Gregory Dexter

Orcid: 0009-0002-9422-818X

Affiliations:
  • Purdue University, Department of Computer Science, West Lafayette, IN, USA


According to our database1, Gregory Dexter authored at least 18 papers between 2019 and 2025.

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Bibliography

2025
Efficient AI in Practice: Training and Deployment of Efficient LLMs for Industry Applications.
CoRR, February, 2025

LLM Query Scheduling with Prefix Reuse and Latency Constraints.
CoRR, February, 2025

Stochastic Rounding Implicitly Regularizes Tall-and-Thin Matrices.
SIAM J. Matrix Anal. Appl., 2025

Efficient Algorithms for Leveraging LLMs for Generative and Predictive Recommender Systems.
Proceedings of the Companion Proceedings of the ACM on Web Conference 2025, 2025

2024
Sublinear Time Eigenvalue Approximation via Random Sampling.
Algorithmica, June, 2024

MaSk-LMM: A Matrix Sketching Framework for Linear Mixed Models in Association Studies.
Proceedings of the Research in Computational Molecular Biology, 2024

The Space Complexity of Approximating Logistic Loss.
Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

Universal Matrix Sparsifiers and Fast Deterministic Algorithms for Linear Algebra.
Proceedings of the 15th Innovations in Theoretical Computer Science Conference, 2024

A Precise Characterization of SGD Stability Using Loss Surface Geometry.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

2023
Feature Space Sketching for Logistic Regression.
CoRR, 2023

Sketching Algorithms for Sparse Dictionary Learning: PTAS and Turnstile Streaming.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

2022
Faster Randomized Interior Point Methods for Tall/Wide Linear Programs.
J. Mach. Learn. Res., 2022

On the Convergence of Inexact Predictor-Corrector Methods for Linear Programming.
Proceedings of the International Conference on Machine Learning, 2022

2021
Inverse Reinforcement Learning in the Continuous Setting with Formal Guarantees.
CoRR, 2021

Inverse Reinforcement Learning in a Continuous State Space with Formal Guarantees.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

2020
Randomized Linear Algebra Approaches to Estimate the von Neumann Entropy of Density Matrices.
IEEE Trans. Inf. Theory, 2020

2019
An Adversorial Approach to Enable Re-Use of Machine Learning Models and Collaborative Research Efforts Using Synthetic Unstructured Free-Text Medical Data.
Proceedings of the MEDINFO 2019: Health and Wellbeing e-Networks for All, 2019

Comparison of Free-Text Synthetic Data Produced by Three Generative Adversarial Networks for Collaborative Health Data Analytics.
Proceedings of the AMIA 2019, 2019


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