distributions of Networks—0
Speaker Identification From Youtube Obtained Data—0
Bayesian group latent factor analysis with structured sparsityCode0
Parameter estimation in spherical symmetry groups—0
Large-Margin Determinantal Point Processes—0
Sublinear-Time Approximate MCMC Transitions for Probabilistic Programs—0
Multivariate response and parsimony for Gaussian cluster-weighted models—0
Notes on Noise Contrastive Estimation and Negative SamplingCode0
Training for Fast Sequential Prediction Using Dynamic Feature Selection—0
Bayesian estimation of the multifractality parameter for image texture using a Whittle approximation—0
Adaptive Low-Complexity Sequential Inference for Dirichlet Process Mixture Models—0
SAME but Different: Fast and High-Quality Gibbs Parameter EstimationCode1
Real-time Crowd Tracking using Parameter Optimized Mixture of Motion Models—0
Hardness of parameter estimation in graphical models—0
Context-specific independence in graphical log-linear models—0
Asymptotic and finite-sample properties of estimators based on stochastic gradients—0
Low-rank SIFT: An Affine Invariant Feature for Place Recognition—0
RankMerging: A supervised learning-to-rank framework to predict links in large social network—0
Theoretical Analysis of Bayesian Optimisation with Unknown Gaussian Process Hyper-ParametersCode0
Guaranteed Scalable Learning of Latent Tree Models—0
Distributed Parameter Estimation in Probabilistic Graphical Models—0
Learning Latent Variable Gaussian Graphical Models—0
Newton Greedy Pursuit: A Quadratic Approximation Method for Sparsity-Constrained Optimization—0
Predicting Failures of Vision Systems—0
Seeking multi-thresholds for image segmentation with Learning Automata—0
On the Theoretical Guarantees for Parameter Estimation of Gaussian Random Field Models: A Sparse Precision Matrix ApproachCode0
On Communication Cost of Distributed Statistical Estimation and Dimensionality—0
Optimality guarantees for distributed statistical estimation—0
Probabilistic Inductive Logic Programming Based on Answer Set ProgrammingCode1
Implementing spectral methods for hidden Markov models with real-valued emissionsCode0
Asymmetric Clusters and Outliers: Mixtures of Multivariate Contaminated Shifted Asymmetric Laplace Distributions—0
Parameter estimation based on interval-valued belief structures—0
Ranking via Robust Binary Classification and Parallel Parameter Estimation in Large-Scale Data—0
A Generalized Probabilistic Framework for Compact Codebook Creation—0
Nonparametric Latent Tree Graphical Models: Inference, Estimation, and Structure Learning—0
Model-based clustering with Hidden Markov Model regression for time series with regime changes—0
Comparative Analysis of Viterbi Training and Maximum Likelihood Estimation for HMMs—0
Families of Parsimonious Finite Mixtures of Regression Models—0
Confidence Intervals and Hypothesis Testing for High-Dimensional Statistical Models—0
EDML for Learning Parameters in Directed and Undirected Graphical Models—0
Relevance Topic Model for Unstructured Social Group Activity Recognition—0
Sparse Inverse Covariance Estimation with Calibration—0
Gradient Hard Thresholding Pursuit for Sparsity-Constrained Optimization—0
Parsimonious Shifted Asymmetric Laplace Mixtures—0
Joint Estimation of Multiple Graphical Models from High Dimensional Time Series—0
Deep AutoRegressive Networks—0
The Information Geometry of Mirror Descent—0
Distributed parameter estimation of discrete hierarchical models via marginal likelihoods—0
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