Syamantak Kumar

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20242026

most citedOja's Algorithm for Streaming Sparse PCA

1 citations · 1 across the 10 of their papers we have counts for

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math.NA2024

Black-Box $k$ -to- $1$ -PCA Reductions: Theory and Applications

Arun Jambulapati, Syamantak Kumar, Jerry Li +3

The $k$ -principal component analysis ( $k$ -PCA) problem is a fundamental algorithmic primitive that is widely-used in data analysis and dimensionality reduction applications. In sta…

math.ST2024★ 1 cited

Oja's Algorithm for Streaming Sparse PCA

Syamantak Kumar, Purnamrita Sarkar

Oja's algorithm for Streaming Principal Component Analysis (PCA) for $n$ data-points in a $d$ dimensional space achieves the same sin-squared error $O (r_{eff} / n)$ as the o…

math.ST2024

Nonparametric Evaluation of Noisy ICA Solutions

Syamantak Kumar, Purnamrita Sarkar, Peter Bickel +1

Independent Component Analysis (ICA) was introduced in the 1980's as a model for Blind Source Separation (BSS), which refers to the process of recovering the sources underlying a m…

Black-Box k-to-1-PCA Reductions: Theory and Applications

Oja's Algorithm for Streaming Sparse PCA

Nonparametric Evaluation of Noisy ICA Solutions

Black-Box $k$ -to- $1$ -PCA Reductions: Theory and Applications