Theodore L. Willke

According to our database1, Theodore L. Willke authored at least 48 papers between 1977 and 2020.

Collaborative distances:



In proceedings 
PhD thesis 




BrainIAK tutorials: User-friendly learning materials for advanced fMRI analysis.
PLoS Comput. Biol., 2020

Navigating the Trade-Off between Multi-Task Learning and Learning to Multitask in Deep Neural Networks.
CoRR, 2020

Procrustean Orthogonal Sparse Hashing.
CoRR, 2020

NeuroVectorizer: end-to-end vectorization with deep reinforcement learning.
Proceedings of the CGO '20: 18th ACM/IEEE International Symposium on Code Generation and Optimization, 2020

Deep Graph Similarity Learning: A Survey.
CoRR, 2019

A single-layer RNN can approximate stacked and bidirectional RNNs, and topologies in between.
CoRR, 2019

Deep Reinforcement Learning in System Optimization.
CoRR, 2019

Deep Graph Similarity Learning for Brain Data Analysis.
Proceedings of the 28th ACM International Conference on Information and Knowledge Management, 2019

A probabilistic approach to discovering dynamic full-brain functional connectivity patterns.
NeuroImage, 2018

Similarity Learning with Higher-Order Proximity for Brain Network Analysis.
CoRR, 2018

Clinically Deployed Distributed Magnetic Resonance Imaging Reconstruction: Application to Pediatric Knee Imaging.
CoRR, 2018

Scheduling Computation Graphs of Deep Learning Models on Manycore CPUs.
CoRR, 2018

Learning Role-based Graph Embeddings.
CoRR, 2018

Capturing Shared and Individual Information in fMRI Data.
Proceedings of the 2018 IEEE International Conference on Acoustics, 2018

Out-of-Distribution Detection Using an Ensemble of Self Supervised Leave-Out Classifiers.
Proceedings of the Computer Vision - ECCV 2018, 2018

Matrix-normal models for fMRI analysis.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2018

Bridging the Gap between HPC and Big Data frameworks.
Proc. VLDB Endow., 2017

On Sampling from Massive Graph Streams.
Proc. VLDB Endow., 2017

Graphlet decomposition: framework, algorithms, and applications.
Knowl. Inf. Syst., 2017

Segmenting Brain Tumors with Symmetry.
CoRR, 2017

Representation Learning in Large Attributed Graphs.
CoRR, 2017

A Framework for Generalizing Graph-based Representation Learning Methods.
CoRR, 2017

High-Performance Incremental SVM Learning on Intel<sup>®</sup> Xeon Phi™ Processors.
Proceedings of the High Performance Computing - 32nd International Conference, 2017

Edge Role Discovery via Higher-Order Structures.
Proceedings of the Advances in Knowledge Discovery and Data Mining, 2017

A semi-supervised method for multi-subject FMRI functional alignment.
Proceedings of the 2017 IEEE International Conference on Acoustics, 2017

A Formal Approach to Modeling the Cost of Cognitive Control.
Proceedings of the 39th Annual Meeting of the Cognitive Science Society, 2017

A Higher-Order Latent Space Network Model.
Proceedings of the Workshops of the The Thirty-First AAAI Conference on Artificial Intelligence, 2017

A Searchlight Factor Model Approach for Locating Shared Information in Multi-Subject fMRI Analysis.
CoRR, 2016

A Convolutional Autoencoder for Multi-Subject fMRI Data Aggregation.
CoRR, 2016

Revisiting Role Discovery in Networks: From Node to Edge Roles.
CoRR, 2016

Exact and Estimation of Local Edge-centric Graphlet Counts.
Proceedings of the 5th International Workshop on Big Data, 2016

GraphPad: Optimized Graph Primitives for Parallel and Distributed Platforms.
Proceedings of the 2016 IEEE International Parallel and Distributed Processing Symposium, 2016

GraphIn: An Online High Performance Incremental Graph Processing Framework.
Proceedings of the Euro-Par 2016: Parallel Processing, 2016

Controlled vs. Automatic Processing: A Graph-Theoretic Approach to the Analysis of Serial vs. Parallel Processing in Neural Network Architectures.
Proceedings of the 38th Annual Meeting of the Cognitive Science Society, 2016

Real-time full correlation matrix analysis of fMRI data.
Proceedings of the 2016 IEEE International Conference on Big Data, 2016

Enabling factor analysis on thousand-subject neuroimaging datasets.
Proceedings of the 2016 IEEE International Conference on Big Data, 2016

Estimation of local subgraph counts.
Proceedings of the 2016 IEEE International Conference on Big Data, 2016

Full correlation matrix analysis of fMRI data on Intel® Xeon Phi™ coprocessors.
Proceedings of the International Conference for High Performance Computing, 2015

Benchmarking graph-processing platforms: a vision.
Proceedings of the ACM/SPEC International Conference on Performance Engineering, 2014

How Well Do Graph-Processing Platforms Perform? An Empirical Performance Evaluation and Analysis.
Proceedings of the 2014 IEEE 28th International Parallel and Distributed Processing Symposium, 2014

GraphBuilder: scalable graph ETL framework.
Proceedings of the First International Workshop on Graph Data Management Experiences and Systems, 2013

Towards Machine Learning-Based Auto-tuning of MapReduce.
Proceedings of the 2013 IEEE 21st International Symposium on Modelling, 2013

Gunther: Search-Based Auto-Tuning of MapReduce.
Proceedings of the Euro-Par 2013 Parallel Processing, 2013

A survey of inter-vehicle communication protocols and their applications.
IEEE Commun. Surv. Tutorials, 2009

Reliable Neighborcast.
IEEE Trans. Veh. Technol., 2007

Coordinated interaction using reliable broadcast in mobile wireless networks.
Comput. Networks, 2007

Reliable Collaborative Decision Making in Mobile Ad Hoc Networks.
Proceedings of the Management of Multimedia Networks and Services: 7th IFIP/IEEE International Conference, 2004

NUFACTS: A tool for the analysis of nuclear development policies.
Proceedings of the 9th conference on Winter simulation, 1977