← Authors

Tamas Sarlos

20 papers · 2013–2024 · 6 conferences · across top CS/AI conferences

Achievements

🐝 Cross-Pollinator (4) 🌍 Conference Polyglot (6) 🌈 Renaissance Researcher (5) πŸŒ‰ Interdisciplinary Bridge πŸ—ΊοΈ Taxonomy Completionist (11) 🧭 Keyword Pioneer 🐣 Hot Topic Early Bird πŸƒ Academic Marathon (11) 🀝 Dynamic Duo (10) πŸ† Grand Slam πŸ† Keyword Champion (2) πŸ”₯ Unstoppable (8) πŸš€ Conference Pioneer πŸ“ˆ Trend Setter πŸ—ƒοΈ Keyword Collector (100) πŸ’Ž Century Club (20)

Conferences

ICML (6) NIPS (6) AISTATS (5) AAAI (1) COLT (1) ICLR (1)

Top co-authors

Adrian Weller (10) Krzysztof Choromanski (7) Valerii Likhosherstov (7) Uri Stemmer (4) Kumar Avinava Dubey (4) Edith Cohen (4) Mark Rowland (3) Han Lin (3) Jelani Nelson (3) Xingyou Song (3)

Keywords

kernel approximation (5) dimensionality reduction (4) transformer architecture (3) spectral analysis (2) tensor sketching (2) random projection (2) structured matrice (2) randomized algorithm (2) random feature (2) graph theory (2) differential privacy (2) wasserstein distance (2) reinforcement learning (2) gaussian kernel (2) heavy hitter (2) softmax kernel (2) point cloud (1) language modeling (1) attention mechanism (1) optimal transport (1)

Papers

Lower Bounds for Differential Privacy Under Continual Observation and Online Threshold Queries COLT 2024
Fast Tree-Field Integrators: From Low Displacement Rank to Topological Transformers NIPS 2024
Learning a Fourier Transform for Linear Relative Positional Encodings in Transformers AISTATS 2024
Tricking the Hashing Trick: A Tight Lower Bound on the Robustness of CountSketch to Adaptive Inputs AAAI 2023
Hardness of Low Rank Approximation of Entrywise Transformed Matrix Products NIPS 2023
Dense-Exponential Random Features: Sharp Positive Estimators of the Gaussian Kernel NIPS 2023
Efficient Graph Field Integrators Meet Point Clouds ICML 2023
On the Robustness of CountSketch to Adaptive Inputs ICML 2022
From block-Toeplitz matrices to differential equations on graphs: towards a general theory for scalable masked Transformers ICML 2022
Chefs' Random Tables: Non-Trigonometric Random Features NIPS 2022
Differentially Private Weighted Sampling AISTATS 2021
Rethinking Attention with Performers ICLR 2021
Stochastic Flows and Geometric Optimization on the Orthogonal Group ICML 2020
Tight Dimensionality Reduction for Sketching Low Degree Polynomial Kernels NIPS 2019
Matrix-Free Preconditioning in Online Learning ICML 2019
Orthogonal Estimation of Wasserstein Distances AISTATS 2019
The Geometry of Random Features AISTATS 2018
Geometrically Coupled Monte Carlo Sampling NIPS 2018
Structured adaptive and random spinners for fast machine learning computations AISTATS 2017
Fastfood - Computing Hilbert Space Expansions in loglinear time ICML 2013