Tamás Sarlós

According to our database, Tamás Sarlós authored at least 51 papers between 2003 and 2024.

Collaborative distances:

• Dijkstra number of three.
• Erdős number of three.

2024

Lower Bounds for Differential Privacy Under Continual Observation and Online Threshold Queries.

Edith Cohen, Xin Lyu, Jelani Nelson, Tamás Sarlós, Uri Stemmer

IACR Cryptol. ePrint Arch., 2024

2023

Hot PATE: Private Aggregation of Distributions for Diverse Task.

Edith Cohen, Xin Lyu, Jelani Nelson, Tamás Sarlós, Uri Stemmer

CoRR, 2023

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, Frederick Liu, Vikas Sindhwani, Quan Vuong, Tamás Sarlós, Ken Oslund, Karol Hausman, Kanishka Rao

CoRR, 2023

Hardness of Low Rank Approximation of Entrywise Transformed Matrix Products.

Tamás Sarlós, Xingyou Song, David P. Woodruff, Qiuyi Zhang

CoRR, 2023

Learning a Fourier Transform for Linear Relative Positional Encodings in Transformers.

Krzysztof Marcin Choromanski, Shanda Li, Valerii Likhosherstov, Kumar Avinava Dubey, Shengjie Luo, Di He, Yiming Yang, Tamás Sarlós, Thomas Weingarten, Adrian Weller

CoRR, 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

Optimal Differentially Private Learning of Thresholds and Quasi-Concave Optimization.

Edith Cohen, Xin Lyu, Jelani Nelson, Tamás Sarlós, Uri Stemmer

Proceedings of the 55th Annual ACM Symposium on Theory of Computing, 2023

Hardness of Low Rank Approximation of Entrywise Transformed Matrix Products.

Tamás Sarlós, Xingyou Song, David P. Woodruff, Richard Zhang

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 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

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Generalized Private Selection and Testing with High Confidence.

Edith Cohen, Xin Lyu, Jelani Nelson, Tamás Sarlós, Uri Stemmer

Proceedings of the 14th Innovations in Theoretical Computer Science Conference, 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, Tamás Sarlós, Snigdha Chaturvedi, Adrian Weller

Proceedings of the International Conference on Machine Learning, 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

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022

Chefs' Random Tables: Non-Trigonometric Random Features.

Valerii Likhosherstov, Krzysztof Marcin Choromanski, Kumar Avinava Dubey, Frederick Liu, Tamás Sarlós, Adrian Weller

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

On the Robustness of CountSketch to Adaptive Inputs.

Edith Cohen, Xin Lyu, Jelani Nelson, Tamás Sarlós, Moshe Shechner, Uri Stemmer

Proceedings of the International Conference on Machine Learning, 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, Tamás Sarlós, Adrian Weller, Thomas Weingarten

Proceedings of the International Conference on Machine Learning, 2022

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

CoRR, 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, Adrian Weller

Proceedings of the 9th International Conference on Learning Representations, 2021

Differentially Private Weighted Sampling.

Edith Cohen, Ofir Geri, Tamás Sarlós, Uri Stemmer

Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

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, Lucy J. Colwell, Adrian Weller

CoRR, 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, Tamás Sarlós, Adrian Weller, Vikas Sindhwani

Proceedings of the 37th International Conference on Machine Learning, 2020

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

CoRR, 2019

Tight Dimensionality Reduction for Sketching Low Degree Polynomial Kernels.

Michela Meister, Tamás Sarlós, David P. Woodruff

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Matrix-Free Preconditioning in Online Learning.

Ashok Cutkosky, Tamás Sarlós

Proceedings of the 36th International Conference on Machine Learning, 2019

Orthogonal Estimation of Wasserstein Distances.

Mark Rowland, Jiri Hron, Yunhao Tang, Krzysztof Choromanski, Tamás Sarlós, Adrian Weller

Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

2018

Orienteering Algorithms for Generating Travel Itineraries.

Zachary Friggstad, Sreenivas Gollapudi, Kostas Kollias, Tamás Sarlós, Chaitanya Swamy, Andrew Tomkins

Proceedings of the Eleventh ACM International Conference on Web Search and Data Mining, 2018

Geometrically Coupled Monte Carlo Sampling.

Mark Rowland, Krzysztof Choromanski, François Chalus, Aldo Pacchiano, Tamás Sarlós, Richard E. Turner, Adrian Weller

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

The Geometry of Random Features.

Krzysztof Choromanski, Mark Rowland, Tamás Sarlós, Vikas Sindhwani, Richard E. Turner, Adrian Weller

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2018

2017

Linear Additive Markov Processes.

Ravi Kumar, Maithra Raghu, Tamás Sarlós, Andrew Tomkins

Proceedings of the 26th International Conference on World Wide Web, 2017

Caching with Dual Costs.

Anirban Dasgupta, Ravi Kumar, Tamás Sarlós

Proceedings of the 26th International Conference on World Wide Web Companion, 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

Proceedings of the 20th International Conference on Artificial Intelligence and Statistics, 2017

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

On Sampling Nodes in a Network.

Flavio Chierichetti, Anirban Dasgupta, Ravi Kumar, Silvio Lattanzi, Tamás Sarlós

Proceedings of the 25th International Conference on World Wide Web, 2016

2014

Fastfood: Approximate Kernel Expansions in Loglinear Time.

Quoc Viet Le, Tamás Sarlós, Alexander Johannes Smola

CoRR, 2014

On estimating the average degree.

Anirban Dasgupta, Ravi Kumar, Tamás Sarlós

Proceedings of the 23rd International World Wide Web Conference, 2014

2013

Optimal hashing schemes for entity matching.

Nilesh N. Dalvi, Vibhor Rastogi, Anirban Dasgupta, Anish Das Sarma, Tamás Sarlós

Proceedings of the 22nd International World Wide Web Conference, 2013

Fastfood - Computing Hilbert Space Expansions in loglinear time.

Quoc V. Le, Tamás Sarlós, Alexander J. Smola

Proceedings of the 30th International Conference on Machine Learning, 2013

Permutation indexing: fast approximate retrieval from large corpora.

Maxim Gurevich, Tamás Sarlós

Proceedings of the 22nd ACM International Conference on Information and Knowledge Management, 2013

2012

Are web users really Markovian?

Flavio Chierichetti, Ravi Kumar, Prabhakar Raghavan, Tamás Sarlós

Proceedings of the 21st World Wide Web Conference 2012, 2012

2011

Faster least squares approximation.

Petros Drineas, Michael W. Mahoney, S. Muthukrishnan, Tamás Sarlós

Numerische Mathematik, 2011

On scheduling in map-reduce and flow-shops.

Benjamin Moseley, Anirban Dasgupta, Ravi Kumar, Tamás Sarlós

Proceedings of the SPAA 2011: Proceedings of the 23rd Annual ACM Symposium on Parallelism in Algorithms and Architectures, 2011

Mining tags using social endorsement networks.

Theodoros Lappas, Kunal Punera, Tamás Sarlós

Proceedings of the Proceeding of the 34th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2011

Fast locality-sensitive hashing.

Anirban Dasgupta, Ravi Kumar, Tamás Sarlós

Proceedings of the 17th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2011

2010

A sparse Johnson: Lindenstrauss transform.

Anirban Dasgupta, Ravi Kumar, Tamás Sarlós

Proceedings of the 42nd ACM Symposium on Theory of Computing, 2010

2007

Web Spam Detection via Commercial Intent Analysis.

András A. Benczúr, István Bíró, Károly Csalogány, Tamás Sarlós

Proceedings of the AIRWeb 2007, 2007

2006

To randomize or not to randomize: space optimal summaries for hyperlink analysis.

Tamás Sarlós, András A. Benczúr, Károly Csalogány, Dániel Fogaras, Balázs Rácz

Proceedings of the 15th international conference on World Wide Web, 2006

Improved Approximation Algorithms for Large Matrices via Random Projections.

Tamás Sarlós

Proceedings of the 47th Annual IEEE Symposium on Foundations of Computer Science (FOCS 2006), 2006

Link-Based Similarity Search to Fight Web Spam.

András A. Benczúr, Károly Csalogány, Tamás Sarlós

Proceedings of the AIRWeb 2006, 2006

2005

Towards Scaling Fully Personalized PageRank: Algorithms, Lower Bounds, and Experiments.

Dániel Fogaras, Balázs Rácz, Károly Csalogány, Tamás Sarlós

Internet Math., 2005

On the feasibility of low-rank approximation for personalized PageRank.

András A. Benczúr, Károly Csalogány, Tamás Sarlós

Proceedings of the 14th international conference on World Wide Web, 2005

SpamRank -- Fully Automatic Link Spam Detection.

András A. Benczúr, Károly Csalogány, Tamás Sarlós, Máté Uher

Proceedings of the AIRWeb 2005, 2005

2003

Searching a Small National Domain - Preliminary Report.

András A. Benczúr, Tamás Sarlós, Máté Uher, Eszter Windhager

Proceedings of the Twelfth International World Wide Web Conference - Posters, 2003