Hunter Lang

According to our database1, Hunter Lang authored at least 20 papers between 2017 and 2024.

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

Timeline

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Links

On csauthors.net:

Bibliography

2024
Learning to Decode Collaboratively with Multiple Language Models.
CoRR, 2024

2023
Who Should Predict? Exact Algorithms For Learning to Defer to Humans.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

TabLLM: Few-shot Classification of Tabular Data with Large Language Models.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

2022
Large Language Models are Zero-Shot Clinical Information Extractors.
CoRR, 2022

Training Subset Selection for Weak Supervision.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Co-training Improves Prompt-based Learning for Large Language Models.
Proceedings of the International Conference on Machine Learning, 2022

Large language models are few-shot clinical information extractors.
Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing, 2022

Leveraging Time Irreversibility with Order-Contrastive Pre-training.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

2021
Combining Probabilistic Logic and Deep Learning for Self-Supervised Learning.
Proceedings of the Neuro-Symbolic Artificial Intelligence: The State of the Art, 2021

Combining Probabilistic Logic and Deep Learning for Self-Supervised Learning.
CoRR, 2021

Graph Cuts Always Find a Global Optimum for Potts Models (With a Catch).
Proceedings of the 38th International Conference on Machine Learning, 2021

Beyond Perturbation Stability: LP Recovery Guarantees for MAP Inference on Noisy Stable Instances.
Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

Self-Supervised Self-Supervision by Combining Deep Learning and Probabilistic Logic.
Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020
Graph cuts always find a global optimum (with a catch).
CoRR, 2020

Statistical Adaptive Stochastic Gradient Methods.
CoRR, 2020

2019
Using Statistics to Automate Stochastic Optimization.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Understanding the Role of Momentum in Stochastic Gradient Methods.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Block Stability for MAP Inference.
Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

2018
Optimality of Approximate Inference Algorithms on Stable Instances.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2018

2017
Alpha-expansion is Exact on Stable Instances.
CoRR, 2017


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