Benoit Steiner

Orcid: 0000-0002-5767-4976

According to our database1, Benoit Steiner authored at least 23 papers between 2016 and 2023.

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Bibliography

2023
Studying Large Language Model Generalization with Influence Functions.
CoRR, 2023

Measuring Faithfulness in Chain-of-Thought Reasoning.
CoRR, 2023

MODeL: Memory Optimizations for Deep Learning.
Proceedings of the International Conference on Machine Learning, 2023

Learning Compiler Pass Orders using Coreset and Normalized Value Prediction.
Proceedings of the International Conference on Machine Learning, 2023

Searching Large Neighborhoods for Integer Linear Programs with Contrastive Learning.
Proceedings of the International Conference on Machine Learning, 2023

SurCo: Learning Linear SURrogates for COmbinatorial Nonlinear Optimization Problems.
Proceedings of the International Conference on Machine Learning, 2023

Local Branching Relaxation Heuristics for Integer Linear Programs.
Proceedings of the Integration of Constraint Programming, Artificial Intelligence, and Operations Research, 2023

2022
OLLA: Decreasing the Memory Usage of Neural Networks by Optimizing the Lifetime and Location of Arrays.
CoRR, 2022

LoopStack: a Lightweight Tensor Algebra Compiler Stack.
CoRR, 2022

A graph neural network-based performance model for deep learning applications.
Proceedings of the MAPS@PLDI 2022: 6th ACM SIGPLAN International Symposium on Machine Programming, 2022

Flashlight: Enabling Innovation in Tools for Machine Learning.
Proceedings of the International Conference on Machine Learning, 2022

CompilerGym: Robust, Performant Compiler Optimization Environments for AI Research.
Proceedings of the IEEE/ACM International Symposium on Code Generation and Optimization, 2022

2021
Using Graph Neural Networks to model the performance of Deep Neural Networks.
CoRR, 2021

Learning Space Partitions for Path Planning.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Value Learning for Throughput Optimization of Deep Learning Workloads.
Proceedings of the Fourth Conference on Machine Learning and Systems, 2021

2020
Value Function Based Performance Optimization of Deep Learning Workloads.
CoRR, 2020

2019
Learning to optimize halide with tree search and random programs.
ACM Trans. Graph., 2019

PyTorch: An Imperative Style, High-Performance Deep Learning Library.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

2018
A Hierarchical Model for Device Placement.
Proceedings of the 6th International Conference on Learning Representations, 2018

2017
Device Placement Optimization with Reinforcement Learning.
Proceedings of the 34th International Conference on Machine Learning, 2017

2016
TensorFlow: A system for large-scale machine learning.
CoRR, 2016

TensorFlow: Large-Scale Machine Learning on Heterogeneous Distributed Systems.
CoRR, 2016



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