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Pritish Kamath

Topic trends: 32,543 papers · similarity ≥ 0.4 · year ≥ 2024 · Data sourced from Semantic Scholar

34,598 papers | Abstracts: 31,650 (91.5%) | Citations: 34,598 (100.0%) | arXiv: 26,074 (75.4%)

Built: Feb 14, 2026, 10:11 PM AMS

14

papers

117

total citations

papers (14)

On the Power of Differentiable Learning versus PAC and SQ Learning

NEURIPS 2021arXiv

How Private are DP-SGD Implementations?

Understanding the Eluder Dimension

NEURIPS 2022arXiv

User-Level Differential Privacy With Few Examples Per User

NEURIPS 2023arXiv

Scaling Embedding Layers in Language Models

NEURIPS 2025arXiv

Crosslingual Capabilities and Knowledge Barriers in Multilingual Large Language Models

Sparsity-Preserving Differentially Private Training of Large Embedding Models

NEURIPS 2023arXiv

Anonymized Histograms in Intermediate Privacy Models

NEURIPS 2022arXiv

On Computing Pairwise Statistics with Local Differential Privacy

NEURIPS 2023arXiv

Empirical Privacy Variance

URANIA: Differentially Private Insights into AI Use

Individualized Privacy Accounting via Subsampling with Applications in Combinatorial Optimization

Private Isotonic Regression

NEURIPS 2022arXiv

Optimal Unbiased Randomizers for Regression with Label Differential Privacy