
Hierarchical clustering by aggregating representatives in subminimumspanningtrees
One of the main challenges for hierarchical clustering is how to appropr...
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Iterative Teaching by Label Synthesis
In this paper, we consider the problem of iterative machine teaching, wh...
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A ConsciousnessInspired Planning Agent for ModelBased Reinforcement Learning
We present an endtoend, modelbased deep reinforcement learning agent ...
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ADNet: Attentionguided Deformable Convolutional Network for High Dynamic Range Imaging
In this paper, we present an attentionguided deformable convolutional n...
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LSTM Based Sentiment Analysis for Cryptocurrency Prediction
Recent studies in big data analytics and natural language processing dev...
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Learning with Hyperspherical Uniformity
Due to the overparameterization nature, neural networks are a powerful ...
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A Bayesian Spatial Modeling Approach to Mortality Forecasting
This paper extends Bayesian mortality projection models for multiple pop...
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A Datadriven Human Responsibility Management System
An ideal safe workplace is described as a place where staffs fulfill res...
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Using Machine Learning to Automate Mammogram Images Analysis
Breast cancer is the second leading cause of cancerrelated death after ...
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Bayesian Poisson Lognormal Model with Regularized Time Structure for Mortality Projection of Multipopulation
The improvement of mortality projection is a pivotal topic in the divers...
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Orthogonal OverParameterized Training
The inductive bias of a neural network is largely determined by the arch...
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NEW: A Generic Learning Model for Tie Strength Prediction in Networks
Tie strength prediction, sometimes named weight prediction, is vital in ...
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A Compared Study Between Some Subspace Based Algorithms
The technology of face recognition has made some progress in recent year...
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VisualTextual Association with Hardest and SemiHard Negative Pairs Mining for Person Search
Searching persons in largescale image databases with the query of natur...
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Neural Similarity Learning
Inner productbased convolution has been the founding stone of convoluti...
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Contextendcoding for neural network based skull stripping in magnetic resonance imaging
Skull stripping is usually the first step for most brain analysisprocess...
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Compressive Hyperspherical Energy Minimization
Recent work on minimum hyperspherical energy (MHE) has demonstrated its ...
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Exponential Family Estimation via Adversarial Dynamics Embedding
We present an efficient algorithm for maximum likelihood estimation (MLE...
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Learning towards Minimum Hyperspherical Energy
Neural networks are a powerful class of nonlinear functions that can be ...
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Decoupled Networks
Inner productbased convolution has been a central component of convolut...
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Deep Forward and Inverse Perceptual Models for Tracking and Prediction
We consider the problems of learning forward models that map state to hi...
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OneShot Learning for Semantic Segmentation
Lowshot learning methods for image classification support learning from...
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Kernelized Deep Convolutional Neural Network for Describing Complex Images
With the impressive capability to capture visual content, deep convoluti...
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Efficient Bayesian analysis of multiple changepoint models with dependence across segments
We consider Bayesian analysis of a class of multiple changepoint models....
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Zhen Liu
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