Sarlos, Tamas

20 publications

NeurIPS 2024 Fast Tree-Field Integrators: From Low Displacement Rank to Topological Transformers Krzysztof Choromanski, Arijit Sehanobish, Somnath Basu Roy Chowdhury, Han Lin, Avinava Dubey, Tamas Sarlos, Snigdha Chaturvedi

AISTATS 2024 Learning a Fourier Transform for Linear Relative Positional Encodings in Transformers Krzysztof Choromanski, Shanda Li, Valerii Likhosherstov, Kumar Avinava Dubey, Shengjie Luo, Di He, Yiming Yang, Tamas Sarlos, Thomas Weingarten, Adrian Weller

COLT 2024 Lower Bounds for Differential Privacy Under Continual Observation and Online Threshold Queries Edith Cohen, Xin Lyu, Jelani Nelson, Tamás Sarlós, Uri Stemmer

NeurIPS 2023 Dense-Exponential Random Features: Sharp Positive Estimators of the Gaussian Kernel Valerii Likhosherstov, Krzysztof M Choromanski, Kumar Avinava Dubey, Frederick Liu, Tamas Sarlos, Adrian Weller

ICML 2023 Efficient Graph Field Integrators Meet Point Clouds Krzysztof Marcin Choromanski, Arijit Sehanobish, Han Lin, Yunfan Zhao, Eli Berger, Tetiana Parshakova, Alvin Pan, David Watkins, Tianyi Zhang, Valerii Likhosherstov, Somnath Basu Roy Chowdhury, Kumar Avinava Dubey, Deepali Jain, Tamas Sarlos, Snigdha Chaturvedi, Adrian Weller

NeurIPS 2023 Hardness of Low Rank Approximation of Entrywise Transformed Matrix Products Tamas Sarlos, Xingyou Song, David Woodruff, Richard Zhang

AAAI 2023 Tricking the Hashing Trick: A Tight Lower Bound on the Robustness of CountSketch to Adaptive Inputs Edith Cohen, Jelani Nelson, Tamás Sarlós, Uri Stemmer

NeurIPS 2022 Chefs' Random Tables: Non-Trigonometric Random Features Valerii Likhosherstov, Krzysztof M Choromanski, Kumar Avinava Dubey, Frederick Liu, Tamas Sarlos, Adrian Weller

ICML 2022 From Block-Toeplitz Matrices to Differential Equations on Graphs: Towards a General Theory for Scalable Masked Transformers Krzysztof Choromanski, Han Lin, Haoxian Chen, Tianyi Zhang, Arijit Sehanobish, Valerii Likhosherstov, Jack Parker-Holder, Tamas Sarlos, Adrian Weller, Thomas Weingarten

ICML 2022 On the Robustness of CountSketch to Adaptive Inputs Edith Cohen, Xin Lyu, Jelani Nelson, Tamas Sarlos, Moshe Shechner, Uri Stemmer

AISTATS 2021 Differentially Private Weighted Sampling Edith Cohen, Ofir Geri, Tamas Sarlos, Uri Stemmer

ICLR 2021 Rethinking Attention with Performers Krzysztof Marcin Choromanski, Valerii Likhosherstov, David Dohan, Xingyou Song, Andreea Gane, Tamas Sarlos, Peter Hawkins, Jared Quincy Davis, Afroz Mohiuddin, Lukasz Kaiser, David Benjamin Belanger, Lucy J Colwell, Adrian Weller

ICML 2020 Stochastic Flows and Geometric Optimization on the Orthogonal Group Krzysztof Choromanski, David Cheikhi, Jared Davis, Valerii Likhosherstov, Achille Nazaret, Achraf Bahamou, Xingyou Song, Mrugank Akarte, Jack Parker-Holder, Jacob Bergquist, Yuan Gao, Aldo Pacchiano, Tamas Sarlos, Adrian Weller, Vikas Sindhwani

ICML 2019 Matrix-Free Preconditioning in Online Learning Ashok Cutkosky, Tamas Sarlos

AISTATS 2019 Orthogonal Estimation of Wasserstein Distances Mark Rowland, Jiri Hron, Yunhao Tang, Krzysztof Choromanski, Tamas Sarlos, Adrian Weller

NeurIPS 2019 Tight Dimensionality Reduction for Sketching Low Degree Polynomial Kernels Michela Meister, Tamas Sarlos, David Woodruff

NeurIPS 2018 Geometrically Coupled Monte Carlo Sampling Mark Rowland, Krzysztof M Choromanski, François Chalus, Aldo Pacchiano, Tamas Sarlos, Richard E Turner, Adrian Weller

AISTATS 2018 The Geometry of Random Features Krzysztof Choromanski, Mark Rowland, Tamás Sarlós, Vikas Sindhwani, Richard E. Turner, Adrian Weller

AISTATS 2017 Structured Adaptive and Random Spinners for Fast Machine Learning Computations Mariusz Bojarski, Anna Choromanska, Krzysztof Choromanski, Francois Fagan, Cédric Gouy-Pailler, Anne Morvan, Nourhan Sakr, Tamás Sarlós, Jamal Atif

ICML 2013 Fastfood - Computing Hilbert Space Expansions in Loglinear Time Quoc Le, Tamas Sarlos, Alexander Smola