Noah Amsel

Orcid: 0000-0001-9241-8284

According to our database1, Noah Amsel authored at least 19 papers between 2018 and 2025.

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

Timeline

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PhD thesis 
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Links

On csauthors.net:

Bibliography

2025
Query Efficient Structured Matrix Learning.
CoRR, July, 2025

Quasi-optimal hierarchically semi-separable matrix approximation.
CoRR, May, 2025

The Polar Express: Optimal Matrix Sign Methods and Their Application to the Muon Algorithm.
CoRR, May, 2025

Compositional Reasoning with Transformers, RNNs, and Chain of Thought.
CoRR, March, 2025

Quality over Quantity in Attention Layers: When Adding More Heads Hurts.
Proceedings of the Thirteenth International Conference on Learning Representations, 2025

2024
On the Benefits of Rank in Attention Layers.
CoRR, 2024

Fixed-sparsity matrix approximation from matrix-vector products.
CoRR, 2024

Nearly Optimal Approximation of Matrix Functions by the Lanczos Method.
Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

2023
Near-Optimality Guarantees for Approximating Rational Matrix Functions by the Lanczos Method.
CoRR, 2023

2022
A Quantitative Theory of Bottleneck Structures for Data Networks.
CoRR, 2022

2021
Spectral Neighbor Joining for Reconstruction of Latent Tree Models.
SIAM J. Math. Data Sci., 2021

Spectral Top-Down Recovery of Latent Tree Models.
CoRR, 2021

Designing data center networks using bottleneck structures.
Proceedings of the ACM SIGCOMM 2021 Conference, Virtual Event, USA, August 23-27, 2021., 2021

Boundary Integral Solver Approaches for Particle Accelerator Simulation Problems and Deployment on NERSC Hardware.
Proceedings of the 2021 IEEE High Performance Extreme Computing Conference, 2021

2020
Spectral neighbor joining for reconstruction of latent tree models.
CoRR, 2020

Computing Bottleneck Structures at Scale for High-Precision Network Performance Analysis.
Proceedings of the IEEE/ACM Innovating the Network for Data-Intensive Science, 2020

2019
Finding Syntactic Representations in Neural Stacks.
CoRR, 2019

Finding Hierarchical Structure in Neural Stacks Using Unsupervised Parsing.
Proceedings of the 2019 ACL Workshop BlackboxNLP: Analyzing and Interpreting Neural Networks for NLP, 2019

2018
Context-Free Transductions with Neural Stacks.
Proceedings of the Workshop: Analyzing and Interpreting Neural Networks for NLP, 2018


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