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Anant Gupta

5 accepted papers

2026

Avoid Catastrophic Forgetting with Rank-1 Fisher from Diffusion Models

ICLR 2026poster

Catastrophic forgetting remains a central obstacle for continual learning in neural models. Popular approaches---replay and elastic weight consolidation (EWC)---have limitations: replay requires a strong generator and is prone to distributional drift, while EWC implicitly assumes a shared optimum ac…

Cited by 4SourceScholar
2024

Leveraging Contextual Information for Effective Entity Salience Detection

NAACL 2024findings

In text documents such as news articles, the content and key events usually revolve around a subset of all the entities mentioned in a document. These entities, often deemed as salient entities, provide useful cues of the aboutness of a document to a reader. Identifying the salience of entities was…

Cited by 2SourcePDFScholar
2020

Closing the convergence gap of SGD without replacement

ICML 2020poster

Stochastic gradient descent without replacement sampling is widely used in practice for model training. However, the vast majority of SGD analyses assumes data is sampled with replacement, and when the function minimized is strongly convex, an $\mathcal{O}\left(\frac{1}{T}\right)$ rate can be establ…