Yatin Dandi

According to our database1, Yatin Dandi authored at least 18 papers between 2020 and 2024.

Collaborative distances:

Timeline

2020
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2022
2023
2024
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Bibliography

2024
A Random Matrix Theory Perspective on the Spectrum of Learned Features and Asymptotic Generalization Capabilities.
CoRR, 2024

Online Learning and Information Exponents: On The Importance of Batch size, and Time/Complexity Tradeoffs.
CoRR, 2024

Fundamental limits of weak learnability in high-dimensional multi-index models.
CoRR, 2024

Repetita Iuvant: Data Repetition Allows SGD to Learn High-Dimensional Multi-Index Functions.
CoRR, 2024

The Benefits of Reusing Batches for Gradient Descent in Two-Layer Networks: Breaking the Curse of Information and Leap Exponents.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

Asymptotics of feature learning in two-layer networks after one gradient-step.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

Online Learning and Information Exponents: The Importance of Batch size & Time/Complexity Tradeoffs.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

2023
A Gentle Introduction to Gradient-Based Optimization and Variational Inequalities for Machine Learning.
CoRR, 2023

Sampling with flows, diffusion and autoregressive neural networks: A spin-glass perspective.
CoRR, 2023

Learning Two-Layer Neural Networks, One (Giant) Step at a Time.
CoRR, 2023

Universality laws for Gaussian mixtures in generalized linear models.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

2022
Data-heterogeneity-aware Mixing for Decentralized Learning.
CoRR, 2022

Implicit Gradient Alignment in Distributed and Federated Learning.
Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021
NeurInt : Learning to Interpolate through Neural ODEs.
CoRR, 2021

Understanding Layer-wise Contributions in Deep Neural Networks through Spectral Analysis.
CoRR, 2021

Generalized Adversarially Learned Inference.
Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020
Jointly Trained Image and Video Generation using Residual Vectors.
Proceedings of the IEEE Winter Conference on Applications of Computer Vision, 2020

Model-Agnostic Learning to Meta-Learn.
Proceedings of the NeurIPS 2020 Workshop on Pre-registration in Machine Learning, 2020


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