
Highquality Lowdose CT Reconstruction Using Convolutional Neural Networks with Spatial and Channel Squeeze and Excitation
Lowdose computed tomography (CT) allows the reduction of radiation risk...
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Quantization Algorithms for Random Fourier Features
The method of random projection (RP) is the standard technique in machin...
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Learning EnergyBased Model with Variational AutoEncoder as Amortized Sampler
Due to the intractable partition function, training energybased models ...
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Identification of Matrix Joint Block Diagonalization
Given a set 𝒞={C_i}_i=1^m of square matrices, the matrix blind joint blo...
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Tensor Completion via Tensor Networks with a Tucker Wrapper
In recent years, lowrank tensor completion (LRTC) has received consider...
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Exploring global diverse attention via pairwise temporal relation for video summarization
Video summarization is an effective way to facilitate video searching an...
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A Framework of Randomized Selection Based Certified Defenses Against Data Poisoning Attacks
Neural network classifiers are vulnerable to data poisoning attacks, as ...
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Adaptive Randomization in Network Data
Network data have appeared frequently in recent research. For example, i...
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Understanding and Detecting Convergence for Stochastic Gradient Descent with Momentum
Convergence detection of iterative stochastic optimization methods is of...
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ClusterAdaptive Network A/B Testing: From Randomization to Estimation
A/B testing is an important decisionmaking tool in product development ...
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MeDaS: An opensource platform as service to help break the walls between medicine and informatics
In the past decade, deep learning (DL) has achieved unprecedented succes...
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Cooperative RateSplitting for Secrecy SumRate Enhancement in Multiantenna Broadcast Channels
In this paper, we employ Cooperative RateSplitting (CRS) technique to e...
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A hybridizable discontinuous Galerkin method for simulation of electrostatic problems with floating potential conductors
In an electrostatic simulation, an equipotential condition with an undef...
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Distributed PrimalDual Optimization for Online MultiTask Learning
Conventional online multitask learning algorithms suffer from two criti...
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IVFS: Simple and Efficient Feature Selection for High Dimensional Topology Preservation
Feature selection is an important tool to deal with high dimensional dat...
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Randomized Kernel Multiview Discriminant Analysis
In many artificial intelligence and computer vision systems, the same ob...
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Solving the Robust Matrix Completion Problem via a System of Nonlinear Equations
We consider the problem of robust matrix completion, which aims to recov...
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An Inversefree Truncated RayleighRitz Method for Sparse Generalized Eigenvalue Problem
This paper considers the sparse generalized eigenvalue problem (SGEP), w...
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Distributed Hierarchical GPU Parameter Server for Massive Scale Deep Learning Ads Systems
Neural networks of ads systems usually take input from multiple resource...
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MetaCoTGAN: A Meta Cooperative Training Paradigm for Improving Adversarial Text Generation
Training generative models that can generate highquality text with suff...
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Selective Convolutional Network: An Efficient Object Detector with Ignoring Background
It is well known that attention mechanisms can effectively improve the p...
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StructureFeature based Graph Selfadaptive Pooling
Various methods to deal with graph data have been proposed in recent yea...
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Generalization Bounds for Highdimensional Mestimation under Sparsity Constraint
The ℓ_0constrained empirical risk minimization (ℓ_0ERM) is a promising...
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Outlier Detection and Data Clustering via Innovation Search
The idea of Innovation Search was proposed as a data clustering method i...
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Complexity results for the proper disconnection of graphs
For an edgecolored graph G, a set F of edges of G is called a proper ed...
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A Fourier Analytical Approach to Estimation of Smooth Functions in Gaussian Shift Model
We study the estimation of f() under Gaussian shift model = +, where ∈^d...
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Graph Analysis and Graph Pooling in the Spatial Domain
The spatial convolution layer which is widely used in the Graph Neural N...
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Permutation Recovery from Multiple Measurement Vectors in Unlabeled Sensing
In "Unlabeled Sensing", one observes a set of linear measurements of an ...
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MultiSpectral Visual Odometry without Explicit Stereo Matching
Multispectral sensors consisting of a standard (visiblelight) camera a...
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On Convergence of Distributed Approximate Newton Methods: Globalization, Sharper Bounds and Beyond
The DANE algorithm is an approximate Newton method popularly used for co...
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A TwoStage Approach to Multivariate Linear Regression with Sparsely Mismatched Data
A tacit assumption in linear regression is that (response, predictor)pa...
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Logician: A Unified EndtoEnd Neural Approach for OpenDomain Information Extraction
In this paper, we consider the problem of open information extraction (O...
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CycleSUM: Cycleconsistent Adversarial LSTM Networks for Unsupervised Video Summarization
In this paper, we present a novel unsupervised video summarization model...
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Optimistic Adaptive Acceleration for Optimization
We consider a new variant of AMSGrad. AMSGrad RKK18 is a popular adaptiv...
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NonAsymptotic Chernoff Lower Bound and Its Application to Community Detection in Stochastic Block Model
Chernoff coefficient is an upper bound of Bayes error probability in cla...
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RGBD SLAM in Dynamic Environments Using Points Correlations
This paper proposed a novel RGBD SLAM method for dynamic environments. ...
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On cyclic codes of length 2^e over finite fields
Professor Cunsheng Ding gave cyclotomic constructions of cyclic codes wi...
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Several Tunable GMM Kernels
While tree methods have been popular in practice, researchers and practi...
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SignFull Random Projections
The method of 1bit ("signsign") random projections has been a popular ...
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Image matting with normalized weight and semisupervised learning
Image matting is an important vision problem. The main stream methods fo...
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L2GSCI: Local to Global Seam Cutting and Integrating for Accurate Face Contour Extraction
Current face alignment algorithms can robustly find a set of landmarks a...
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Tunable GMM Kernels
The recently proposed "generalized minmax" (GMM) kernel can be efficien...
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Generalized Intersection Kernel
Following the very recent line of work on the "generalized minmax" (GMM...
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Constrained LowRank Learning Using Least SquaresBased Regularization
Lowrank learning has attracted much attention recently due to its effic...
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Nystrom Method for Approximating the GMM Kernel
The GMM (generalized minmax) kernel was recently proposed (Li, 2016) as...
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Linearized GMM Kernels and Normalized Random Fourier Features
The method of "random Fourier features (RFF)" has become a popular tool ...
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A Tight Bound of Hard Thresholding
This paper is concerned with the hard thresholding technique which sets ...
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A Comparison Study of Nonlinear Kernels
In this paper, we compare 5 different nonlinear kernels: minmax, RBF, f...
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2Bit Random Projections, NonLinear Estimators, and Approximate Near Neighbor Search
The method of random projections has become a standard tool for machine ...
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Sign Stable Random Projections for LargeScale Learning
We study the use of "sign αstable random projections" (where 0<α≤ 2) fo...
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