
Attentionbased network for lowlight image enhancement
The captured images under low light conditions often suffer insufficient...
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Assessing the Memory Ability of Recurrent Neural Networks
It is known that Recurrent Neural Networks (RNNs) can remember, in their...
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A Causal View on Robustness of Neural Networks
We present a causal view on the robustness of neural networks against in...
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Tightening Bounds for Variational Inference by Revisiting Perturbation Theory
Variational inference has become one of the most widely used methods in ...
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Generalization in Reinforcement Learning with Selective Noise Injection and Information Bottleneck
The ability for policies to generalize to new environments is key to the...
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Interpretable Outcome Prediction with Sparse Bayesian Neural Networks in Intensive Care
Clinical decision making is challenging because of pathological complexi...
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Data Manipulation: Towards Effective Instance Learning for Neural Dialogue Generation via Learning to Augment and Reweight
Current stateoftheart neural dialogue models learn from human convers...
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Causal discovery in the presence of missing data
Missing data are ubiquitous in many domains such as healthcare. Dependin...
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EDDI: Efficient Dynamic Discovery of HighValue Information with Partial VAE
Making decisions requires information relevant to the task at hand. Many...
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A Hierarchical Grocery Store Image Dataset with Visual and Semantic Labels
Image classification models built into visual support systems and other ...
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Neuropathic Pain Diagnosis Simulator for Causal Discovery Algorithm Evaluation
Discovery of causal relations from observational data is essential for m...
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Causality Refined Diagnostic Prediction
Applying machine learning in the health care domain has shown promising ...
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Advances in Variational Inference
Many modern unsupervised or semisupervised machine learning algorithms ...
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Perturbative Black Box Variational Inference
Black box variational inference (BBVI) with reparameterization gradients...
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FontCode: Embedding Information in Text Documents using Glyph Perturbation
We introduce FontCode, an information embedding technique for text docum...
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Determinantal Point Processes for MiniBatch Diversification
We study a minibatch diversification scheme for stochastic gradient des...
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Variational Hamiltonian Monte Carlo via Score Matching
Traditionally, the field of computational Bayesian statistics has been d...
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Hamiltonian Monte Carlo Acceleration Using Surrogate Functions with Random Bases
For big data analysis, high computational cost for Bayesian methods ofte...
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InterBattery Topic Representation Learning
In this paper, we present the InterBattery Topic Model (IBTM). Our appr...
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MultiClass Detection and Segmentation of Objects in Depth
The quality of life of many people could be improved by autonomous human...
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Factorized Topic Models
In this paper we present a modification to a latent topic model, which m...
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Viewpoint and Topic Modeling of Current Events
There are multiple sides to every story, and while statistical topic mod...
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Signal Processing for MIMONOMA: Present and Future Challenges
Nonorthogonal multiple access (NOMA), as the newest member of the multi...
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Cost and EnergyAware MultiFlow Mobile Data Offloading Using Markov Decision Process
With the rapid increase in demand for mobile data, mobile network operat...
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A Deep Reinforcement Learning Based Approach for Cost and EnergyAware MultiFlow Mobile Data Offloading
With the rapid increase in demand for mobile data, mobile network operat...
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Active MiniBatch Sampling using Repulsive Point Processes
The convergence speed of stochastic gradient descent (SGD) can be improv...
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Nonbifurcating phylogenetic tree inference via the adaptive LASSO
Phylogenetic tree inference using deep DNA sequencing is reshaping our u...
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Nonrigid image registration using spatially regionweighted correlation ratio and GPUacceleration
Objective: Nonrigid image registration with high accuracy and efficienc...
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Application of HilbertHuang decomposition to reduce noise and characterize for NMR FID signal of proton precession magnetometer
The parameters in a nuclear magnetic resonance (NMR) free induction deca...
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Generalizing Tree Probability Estimation via Bayesian Networks
Probability estimation is one of the fundamental tasks in statistics and...
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Learning Discriminative 3D Shape Representations by View Discerning Networks
In viewbased 3D shape recognition, extracting discriminative visual rep...
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An Empirical Study on Leveraging Scene Graphs for Visual Question Answering
Visual question answering (Visual QA) has attracted significant attentio...
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On the identifiability of interaction functions in systems of interacting particles
Identifiability is of fundamental importance in the statistical learning...
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Learning from Easy to Complex: Adaptive Multicurricula Learning for Neural Dialogue Generation
Current stateoftheart neural dialogue systems are mainly datadriven ...
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Adaptive Parameterization for Neural Dialogue Generation
Neural conversation systems generate responses based on the sequenceto...
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LargeScale Educational Question Analysis with Partial Variational Autoencoders
Online education platforms enable teachers to share a large number of ed...
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Cheng Zhang
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Graduate Research Assisstant at Ubiquitous Computing Group at Georgia Institute of Technology since 2012, Research Intern at Yahoo! Labs 2014, Graduate Research Assistant at Institute of Software, Chinese Academy of Sciences from 20092012, Graduate Student of omputer Science at Georgia Institute of Technology from 20122017