Mike Heddes

According to our database, Mike Heddes authored at least 12 papers between 2022 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Hyperdimensional computing: a framework for stochastic computation and symbolic AI.

Mike Heddes, Igor Nunes, Tony Givargis, Alexandru Nicolau, Alexander V. Veidenbaum

J. Big Data, December, 2024

Convolution and Cross-Correlation of Count Sketches Enables Fast Cardinality Estimation of Multi-Join Queries.

Mike Heddes, Igor Nunes, Tony Givargis, Alex Nicolau

Proc. ACM Manag. Data, 2024

Always-Sparse Training by Growing Connections with Guided Stochastic Exploration.

Mike Heddes, Narayan Srinivasa, Tony Givargis, Alexandru Nicolau

CoRR, 2024

Molecular Classification Using Hyperdimensional Graph Classification.

Pere Vergés, Igor Nunes, Mike Heddes, Tony Givargis, Alexandru Nicolau

Proceedings of the International Joint Conference on Neural Networks, 2024

2023

Torchhd: An Open Source Python Library to Support Research on Hyperdimensional Computing and Vector Symbolic Architectures.

Mike Heddes, Igor Nunes, Pere Vergés, Denis Kleyko, Danny Abraham, Tony Givargis, Alexandru Nicolau, Alexander V. Veidenbaum

J. Mach. Learn. Res., 2023

HDCC: A Hyperdimensional Computing compiler for classification on embedded systems and high-performance computing.

Pere Vergés, Mike Heddes, Igor Nunes, Tony Givargis, Alexandru Nicolau

CoRR, 2023

Accelerating Permute and N-Gram Operations for Hyperdimensional Learning in Embedded Systems.

Pere Vergés, Igor Nunes, Mike Heddes, Tony Givargis, Alexandru Nicolau

Proceedings of the 29th IEEE International Conference on Embedded and Real-Time Computing Systems and Applications, 2023

DotHash: Estimating Set Similarity Metrics for Link Prediction and Document Deduplication.

Igor Nunes, Mike Heddes, Pere Vergés, Danny Abraham, Alexander V. Veidenbaum, Alex Nicolau, Tony Givargis

Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023

An Extension to Basis-Hypervectors for Learning from Circular Data in Hyperdimensional Computing.

Igor Nunes, Mike Heddes, Tony Givargis, Alexandru Nicolau

Proceedings of the 60th ACM/IEEE Design Automation Conference, 2023

2022

Torchhd: An Open-Source Python Library to Support Hyperdimensional Computing Research.

Mike Heddes, Igor Nunes, Pere Vergés, Dheyay Desai, Tony Givargis, Alexandru Nicolau

CoRR, 2022

GraphHD: Efficient graph classification using hyperdimensional computing.

Igor Nunes, Mike Heddes, Tony Givargis, Alexandru Nicolau, Alexander V. Veidenbaum

Proceedings of the 2022 Design, Automation & Test in Europe Conference & Exhibition, 2022

Hyperdimensional hashing: a robust and efficient dynamic hash table.

Mike Heddes, Igor Nunes, Tony Givargis, Alexandru Nicolau, Alexander V. Veidenbaum

Proceedings of the DAC '22: 59th ACM/IEEE Design Automation Conference, San Francisco, California, USA, July 10, 2022