Theodore L. Willke

Orcid: 0000-0001-9825-513X

Affiliations:
  • Intel Labs, OR, USA


According to our database1, Theodore L. Willke authored at least 72 papers between 1977 and 2024.

Collaborative distances:

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Dataset
Other 

Links

Online presence:

On csauthors.net:

Bibliography

2024
Memory-Augmented Graph Neural Networks: A Brain-Inspired Review.
IEEE Trans. Artif. Intell., May, 2024

LeanVec: Searching vectors faster by making them fit.
Trans. Mach. Learn. Res., 2024

GleanVec: Accelerating vector search with minimalist nonlinear dimensionality reduction.
CoRR, 2024

A structure-aware framework for learning device placements on computation graphs.
CoRR, 2024

MPIrigen: MPI Code Generation through Domain-Specific Language Models.
CoRR, 2024

Locally-Adaptive Quantization for Streaming Vector Search.
CoRR, 2024

The Landscape and Challenges of HPC Research and LLMs.
CoRR, 2024

Structure Guided Prompt: Instructing Large Language Model in Multi-Step Reasoning by Exploring Graph Structure of the Text.
Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing, 2024

2023
Similarity search in the blink of an eye with compressed indices.
Proc. VLDB Endow., 2023

LeanVec: Search your vectors faster by making them fit.
CoRR, 2023

Domain-Specific Code Language Models: Unraveling the Potential for HPC Codes and Tasks.
CoRR, 2023

Leveraging Reinforcement Learning and Large Language Models for Code Optimization.
CoRR, 2023

Scope is all you need: Transforming LLMs for HPC Code.
CoRR, 2023

Augmenting Recurrent Graph Neural Networks with a Cache.
Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023

2022
Role-Based Graph Embeddings.
IEEE Trans. Knowl. Data Eng., 2022

Memory in humans and deep language models: Linking hypotheses for model augmentation.
CoRR, 2022

Memory-Augmented Graph Neural Networks: A Neuroscience Perspective.
CoRR, 2022

Toward a Geometrical Understanding of Self-supervised Contrastive Learning.
CoRR, 2022

End-to-end Mapping in Heterogeneous Systems Using Graph Representation Learning.
CoRR, 2022

2021
Deep graph similarity learning: a survey.
Data Min. Knowl. Discov., 2021

Slower is Better: Revisiting the Forgetting Mechanism in LSTM for Slower Information Decay.
CoRR, 2021

A Distributed Graph-Theoretic Framework for Automatic Parallelization in Multi-core Systems.
Proceedings of the Fourth Conference on Machine Learning and Systems, 2021

Learning Code Representations Using Multifractal-based Graph Networks.
Proceedings of the 2021 IEEE International Conference on Big Data (Big Data), 2021

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

A Vertex Cut based Framework for Load Balancing and Parallelism Optimization in Multi-core Systems.
CoRR, 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

Approximating Stacked and Bidirectional Recurrent Architectures with the Delayed Recurrent Neural Network.
Proceedings of the 37th International Conference on Machine Learning, 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

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

2018
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

2017
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

2016
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 (IEEE BigData 2016), 2016

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

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

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

2014
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

2013
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

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

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

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

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

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


  Loading...