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Arvind V. Mahankali

3 accepted papers

2024

One Step of Gradient Descent is Provably the Optimal In-Context Learner with One Layer of Linear Self-Attention

ICLR 2024poster

Recent works have empirically analyzed in-context learning and shown that transformers trained on synthetic linear regression tasks can learn to implement ridge regression, which is the Bayes-optimal predictor, given sufficient capacity (Akyurek et al., 2023), while one-layer transformers with linea…

Cited by 112SourcePDFScholar
2021

Linear and Kernel Classification in the Streaming Model: Improved Bounds for Heavy Hitters

NeurIPS 2021poster

We study linear and kernel classification in the streaming model. For linear classification, we improve upon the algorithm of (Tai, et al. 2018), which solves the $\ell_1$ point query problem on the optimal weight vector $w_* \in \mathbb{R}^d$ in sublinear space. We first give an algorithm solving t…

Cited by 3SourcePDFScholar
2021

Streaming and Distributed Algorithms for Robust Column Subset Selection

ICML 2021spotlight

We give the first single-pass streaming algorithm for Column Subset Selection with respect to the entrywise $\ell_p$-norm with $1 \leq p < 2$. We study the $\ell_p$ norm loss since it is often considered more robust to noise than the standard Frobenius norm. Given an input matrix $A \in \mathbb{R}^{…