Nikunj Saunshi

According to our database1, Nikunj Saunshi authored at least 16 papers between 2018 and 2024.

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Bibliography

2024
Efficient Stagewise Pretraining via Progressive Subnetworks.
CoRR, 2024

2023
Task-Specific Skill Localization in Fine-tuned Language Models.
Proceedings of the International Conference on Machine Learning, 2023

Understanding Influence Functions and Datamodels via Harmonic Analysis.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

Reasoning in Large Language Models Through Symbolic Math Word Problems.
Proceedings of the Findings of the Association for Computational Linguistics: ACL 2023, 2023

2022
New Definitions and Evaluations for Saliency Methods: Staying Intrinsic, Complete and Sound.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Understanding Contrastive Learning Requires Incorporating Inductive Biases.
Proceedings of the International Conference on Machine Learning, 2022

On Predicting Generalization using GANs.
Proceedings of the Tenth International Conference on Learning Representations, 2022

2021
Predicting What You Already Know Helps: Provable Self-Supervised Learning.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

A Representation Learning Perspective on the Importance of Train-Validation Splitting in Meta-Learning.
Proceedings of the 38th International Conference on Machine Learning, 2021

A Mathematical Exploration of Why Language Models Help Solve Downstream Tasks.
Proceedings of the 9th International Conference on Learning Representations, 2021

2020
A Sample Complexity Separation between Non-Convex and Convex Meta-Learning.
Proceedings of the 37th International Conference on Machine Learning, 2020

Provable Representation Learning for Imitation Learning via Bi-level Optimization.
Proceedings of the 37th International Conference on Machine Learning, 2020

2019
A Theoretical Analysis of Contrastive Unsupervised Representation Learning.
Proceedings of the 36th International Conference on Machine Learning, 2019

2018
A Large Self-Annotated Corpus for Sarcasm.
Proceedings of the Eleventh International Conference on Language Resources and Evaluation, 2018

A Compressed Sensing View of Unsupervised Text Embeddings, Bag-of-n-Grams, and LSTMs.
Proceedings of the 6th International Conference on Learning Representations, 2018

A La Carte Embedding: Cheap but Effective Induction of Semantic Feature Vectors.
Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics, 2018


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