Justin Whitehouse

According to our database1, Justin Whitehouse authored at least 12 papers between 2018 and 2024.

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

Timeline

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Links

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Bibliography

2024
Orthogonal Causal Calibration.
CoRR, 2024

Multi-Armed Bandits with Network Interference.
CoRR, 2024

2023
Improved Self-Normalized Concentration in Hilbert Spaces: Sublinear Regret for GP-UCB.
CoRR, 2023

On the Sublinear Regret of GP-UCB.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Adaptive Principal Component Regression with Applications to Panel Data.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Fully-Adaptive Composition in Differential Privacy.
Proceedings of the International Conference on Machine Learning, 2023

2022
The case for phase-aware scheduling of parallelizable jobs.
Perform. Evaluation, 2022

Brownian Noise Reduction: Maximizing Privacy Subject to Accuracy Constraints.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

2020
Optimal Resource Allocation for Elastic and Inelastic Jobs.
Proceedings of the SPAA '20: 32nd ACM Symposium on Parallelism in Algorithms and Architectures, 2020

2019
Bringing Engineering Rigor to Deep Learning.
ACM SIGOPS Oper. Syst. Rev., 2019

2018
Formal Security Analysis of Neural Networks using Symbolic Intervals.
Proceedings of the 27th USENIX Security Symposium, 2018

Efficient Formal Safety Analysis of Neural Networks.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018


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