Searching a Small National Domain - Preliminary Report. - András A. Benczúr; Tamás Sarlós; Máté Uher; Eszter Windhager (WWW (Posters), 2003)

SpamRank – Fully Automatic Link Spam Detection. - András A. Benczúr; Károly Csalogány; Tamás Sarlós; Máté Uher (AIRWeb, 2005)

On the feasibility of low-rank approximation for personalized PageRank. - András A. Benczúr; Károly Csalogány; Tamás Sarlós (WWW (Special interest tracks and posters), 2005)

Towards Scaling Fully Personalized PageRank: Algorithms, Lower Bounds, and Experiments. - Dániel Fogaras; Balázs Rácz; Károly Csalogány; Tamás Sarlós (Internet Math., 2005)

Link-Based Similarity Search to Fight Web Spam. - András A. Benczúr; Károly Csalogány; Tamás Sarlós (AIRWeb, 2006)

Improved Approximation Algorithms for Large Matrices via Random Projections. - Tamás Sarlós (FOCS, 2006)

To randomize or not to randomize: space optimal summaries for hyperlink analysis. - Tamás Sarlós; András A. Benczúr; Károly Csalogány; Dániel Fogaras; Balázs Rácz (WWW, 2006)

Web Spam Detection via Commercial Intent Analysis. - András A. Benczúr; István Bíró; Károly Csalogány; Tamás Sarlós (AIRWeb, 2007)

A sparse Johnson: Lindenstrauss transform. - Anirban Dasgupta 001; Ravi Kumar 001; Tamás Sarlós (STOC, 2010)

Fast locality-sensitive hashing. - Anirban Dasgupta 001; Ravi Kumar 001; Tamás Sarlós (KDD, 2011)

Mining tags using social endorsement networks. - Theodoros Lappas; Kunal Punera; Tamás Sarlós (SIGIR, 2011)

On scheduling in map-reduce and flow-shops. - Benjamin Moseley; Anirban Dasgupta 001; Ravi Kumar 001; Tamás Sarlós (SPAA, 2011)

Faster least squares approximation. - Petros Drineas; Michael W. Mahoney; S. Muthukrishnan 001; Tamás Sarlós (Numerische Mathematik, 2011)

Are web users really Markovian? - Flavio Chierichetti; Ravi Kumar 001; Prabhakar Raghavan; Tamás Sarlós (WWW, 2012)

Permutation indexing: fast approximate retrieval from large corpora. - Maxim Gurevich; Tamás Sarlós (CIKM, 2013)

Fastfood - Computing Hilbert Space Expansions in loglinear time. - Quoc V. Le; Tamás Sarlós; Alexander J. Smola (ICML (3), 2013)

Optimal hashing schemes for entity matching. - Nilesh N. Dalvi; Vibhor Rastogi; Anirban Dasgupta 001; Anish Das Sarma; Tamás Sarlós (WWW, 2013)

On estimating the average degree. - Anirban Dasgupta 001; Ravi Kumar 001; Tamás Sarlós (WWW, 2014)

Fastfood: Approximate Kernel Expansions in Loglinear Time. - Quoc Viet Le; Tamás Sarlós; Alexander Johannes Smola (CoRR, 2014)

On Sampling Nodes in a Network. - Flavio Chierichetti; Anirban Dasgupta 001; Ravi Kumar 001; Silvio Lattanzi; Tamás Sarlós (WWW, 2016)

TripleSpin - a generic compact paradigm for fast machine learning computations. - Krzysztof Choromanski; Francois Fagan; Cédric Gouy-Pailler; Anne Morvan; Tamás Sarlós; Jamal Atif (CoRR, 2016)

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 (AISTATS, 2017)

Caching with Dual Costs. - Anirban Dasgupta 001; Ravi Kumar 001; Tamás Sarlós (WWW (Companion Volume), 2017)

Linear Additive Markov Processes. - Ravi Kumar 001; Maithra Raghu; Tamás Sarlós; Andrew Tomkins (WWW, 2017)

The Geometry of Random Features. - Krzysztof Choromanski; Mark Rowland 001; Tamás Sarlós; Vikas Sindhwani; Richard E. Turner; Adrian Weller (AISTATS, 2018)

Geometrically Coupled Monte Carlo Sampling. - Mark Rowland 001; Krzysztof Choromanski; François Chalus; Aldo Pacchiano; Tamás Sarlós; Richard E. Turner; Adrian Weller (NeurIPS, 2018)

Orienteering Algorithms for Generating Travel Itineraries. - Zachary Friggstad; Sreenivas Gollapudi; Kostas Kollias; Tamás Sarlós; Chaitanya Swamy; Andrew Tomkins (WSDM, 2018)

Orthogonal Estimation of Wasserstein Distances. - Mark Rowland 001; Jiri Hron; Yunhao Tang; Krzysztof Choromanski; Tamás Sarlós; Adrian Weller (AISTATS, 2019)

Matrix-Free Preconditioning in Online Learning. - Ashok Cutkosky; Tamás Sarlós (ICML, 2019)

Tight Dimensionality Reduction for Sketching Low Degree Polynomial Kernels. - Michela Meister; Tamás Sarlós; David P. Woodruff (NeurIPS, 2019)

Reinforcement Learning with Chromatic Networks. - Xingyou Song; Krzysztof Choromanski; Jack Parker-Holder; Yunhao Tang; Wenbo Gao; Aldo Pacchiano; Tamás Sarlós; Deepali Jain; Yuxiang Yang 007 (CoRR, 2019)

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 038; Aldo Pacchiano; et al. (ICML, 2020)

Masked Language Modeling for Proteins via Linearly Scalable Long-Context Transformers. - Krzysztof Choromanski; Valerii Likhosherstov; David Dohan; Xingyou Song; Jared Davis; Tamás Sarlós; David Belanger 002; Lucy J. Colwell; Adrian Weller (CoRR, 2020)

Differentially Private Weighted Sampling. - Edith Cohen; Ofir Geri; Tamás Sarlós; Uri Stemmer (AISTATS, 2021)

Rethinking Attention with Performers. - Krzysztof Marcin Choromanski; Valerii Likhosherstov; David Dohan; Xingyou Song; Andreea Gane; Tamás Sarlós; Peter Hawkins; Jared Quincy Davis; Afroz Mohiuddin; Lukasz Kaiser; David Benjamin Belanger; Lucy J. Colwell; et al. (ICLR, 2021)

ES-ENAS: Combining Evolution Strategies with Neural Architecture Search at No Extra Cost for Reinforcement Learning. - Xingyou Song; Krzysztof Choromanski; Jack Parker-Holder; Yunhao Tang; Daiyi Peng; Deepali Jain; Wenbo Gao; Aldo Pacchiano; Tamás Sarlós; Yuxiang Yang 007 (CoRR, 2021)

From block-Toeplitz matrices to differential equations on graphs: towards a general theory for scalable masked Transformers. - Krzysztof Choromanski; Han Lin; Haoxian Chen 002; Tianyi Zhang; Arijit Sehanobish; Valerii Likhosherstov; Jack Parker-Holder; Tamás Sarlós; Adrian Weller; Thomas Weingarten (ICML, 2022)

On the Robustness of CountSketch to Adaptive Inputs. - Edith Cohen; Xin Lyu 002; Jelani Nelson; Tamás Sarlós; Moshe Shechner; Uri Stemmer (ICML, 2022)

Chefs' Random Tables: Non-Trigonometric Random Features. - Valerii Likhosherstov; Krzysztof Marcin Choromanski; Kumar Avinava Dubey; Frederick Liu; Tamás Sarlós; Adrian Weller (NeurIPS, 2022)

Tricking the Hashing Trick: A Tight Lower Bound on the Robustness of CountSketch to Adaptive Inputs. - Edith Cohen; Jelani Nelson; Tamás Sarlós; Uri Stemmer (AAAI, 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; et al. (ICML, 2023)

Generalized Private Selection and Testing with High Confidence. - Edith Cohen; Xin Lyu 002; Jelani Nelson; Tamás Sarlós; Uri Stemmer (ITCS, 2023)

Dense-Exponential Random Features: Sharp Positive Estimators of the Gaussian Kernel. - Valerii Likhosherstov; Krzysztof Marcin Choromanski; Kumar Avinava Dubey; Frederick Liu; Tamás Sarlós; Adrian Weller (NeurIPS, 2023)

Hardness of Low Rank Approximation of Entrywise Transformed Matrix Products. - Tamás Sarlós; Xingyou Song; David P. Woodruff; Richard Zhang 003 (NeurIPS, 2023)

Optimal Differentially Private Learning of Thresholds and Quasi-Concave Optimization. - Edith Cohen; Xin Lyu 002; Jelani Nelson; Tamás Sarlós; Uri Stemmer (STOC, 2023)

FAVOR#: Sharp Attention Kernel Approximations via New Classes of Positive Random Features. - Valerii Likhosherstov; Krzysztof Choromanski; Avinava Dubey; Frederick Liu; Tamás Sarlós; Adrian Weller (CoRR, 2023)

Hot PATE: Private Aggregation of Distributions for Diverse Task. - Edith Cohen; Xin Lyu 002; Jelani Nelson; Tamás Sarlós; Uri Stemmer (CoRR, 2023)

Learning a Fourier Transform for Linear Relative Positional Encodings in Transformers. - Krzysztof Choromanski; Shanda Li; Valerii Likhosherstov; Kumar Avinava Dubey; Shengjie Luo; Di He 001; Yiming Yang; Tamás Sarlós; Thomas Weingarten; Adrian Weller (AISTATS, 2024)

SARA-RT: Scaling up Robotics Transformers with Self-Adaptive Robust Attention. - Isabel Leal; Krzysztof Choromanski; Deepali Jain; Avinava Dubey; Jake Varley; Michael S. Ryoo; Yao Lu 006; Frederick Liu; Vikas Sindhwani; Quan Vuong; Tamás Sarlós; Ken Oslund; et al. (ICRA, 2024)

Fast Tree-Field Integrators: From Low Displacement Rank to Topological Transformers. - Krzysztof Marcin Choromanski; Arijit Sehanobish; Somnath Basu Roy Chowdhury; Han Lin; Kumar Avinava Dubey; Tamás Sarlós; Snigdha Chaturvedi (NeurIPS, 2024)

One Attack to Rule Them All: Tight Quadratic Bounds for Adaptive Queries on Cardinality Sketches. - Edith Cohen; Jelani Nelson; Tamás Sarlós; Mihir Singhal; Uri Stemmer (CoRR, 2024)

Lower Bounds for Differential Privacy Under Continual Observation and Online Threshold Queries. - Edith Cohen; Xin Lyu 002; Jelani Nelson; Tamás Sarlós; Uri Stemmer (IACR Cryptol. ePrint Arch., 2024)