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Class Knowledge Overlay to Visual Feature Learning for Zero-Shot Image Classification
New categories can be discovered by transforming semantic features into ...
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Multi-Knowledge Fusion for New Feature Generation in Generalized Zero-Shot Learning
Suffering from the semantic insufficiency and domain-shift problems, mos...
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EdgeWorkflowReal: An Edge Computing based Workflow Execution Engine for Smart Systems
Current cloud-based smart systems suffer from weaknesses such as high re...
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Cross Knowledge-based Generative Zero-Shot Learning Approach with Taxonomy Regularization
Although zero-shot learning (ZSL) has an inferential capability of recog...
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Efficiently Finding a Maximal Clique Summary via Effective Sampling
Maximal clique enumeration (MCE) is a fundamental problem in graph theor...
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MFL_COVID19: Quantifying Country-based Factors affecting Case Fatality Rate in Early Phase of COVID-19 Epidemic via Regularised Multi-task Feature Learning
Recent outbreak of COVID-19 has led a rapid global spread around the wor...
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Hyperspectral image classification based on multi-scale residual network with attention mechanism
Compared with traditional machine learning methods, deep learning method...
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Distributed Estimation for Principal Component Analysis: a Gap-free Approach
The growing size of modern data sets brings many challenges to the exist...
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Cutoff for exact recovery of Gaussian mixture models
We determine the cutoff value on separation of cluster centers for exact...
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Statistical Inference in Mean-Field Variational Bayes
We conduct non-asymptotic analysis on the mean-field variational inferen...
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Gaussian Processes with Errors in Variables: Theory and Computation
Covariate measurement error in nonparametric regression is a common prob...
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Model-based Statistical Depth with Applications to Functional Data
Statistical depth, a commonly used analytic tool in non-parametric stati...
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Cutting the Unnecessary Long Tail: Cost-Effective Big Data Clustering in the Cloud
Clustering big data often requires tremendous computational resources wh...
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Edge User Allocation with Dynamic Quality of Service
In edge computing, edge servers are placed in close proximity to end-use...
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Optimal Edge User Allocation in Edge Computing with Variable Sized Vector Bin Packing
In mobile edge computing, edge servers are geographically distributed ar...
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Implicit Regularization via Hadamard Product Over-Parametrization in High-Dimensional Linear Regression
We consider Hadamard product parametrization as a change-of-variable (ov...
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Diffusion K-means clustering on manifolds: provable exact recovery via semidefinite relaxations
We introduce the diffusion K-means clustering method on Riemannian subm...
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Hanson-Wright inequality in Hilbert spaces with application to K-means clustering for non-Euclidean data
We derive a dimensional-free Hanson-Wright inequality for quadratic form...
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On Statistical Optimality of Variational Bayes
The article addresses a long-standing open problem on the justification ...
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α-Variational Inference with Statistical Guarantees
We propose a variational approximation to Bayesian posterior distributio...
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Frequentist coverage and sup-norm convergence rate in Gaussian process regression
Gaussian process (GP) regression is a powerful interpolation technique d...
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Statistical inference for high dimensional regression via Constrained Lasso
In this paper, we propose a new method for estimation and constructing c...
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Bayesian model selection consistency and oracle inequality with intractable marginal likelihood
In this article, we investigate large sample properties of model selecti...
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Communication-Efficient Distributed Statistical Inference
We present a Communication-efficient Surrogate Likelihood (CSL) framewor...
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On the Computational Complexity of High-Dimensional Bayesian Variable Selection
We study the computational complexity of Markov chain Monte Carlo (MCMC)...
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Randomized sketches for kernels: Fast and optimal non-parametric regression
Kernel ridge regression (KRR) is a standard method for performing non-pa...
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Minimax Optimal Bayesian Aggregation
It is generally believed that ensemble approaches, which combine multipl...
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Bayesian crack detection in ultra high resolution multimodal images of paintings
The preservation of our cultural heritage is of paramount importance. Th...
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