David Tuckey

According to our database1, David Tuckey authored at least 11 papers between 2019 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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PhD thesis 
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Links

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Bibliography

2024
DP-DyLoRA: Fine-Tuning Transformer-Based Models On-Device under Differentially Private Federated Learning using Dynamic Low-Rank Adaptation.
CoRR, 2024

2023
FastRAT: Fast and Efficient Cross-lingual Text-to-SQL Semantic Parsing.
Proceedings of the 13th International Joint Conference on Natural Language Processing and the 3rd Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics, 2023

Consistency Based Unsupervised Self-Training for ASR Personalisation.
Proceedings of the IEEE Automatic Speech Recognition and Understanding Workshop, 2023

2022
Detect, Understand, Act: A Neuro-symbolic Hierarchical Reinforcement Learning Framework.
Mach. Learn., 2022

Tunable Quantum Neural Networks in the QPAC-Learning Framework.
Proceedings of the Proceedings 19th International Conference on Quantum Physics and Logic, 2022

Detect, Understand, Act: A Neuro-Symbolic Hierarchical Reinforcement Learning Framework (Extended Abstract).
Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence, 2022

A Semantics For Probabilistic Answer Set Programs With Incomplete Stochastic Knowledge.
Proceedings of the International Conference on Logic Programming 2022 Workshops co-located with the 38th International Conference on Logic Programming (ICLP 2022), Haifa, Israel, July 31st, 2022

2021
PASOCS: A Parallel Approximate Solver for Probabilistic Logic Programs under the Credal Semantics.
CoRR, 2021

2020
A general framework for scientifically inspired explanations in AI.
CoRR, 2020

Towards Structure Learning under the Credal Semantics.
Proceedings of the International Conference on Logic Programming 2020 Workshop Proceedings co-located with 36th International Conference on Logic Programming (ICLP 2020), 2020

2019
Saliency Maps Generation for Automatic Text Summarization.
CoRR, 2019


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