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2020 – today
- 2024
[j3]Mike Heddes, Igor Nunes, Tony Givargis, Alexandru Nicolau, Alexander V. Veidenbaum:
Hyperdimensional computing: a framework for stochastic computation and symbolic AI. J. Big Data 11(1): 145 (2024)- [j2]Mike Heddes
, Igor Nunes, Tony Givargis, Alex Nicolau:
Convolution and Cross-Correlation of Count Sketches Enables Fast Cardinality Estimation of Multi-Join Queries. Proc. ACM Manag. Data 2(3): 129 (2024) - [c6]Pere Vergés, Igor Nunes, Mike Heddes, Tony Givargis, Alexandru Nicolau:
Molecular Classification Using Hyperdimensional Graph Classification. IJCNN 2024: 1-8 - [i9]Mike Heddes, Narayan Srinivasa, Tony Givargis, Alexandru Nicolau:
Always-Sparse Training by Growing Connections with Guided Stochastic Exploration. CoRR abs/2401.06898 (2024) - [i8]Mike Heddes, Igor Nunes, Tony Givargis, Alex Nicolau:
Convolution and Cross-Correlation of Count Sketches Enables Fast Cardinality Estimation of Multi-Join Queries. CoRR abs/2402.15953 (2024) - [i7]Pere Vergés, Igor Nunes, Mike Heddes, Tony Givargis, Alexandru Nicolau:
Molecular Classification Using Hyperdimensional Graph Classification. CoRR abs/2403.12307 (2024) - 2023
- [j1]Mike Heddes, Igor Nunes, Pere Vergés, Denis Kleyko, Danny Abraham, Tony Givargis, Alexandru Nicolau, Alexander V. Veidenbaum:
Torchhd: An Open Source Python Library to Support Research on Hyperdimensional Computing and Vector Symbolic Architectures. J. Mach. Learn. Res. 24: 255:1-255:10 (2023) - [c5]Igor Nunes, Mike Heddes, Tony Givargis, Alexandru Nicolau:
An Extension to Basis-Hypervectors for Learning from Circular Data in Hyperdimensional Computing. DAC 2023: 1-6 - [c4]Igor Nunes, Mike Heddes, Pere Vergés, Danny Abraham, Alexander V. Veidenbaum, Alex Nicolau, Tony Givargis:
DotHash: Estimating Set Similarity Metrics for Link Prediction and Document Deduplication. KDD 2023: 1758-1769 - [c3]Pere Vergés, Igor Nunes, Mike Heddes, Tony Givargis, Alexandru Nicolau:
Accelerating Permute and N-Gram Operations for Hyperdimensional Learning in Embedded Systems. RTCSA 2023: 253-260 - [i6]Pere Vergés, Mike Heddes, Igor Nunes, Tony Givargis, Alexandru Nicolau:
HDCC: A Hyperdimensional Computing compiler for classification on embedded systems and high-performance computing. CoRR abs/2304.12398 (2023) - [i5]Igor Nunes, Mike Heddes, Pere Vergés, Danny Abraham, Alexander V. Veidenbaum, Alexandru Nicolau, Tony Givargis:
DotHash: Estimating Set Similarity Metrics for Link Prediction and Document Deduplication. CoRR abs/2305.17310 (2023) - 2022
- [c2]Mike Heddes, Igor Nunes, Tony Givargis, Alexandru Nicolau, Alexander V. Veidenbaum:
Hyperdimensional hashing: a robust and efficient dynamic hash table. DAC 2022: 907-912 - [c1]Igor Nunes, Mike Heddes, Tony Givargis, Alexandru Nicolau, Alexander V. Veidenbaum:
GraphHD: Efficient graph classification using hyperdimensional computing. DATE 2022: 1485-1490 - [i4]Igor Nunes, Mike Heddes, Tony Givargis, Alexandru Nicolau, Alexander V. Veidenbaum:
GraphHD: Efficient graph classification using hyperdimensional computing. CoRR abs/2205.07826 (2022) - [i3]Mike Heddes, Igor Nunes, Tony Givargis, Alexandru Nicolau, Alexander V. Veidenbaum:
Hyperdimensional Hashing: A Robust and Efficient Dynamic Hash Table. CoRR abs/2205.07850 (2022) - [i2]Igor Nunes, Mike Heddes, Tony Givargis, Alexandru Nicolau:
An Extension to Basis-Hypervectors for Learning from Circular Data in Hyperdimensional Computing. CoRR abs/2205.07920 (2022) - [i1]Mike Heddes, Igor Nunes, Pere Vergés, Dheyay Desai, Tony Givargis, Alexandru Nicolau:
Torchhd: An Open-Source Python Library to Support Hyperdimensional Computing Research. CoRR abs/2205.09208 (2022)
Coauthor Index
aka: Alex Nicolau
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