Gal Kaplun

According to our database, Gal Kaplun authored at least 11 papers between 2019 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

Beyond Implicit Bias: The Insignificance of SGD Noise in Online Learning.

Nikhil Vyas, Depen Morwani, Rosie Zhao, Gal Kaplun, Sham M. Kakade, Boaz Barak

Proceedings of the Forty-first International Conference on Machine Learning, 2024

2023

Corgi^2: A Hybrid Offline-Online Approach To Storage-Aware Data Shuffling For SGD.

Etay Livne, Gal Kaplun, Eran Malach, Shai Shalev-Schwatz

CoRR, 2023

SubTuning: Efficient Finetuning for Multi-Task Learning.

Gal Kaplun, Andrey Gurevich, Tal Swisa, Mazor David, Shai Shalev-Shwartz, Eran Malach

CoRR, 2023

Deconstructing Distributions: A Pointwise Framework of Learning.

Gal Kaplun, Nikhil Ghosh, Saurabh Garg, Boaz Barak, Preetum Nakkiran

Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022

Knowledge Distillation: Bad Models Can Be Good Role Models.

Gal Kaplun, Eran Malach, Preetum Nakkiran, Shai Shalev-Shwartz

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

2021

For Manifold Learning, Deep Neural Networks can be Locality Sensitive Hash Functions.

Nishanth Dikkala, Gal Kaplun, Rina Panigrahy

CoRR, 2021

For self-supervised learning, Rationality implies generalization, provably.

Yamini Bansal, Gal Kaplun, Boaz Barak

Proceedings of the 9th International Conference on Learning Representations, 2021

2020

Robustness from Simple Classifiers.

Sharon Qian, Dimitris Kalimeris, Gal Kaplun, Yaron Singer

CoRR, 2020

Deep Double Descent: Where Bigger Models and More Data Hurt.

Preetum Nakkiran, Gal Kaplun, Yamini Bansal, Tristan Yang, Boaz Barak, Ilya Sutskever

Proceedings of the 8th International Conference on Learning Representations, 2020

2019

SGD on Neural Networks Learns Functions of Increasing Complexity.

Preetum Nakkiran, Gal Kaplun, Dimitris Kalimeris, Tristan Yang, Benjamin L. Edelman, Fred Zhang, Boaz Barak

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Robust Influence Maximization for Hyperparametric Models.

Dimitris Kalimeris, Gal Kaplun, Yaron Singer

Proceedings of the 36th International Conference on Machine Learning, 2019