Iowa State University of Science and Technology

research

∙ 06/07/2020

How useful is Active Learning for Image-based Plant Phenotyping?

Deep learning models have been successfully deployed for a diverse array...

Koushik Nagasubramanian, et al. ∙

research

∙ 06/22/2022

Heterogeneous Graph Neural Networks for Software Effort Estimation

Software effort can be measured by story point [35]. Current approaches ...

Hung Phan, et al. ∙

research

∙ 03/26/2020

Convolutional Neural Networks for Image-based Corn Kernel Detection and Counting

Precise in-season corn grain yield estimates enable farmers to make real...

Saeed Khaki, et al. ∙

research

∙ 05/31/2018

Root-cause Analysis for Time-series Anomalies via Spatiotemporal Graphical Modeling in Distributed Complex Systems

Performance monitoring, anomaly detection, and root-cause analysis in co...

Chao Liu, et al. ∙

research

∙ 04/17/2019

Semantic Adversarial Attacks: Parametric Transformations That Fool Deep Classifiers

Deep neural networks have been shown to exhibit an intriguing vulnerabil...

Ameya Joshi, et al. ∙

research

∙ 11/09/2019

A perspective on multi-agent communication for information fusion

Collaborative decision making in multi-agent systems typically requires ...

Homagni Saha, et al. ∙

research

∙ 11/29/2018

Flow Shape Design for Microfluidic Devices Using Deep Reinforcement Learning

Microfluidic devices are utilized to control and direct flow behavior in...

Xian Yeow Lee, et al. ∙

research

∙ 02/19/2020

Influence Function based Data Poisoning Attacks to Top-N Recommender Systems

Recommender system is an essential component of web services to engage u...

Minghong Fang, et al. ∙

research

∙ 07/16/2018

Online Robust Policy Learning in the Presence of Unknown Adversaries

The growing prospect of deep reinforcement learning (DRL) being used in ...

Aaron J. Havens, et al. ∙

research

∙ 09/05/2019

Spatiotemporally Constrained Action Space Attacks on Deep Reinforcement Learning Agents

Robustness of Deep Reinforcement Learning (DRL) algorithms towards adver...

Xian Yeow Lee, et al. ∙

research

∙ 09/21/2021

Beyond Discriminant Patterns: On the Robustness of Decision Rule Ensembles

Local decision rules are commonly understood to be more explainable, due...

Xin Du, et al. ∙

research

∙ 09/24/2021

A Graph Policy Network Approach for Volt-Var Control in Power Distribution Systems

Volt-var control (VVC) is the problem of operating power distribution sy...

Xian Yeow Lee, et al. ∙

research

∙ 05/31/2019

Driver Behavior Analysis Using Lane Departure Detection Under Challenging Conditions

In this paper, we present a novel model to detect lane regions and extra...

Luis Riera, et al. ∙

research

∙ 10/19/2020

Topology-Aware Graph Pooling Networks

Pooling operations have shown to be effective on computer vision and nat...

Hongyang Gao, et al. ∙

research

∙ 10/04/2021

Cross-Modal Virtual Sensing for Combustion Instability Monitoring

In many cyber-physical systems, imaging can be an important but expensiv...

Tryambak Gangopadhyay, et al. ∙

research

∙ 05/01/2020

Partially-Typed NER Datasets Integration: Connecting Practice to Theory

While typical named entity recognition (NER) models require the training...

Shi Zhi, et al. ∙

research

∙ 03/17/2021

WheatNet: A Lightweight Convolutional Neural Network for High-throughput Image-based Wheat Head Detection and Counting

For a globally recognized planting breeding organization, manually-recor...

Saeed Khaki, et al. ∙

research

∙ 11/29/2021

SPATL: Salient Parameter Aggregation and Transfer Learning for Heterogeneous Clients in Federated Learning

Efficient federated learning is one of the key challenges for training a...

Sixing Yu, et al. ∙

research

∙ 04/29/2022

Concept Activation Vectors for Generating User-Defined 3D Shapes

We explore the interpretability of 3D geometric deep learning models in ...

Stefan Druc, et al. ∙

research

∙ 11/14/2018

Interpretable deep learning for guided structure-property explorations in photovoltaics

The performance of an organic photovoltaic device is intricately connect...

Balaji Sesha Sarath Pokuri, et al. ∙

research

∙ 03/06/2022

Story Point Effort Estimation by Text Level Graph Neural Network

Estimating the software projects' efforts developed by agile methods is ...

Hung Phan, et al. ∙

research

∙ 05/30/2018

Multi-Resolution 3D Convolutional Neural Networks for Object Recognition

Learning from 3D Data is a fascinating idea which is well explored and s...

Sambit Ghadai, et al. ∙

research

∙ 03/26/2020

A Heterogeneous Dynamical Graph Neural Networks Approach to Quantify Scientific Impact

Quantifying and predicting the long-term impact of scientific writings o...

Fan Zhou, et al. ∙

research

∙ 05/22/2020

A Survey of Information Cascade Analysis: Models, Predictions and Recent Advances

The deluge of digital information in our daily life – from user-generate...

Fan Zhou, et al. ∙

research

∙ 12/12/2017

A Mathematical Programming Approach for Integrated Multiple Linear Regression Subset Selection and Validation

Subset selection for multiple linear regression aims to construct a regr...

Seokhyun Chung, et al. ∙

research

∙ 11/13/2017

Learning and Visualizing Localized Geometric Features Using 3D-CNN: An Application to Manufacturability Analysis of Drilled Holes

3D Convolutional Neural Networks (3D-CNN) have been used for object reco...

Sambit Ghadai, et al. ∙

research

∙ 10/05/2017

Learning Graphical Models from a Distributed Stream

A current challenge for data management systems is to support the constr...

Yu Zhang, et al. ∙

research

∙ 10/05/2017

Video Denoising and Enhancement via Dynamic Video Layering

Video denoising refers to the problem of removing "noise" from a video s...

Han Guo, et al. ∙

research

∙ 09/17/2017

Mitigating Evasion Attacks to Deep Neural Networks via Region-based Classification

Deep neural networks (DNNs) have transformed several artificial intellig...

Xiaoyu Cao, et al. ∙

research

∙ 03/25/2016

Early Detection of Combustion Instabilities using Deep Convolutional Selective Autoencoders on Hi-speed Flame Video

This paper proposes an end-to-end convolutional selective autoencoder ap...

Adedotun Akintayo, et al. ∙

research

∙ 12/22/2014

Occlusion Edge Detection in RGB-D Frames using Deep Convolutional Networks

Occlusion edges in images which correspond to range discontinuity in the...

Soumik Sarkar, et al. ∙

research

∙ 03/24/2017

A Nonconvex Splitting Method for Symmetric Nonnegative Matrix Factorization: Convergence Analysis and Optimality

Symmetric nonnegative matrix factorization (SymNMF) has important applic...

Songtao Lu, et al. ∙

research

∙ 03/15/2017

Optimization for L1-Norm Error Fitting via Data Aggregation

We propose a data aggregation-based algorithm with monotonic convergence...

Young Woong Park, et al. ∙

research

∙ 02/06/2017

Hierarchical Symbolic Dynamic Filtering of Streaming Non-stationary Time Series Data

This paper proposes a hierarchical feature extractor for non-stationary ...

Adedotun Akintayo, et al. ∙

research

∙ 02/03/2017

Energy Prediction using Spatiotemporal Pattern Networks

This paper presents a novel data-driven technique based on the spatiotem...

Zhanhong Jiang, et al. ∙

research

∙ 01/20/2017

Bayesian Network Learning via Topological Order

We propose a mixed integer programming (MIP) model and iterative algorit...

Young Woong Park, et al. ∙

research

∙ 08/17/2016

A Bayesian Network approach to County-Level Corn Yield Prediction using historical data and expert knowledge

Crop yield forecasting is the methodology of predicting crop yields prio...

Vikas Chawla, et al. ∙

research

∙ 12/19/2017

Privacy-Preserving Adversarial Networks

We propose a data-driven framework for optimizing privacy-preserving dat...

Ardhendu Tripathy, et al. ∙

research

∙ 12/23/2017

Merging K-means with hierarchical clustering for identifying general-shaped groups

Clustering partitions a dataset such that observations placed together i...

Anna D. Peterson, et al. ∙

research

∙ 05/31/2016

Scalable and Flexible Multiview MAX-VAR Canonical Correlation Analysis

Generalized canonical correlation analysis (GCCA) aims at finding latent...

Xiao Fu, et al. ∙

research

∙ 05/25/2016

NESTT: A Nonconvex Primal-Dual Splitting Method for Distributed and Stochastic Optimization

We study a stochastic and distributed algorithm for nonconvex problems w...

Davood Hajinezhad, et al. ∙

research

∙ 08/07/2014

A Parallel Algorithm for Exact Bayesian Structure Discovery in Bayesian Networks

Exact Bayesian structure discovery in Bayesian networks requires exponen...

Yetian Chen, et al. ∙

research

∙ 03/25/2016

An end-to-end convolutional selective autoencoder approach to Soybean Cyst Nematode eggs detection

This paper proposes a novel selective autoencoder approach within the fr...

Adedotun Akintayo, et al. ∙

research

∙ 01/24/2016

Synthesis of Gaussian Trees with Correlation Sign Ambiguity: An Information Theoretic Approach

In latent Gaussian trees the pairwise correlation signs between the vari...

Ali Moharrer, et al. ∙

research

∙ 02/09/2015

Projected Nesterov's Proximal-Gradient Algorithm for Sparse Signal Reconstruction with a Convex Constraint

We develop a projected Nesterov's proximal-gradient (PNPG) approach for ...

Renliang Gu, et al. ∙

research

∙ 01/19/2015

Structure Learning in Bayesian Networks of Moderate Size by Efficient Sampling

We study the Bayesian model averaging approach to learning Bayesian netw...

Ru He, et al. ∙

research

∙ 01/21/2014

Alternating direction method of multipliers for penalized zero-variance discriminant analysis

We consider the task of classification in the high dimensional setting w...

Brendan P. W. Ames, et al. ∙

research

∙ 09/05/2012

A Max-Product EM Algorithm for Reconstructing Markov-tree Sparse Signals from Compressive Samples

We propose a Bayesian expectation-maximization (EM) algorithm for recons...

Zhao Song, et al. ∙

research

∙ 05/09/2012

Spatial Multiresolution Cluster Detection Method

A novel multi-resolution cluster detection (MCD) method is proposed to i...

Lingsong Zhang, et al. ∙

research

∙ 12/02/2011

Mask Iterative Hard Thresholding Algorithms for Sparse Image Reconstruction of Objects with Known Contour

We develop mask iterative hard thresholding algorithms (mask IHT and mas...

Aleksandar Dogandžić, et al. ∙

Iowa State University of Science and Technology

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