Wayne State University

research

∙ 03/04/2020

On the Learning Property of Logistic and Softmax Losses for Deep Neural Networks

Deep convolutional neural networks (CNNs) trained with logistic and soft...

Xiangrui Li, et al. ∙

research

∙ 08/19/2019

SPA-GAN: Spatial Attention GAN for Image-to-Image Translation

Image-to-image translation is to learn a mapping between images from a s...

Hajar Emami, et al. ∙

research

∙ 04/06/2020

COVID-MobileXpert: On-Device COVID-19 Screening using Snapshots of Chest X-Ray

With the increasing demand for millions of COVID-19 screenings, Computed...

Xin Li, et al. ∙

research

∙ 07/12/2020

Explainable Recommendation via Interpretable Feature Mapping and Evaluation of Explainability

Latent factor collaborative filtering (CF) has been a widely used techni...

Deng Pan, et al. ∙

research

∙ 06/24/2020

Defending against adversarial attacks on medical imaging AI system, classification or detection?

Medical imaging AI systems such as disease classification and segmentati...

Xin Li, et al. ∙

research

∙ 02/23/2020

Improve SGD Training via Aligning Min-batches

Deep neural networks (DNNs) for supervised learning can be viewed as a p...

Xiangrui Li, et al. ∙

research

∙ 04/06/2020

COVID-Xpert: An AI Powered Population Screening of COVID-19 Cases Using Chest Radiography Images

With the increasing demand for millions of COVID-19 tests, Computed Tomo...

Xin Li, et al. ∙

research

∙ 02/23/2020

Improve SGD Training via Aligning Mini-batches

Deep neural networks (DNNs) for supervised learning can be viewed as a p...

Xiangrui Li, et al. ∙

research

∙ 08/08/2021

Hierarchical View Predictor: Unsupervised 3D Global Feature Learning through Hierarchical Prediction among Unordered Views

Unsupervised learning of global features for 3D shape analysis is an imp...

Zhizhong Han, et al. ∙

research

∙ 09/26/2017

SUBIC: A Supervised Bi-Clustering Approach for Precision Medicine

Traditional medicine typically applies one-size-fits-all treatment for t...

Milad Zafar Nezhad, et al. ∙

research

∙ 04/20/2017

SAFS: A Deep Feature Selection Approach for Precision Medicine

In this paper, we propose a new deep feature selection method based on d...

Milad Zafar Nezhad, et al. ∙

research

∙ 01/06/2018

A Predictive Approach Using Deep Feature Learning for Electronic Medical Records: A Comparative Study

Massive amount of electronic medical records accumulating from patients ...

Milad Zafar Nezhad, et al. ∙

research

∙ 06/09/2019

Interpreting Age Effects of Human Fetal Brain from Spontaneous fMRI using Deep 3D Convolutional Neural Networks

Understanding human fetal neurodevelopment is of great clinical importan...

Xiangrui Li, et al. ∙

research

∙ 06/12/2019

Vispi: Automatic Visual Perception and Interpretation of Chest X-rays

Medical imaging contains the essential information for rendering diagnos...

Xin Li, et al. ∙

research

∙ 07/29/2019

Tackling Multiple Ordinal Regression Problems: Sparse and Deep Multi-Task Learning Approaches

Many real-world datasets are labeled with natural orders, i.e., ordinal ...

Lu Wang, et al. ∙

research

∙ 03/22/2020

Toward Tag-free Aspect Based Sentiment Analysis: A Multiple Attention Network Approach

Existing aspect based sentiment analysis (ABSA) approaches leverage vari...

Yao Qiang, et al. ∙

research

∙ 04/23/2022

Surface Reconstruction from Point Clouds by Learning Predictive Context Priors

Surface reconstruction from point clouds is vital for 3D computer vision...

Baorui Ma, et al. ∙

research

∙ 10/12/2017

A Unified Neural Network Approach for Estimating Travel Time and Distance for a Taxi Trip

In building intelligent transportation systems such as taxi or rideshare...

Ishan Jindal, et al. ∙

research

∙ 05/09/2017

Learning Deep Networks from Noisy Labels with Dropout Regularization

Large datasets often have unreliable labels-such as those obtained from ...

Ishan Jindal, et al. ∙

research

∙ 05/07/2017

Performance Limits on the Classification of Kronecker-structured Models

Kronecker-structured (K-S) models recently have been proposed for the ef...

Ishan Jindal, et al. ∙

research

∙ 04/25/2017

Stochastic Optimization from Distributed, Streaming Data in Rate-limited Networks

Motivated by machine learning applications in networks of sensors, inter...

Matthew Nokleby, et al. ∙

research

∙ 06/27/2017

Large-scale Datasets: Faces with Partial Occlusions and Pose Variations in the Wild

Face detection methods have relied on face datasets for training. Howeve...

Tarik Alafif, et al. ∙

research

∙ 02/22/2013

On the performance of a hybrid genetic algorithm in dynamic environments

The ability to track the optimum of dynamic environments is important in...

Quan Yuan, et al. ∙

research

∙ 02/21/2013

A Weight-coded Evolutionary Algorithm for the Multidimensional Knapsack Problem

A revised weight-coded evolutionary algorithm (RWCEA) is proposed for so...

Quan Yuan, et al. ∙

research

∙ 11/16/2016

Machine Learning Approach for Skill Evaluation in Robotic-Assisted Surgery

Evaluating surgeon skill has predominantly been a subjective task. Devel...

Mahtab J. Fard, et al. ∙

research

∙ 05/08/2016

Rate-Distortion Bounds on Bayes Risk in Supervised Learning

We present an information-theoretic framework for bounding the number of...

Matthew Nokleby, et al. ∙

research

∙ 06/10/2012

Comments on "On Approximating Euclidean Metrics by Weighted t-Cost Distances in Arbitrary Dimension"

Mukherjee (Pattern Recognition Letters, vol. 32, pp. 824-831, 2011) rece...

M. Emre Celebi, et al. ∙

research

∙ 09/04/2010

Fast Color Space Transformations Using Minimax Approximations

Color space transformations are frequently used in image processing, gra...

M. Emre Celebi, et al. ∙

research

∙ 08/28/2010

On Euclidean Norm Approximations

Euclidean norm calculations arise frequently in scientific and engineeri...

M. Emre Celebi, et al. ∙

research

∙ 02/23/2018

Multi-scale Spectrum Sensing in 5G Cognitive Networks

A multi-scale approach to spectrum sensing is proposed to overcome the h...

Nicolo Michelusi, et al. ∙

research

∙ 04/10/2018

A Deep Active Survival Analysis Approach for Precision Treatment Recommendations: Application of Prostate Cancer

Survival analysis has been developed and applied in the number of areas ...

Milad Zafar Nezhad, et al. ∙

research

∙ 06/14/2018

Data-Driven Analytics for Benchmarking and Optimizing Retail Store Performance

Growing competitiveness and increasing availability of data is generatin...

Haidar Almohri, et al. ∙

research

∙ 07/02/2018

Unified Scheduling for Predictable Communication Reliability in Cellular Networks with D2D Links

Cellular networks with D2D links are increasingly being explored for mis...

Yuwei Xie, et al. ∙

research

∙ 07/11/2018

Co-KV: A Collaborative Key-Value Store Using Near-Data Processing to Improve Compaction for the LSM-tree

Log-structured merge tree (LSM-tree) based key-value stores are widely e...

Hui Sun, et al. ∙

research

∙ 10/15/2018

CAVBench: A Benchmark Suite for Connected and Autonomous Vehicles

Connected and autonomous vehicles (CAVs) have recently attracted a signi...

Shaoshan Liu, et al. ∙

research

∙ 10/25/2018

Tensor Matched Kronecker-Structured Subspace Detection for Missing Information

We consider the problem of detecting whether a tensor signal having many...

Ishan Jindal, et al. ∙

research

∙ 10/26/2018

Information Bottleneck Methods for Distributed Learning

We study a distributed learning problem in which Alice sends a compresse...

Parinaz Farajiparvar, et al. ∙

research

∙ 11/10/2018

Understanding the Motivations, Challenges and Needs of Blockchain Software Developers: A Survey

The blockchain technology has potential applications in various areas su...

Amiangshu Bosu, et al. ∙

research

∙ 12/13/2018

Expressions of Sentiments During Code Reviews: Male vs. Female

Background: As most of the software development organizations are male-d...

Rajshakhar Paul, et al. ∙

research

∙ 02/19/2019

A Mobility-Aware Vehicular Caching Scheme in Content Centric Networks: Model and Optimization

Edge caching is being explored as a promising technology to alleviate th...

Yao Zhang, et al. ∙

research

∙ 03/18/2019

An Effective Label Noise Model for DNN Text Classification

Because large, human-annotated datasets suffer from labeling errors, it ...

Ishan Jindal, et al. ∙

research

∙ 04/07/2019

An Asynchronous, Decentralized Solution Framework for the Large Scale Unit Commitment Problem

With increased reliance on cyber infrastructure, large scale power netwo...

Paritosh Ramanan, et al. ∙

research

∙ 04/16/2019

A-CNN: Annularly Convolutional Neural Networks on Point Clouds

Analyzing the geometric and semantic properties of 3D point clouds throu...

Artem Komarichev, et al. ∙

research

∙ 05/10/2019

Attention-based Deep Reinforcement Learning for Multi-view Environments

In reinforcement learning algorithms, it is a common practice to account...

Elaheh Barati, et al. ∙

research

∙ 06/05/2019

OpenEI: An Open Framework for Edge Intelligence

In the last five years, edge computing has attracted tremendous attentio...

Xingzhou Zhang, et al. ∙

research

∙ 06/10/2019

CRCEN: A Generalized Cost-sensitive Neural Network Approach for Imbalanced Classification

Classification on imbalanced datasets is a challenging task in real-worl...

Xiangrui Li, et al. ∙

research

∙ 07/19/2019

An Actor-Critic-Attention Mechanism for Deep Reinforcement Learning in Multi-view Environments

In reinforcement learning algorithms, leveraging multiple views of the e...

Elaheh Barati, et al. ∙

research

∙ 08/24/2019

Representation Learning with Autoencoders for Electronic Health Records: A Comparative Study

Increasing volume of Electronic Health Records (EHR) in recent years pro...

Najibesadat Sadati, et al. ∙

research

∙ 11/30/2019

On Multi-Cascade Influence Maximization: Model, Hardness and Algorithmic Framework

This paper studies the multi-cascade influence maximization problem, whi...

Guangmo Tong, et al. ∙

research

∙ 12/21/2019

Unconditionally energy stable discontinuous Galerkin schemes for the Cahn-Hilliard equation

In this paper, we introduce novel discontinuous Galerkin (DG) schemes fo...

Hailiang Liu, et al. ∙

Wayne State University

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