
How useful is Active Learning for Imagebased Plant Phenotyping?
Deep learning models have been successfully deployed for a diverse array...
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Convolutional Neural Networks for Imagebased Corn Kernel Detection and Counting
Precise inseason corn grain yield estimates enable farmers to make real...
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Rootcause Analysis for Timeseries Anomalies via Spatiotemporal Graphical Modeling in Distributed Complex Systems
Performance monitoring, anomaly detection, and rootcause analysis in co...
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Semantic Adversarial Attacks: Parametric Transformations That Fool Deep Classifiers
Deep neural networks have been shown to exhibit an intriguing vulnerabil...
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A perspective on multiagent communication for information fusion
Collaborative decision making in multiagent systems typically requires ...
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Flow Shape Design for Microfluidic Devices Using Deep Reinforcement Learning
Microfluidic devices are utilized to control and direct flow behavior in...
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Influence Function based Data Poisoning Attacks to TopN Recommender Systems
Recommender system is an essential component of web services to engage u...
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Online Robust Policy Learning in the Presence of Unknown Adversaries
The growing prospect of deep reinforcement learning (DRL) being used in ...
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Spatiotemporally Constrained Action Space Attacks on Deep Reinforcement Learning Agents
Robustness of Deep Reinforcement Learning (DRL) algorithms towards adver...
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Driver Behavior Analysis Using Lane Departure Detection Under Challenging Conditions
In this paper, we present a novel model to detect lane regions and extra...
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PartiallyTyped NER Datasets Integration: Connecting Practice to Theory
While typical named entity recognition (NER) models require the training...
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Interpretable deep learning for guided structureproperty explorations in photovoltaics
The performance of an organic photovoltaic device is intricately connect...
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MultiResolution 3D Convolutional Neural Networks for Object Recognition
Learning from 3D Data is a fascinating idea which is well explored and s...
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A Heterogeneous Dynamical Graph Neural Networks Approach to Quantify Scientific Impact
Quantifying and predicting the longterm impact of scientific writings o...
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A Survey of Information Cascade Analysis: Models, Predictions and Recent Advances
The deluge of digital information in our daily life – from usergenerate...
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A Mathematical Programming Approach for Integrated Multiple Linear Regression Subset Selection and Validation
Subset selection for multiple linear regression aims to construct a regr...
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Learning and Visualizing Localized Geometric Features Using 3DCNN: An Application to Manufacturability Analysis of Drilled Holes
3D Convolutional Neural Networks (3DCNN) have been used for object reco...
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Learning Graphical Models from a Distributed Stream
A current challenge for data management systems is to support the constr...
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Video Denoising and Enhancement via Dynamic Video Layering
Video denoising refers to the problem of removing "noise" from a video s...
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Mitigating Evasion Attacks to Deep Neural Networks via Regionbased Classification
Deep neural networks (DNNs) have transformed several artificial intellig...
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Early Detection of Combustion Instabilities using Deep Convolutional Selective Autoencoders on Hispeed Flame Video
This paper proposes an endtoend convolutional selective autoencoder ap...
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Occlusion Edge Detection in RGBD Frames using Deep Convolutional Networks
Occlusion edges in images which correspond to range discontinuity in the...
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A Nonconvex Splitting Method for Symmetric Nonnegative Matrix Factorization: Convergence Analysis and Optimality
Symmetric nonnegative matrix factorization (SymNMF) has important applic...
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Optimization for L1Norm Error Fitting via Data Aggregation
We propose a data aggregationbased algorithm with monotonic convergence...
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Hierarchical Symbolic Dynamic Filtering of Streaming Nonstationary Time Series Data
This paper proposes a hierarchical feature extractor for nonstationary ...
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Energy Prediction using Spatiotemporal Pattern Networks
This paper presents a novel datadriven technique based on the spatiotem...
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Bayesian Network Learning via Topological Order
We propose a mixed integer programming (MIP) model and iterative algorit...
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A Bayesian Network approach to CountyLevel Corn Yield Prediction using historical data and expert knowledge
Crop yield forecasting is the methodology of predicting crop yields prio...
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PrivacyPreserving Adversarial Networks
We propose a datadriven framework for optimizing privacypreserving dat...
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Merging Kmeans with hierarchical clustering for identifying generalshaped groups
Clustering partitions a dataset such that observations placed together i...
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Scalable and Flexible Multiview MAXVAR Canonical Correlation Analysis
Generalized canonical correlation analysis (GCCA) aims at finding latent...
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NESTT: A Nonconvex PrimalDual Splitting Method for Distributed and Stochastic Optimization
We study a stochastic and distributed algorithm for nonconvex problems w...
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A Parallel Algorithm for Exact Bayesian Structure Discovery in Bayesian Networks
Exact Bayesian structure discovery in Bayesian networks requires exponen...
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An endtoend convolutional selective autoencoder approach to Soybean Cyst Nematode eggs detection
This paper proposes a novel selective autoencoder approach within the fr...
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Synthesis of Gaussian Trees with Correlation Sign Ambiguity: An Information Theoretic Approach
In latent Gaussian trees the pairwise correlation signs between the vari...
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Projected Nesterov's ProximalGradient Algorithm for Sparse Signal Reconstruction with a Convex Constraint
We develop a projected Nesterov's proximalgradient (PNPG) approach for ...
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Structure Learning in Bayesian Networks of Moderate Size by Efficient Sampling
We study the Bayesian model averaging approach to learning Bayesian netw...
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Alternating direction method of multipliers for penalized zerovariance discriminant analysis
We consider the task of classification in the high dimensional setting w...
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A MaxProduct EM Algorithm for Reconstructing Markovtree Sparse Signals from Compressive Samples
We propose a Bayesian expectationmaximization (EM) algorithm for recons...
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Spatial Multiresolution Cluster Detection Method
A novel multiresolution cluster detection (MCD) method is proposed to i...
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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...
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Exact Reconstruction Conditions for Regularized Modified Basis Pursuit
In this correspondence, we obtain exact recovery conditions for regulari...
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PaFiMoCS: Particle Filtered ModifiedCS and Applications in Visual Tracking across Illumination Change
We study the problem of tracking (causally estimating) a time sequence o...
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Realtime Robust Principal Components' Pursuit
In the recent work of Candes et al, the problem of recovering low rank m...
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Automated assessment of nonnative learner essays: Investigating the role of linguistic features
Automatic essay scoring (AES) refers to the process of scoring free text...
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Readabilitybased Sentence Ranking for Evaluating Text Simplification
We propose a new method for evaluating the readability of simplified sen...
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DevicetoDevice Networking Meets Cellular via Network Coding
Utilizing devicetodevice (D2D) connections among mobile devices is pro...
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Notes on complexity of packing coloring
A packing kcoloring for some integer k of a graph G=(V,E) is a mapping ...
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Projection Theorems Using Effective Dimension
In this paper we use the theory of computing to study fractal dimensions...
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Barrel Shifter Physical Unclonable Function Based Encryption
Physical Unclonable Functions (PUFs) are circuits designed to extract ph...
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Iowa State University of Science and Technology
Iowa State University of Science and Technology is a flagship public landgrant and spacegrant research university in Ames, Iowa.