Tamás Sarlós

Publication Activity (10 Years)

Years Active: 2003-2024
Publications (10 Years): 50

Top Topics

Markov Processes

Polynomial Kernels

Top Venues

Publications

Edith Cohen, Xin Lyu, Jelani Nelson, Tamás Sarlós, Uri Stemmer
Lower Bounds for Differential Privacy Under Continual Observation and Online Threshold Queries. COLT (2024)
Krzysztof Choromanski, Shanda Li, Valerii Likhosherstov, Kumar Avinava Dubey, Shengjie Luo, Di He, Yiming Yang, Tamás Sarlós, Thomas Weingarten, Adrian Weller
Learning a Fourier Transform for Linear Relative Positional Encodings in Transformers. AISTATS (2024)
Krzysztof Choromanski, Arijit Sehanobish, Somnath Basu Roy Chowdhury, Han Lin, Avinava Dubey, Tamás Sarlós, Snigdha Chaturvedi
Fast Tree-Field Integrators: From Low Displacement Rank to Topological Transformers. CoRR (2024)
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
SARA-RT: Scaling up Robotics Transformers with Self-Adaptive Robust Attention. ICRA (2024)
Edith Cohen, Xin Lyu, Jelani Nelson, Tamás Sarlós, Uri Stemmer
Lower Bounds for Differential Privacy Under Continual Observation and Online Threshold Queries. CoRR (2024)
Edith Cohen, Xin Lyu, Jelani Nelson, Tamás Sarlós, Uri Stemmer
Lower Bounds for Differential Privacy Under Continual Observation and Online Threshold Queries. IACR Cryptol. ePrint Arch. 2024 (2024)
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
Efficient Graph Field Integrators Meet Point Clouds. ICML (2023)
Valerii Likhosherstov, Krzysztof Choromanski, Avinava Dubey, Frederick Liu, Tamás Sarlós, Adrian Weller
FAVOR#: Sharp Attention Kernel Approximations via New Classes of Positive Random Features. CoRR (2023)
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
SARA-RT: Scaling up Robotics Transformers with Self-Adaptive Robust Attention. CoRR (2023)
Tamás Sarlós, Xingyou Song, David P. Woodruff, Qiuyi Zhang
Hardness of Low Rank Approximation of Entrywise Transformed Matrix Products. CoRR (2023)
Edith Cohen, Xin Lyu, Jelani Nelson, Tamás Sarlós, Uri Stemmer
Optimal Differentially Private Learning of Thresholds and Quasi-Concave Optimization. STOC (2023)
Krzysztof Marcin Choromanski, Shanda Li, Valerii Likhosherstov, Kumar Avinava Dubey, Shengjie Luo, Di He, Yiming Yang, Tamás Sarlós, Thomas Weingarten, Adrian Weller
Learning a Fourier Transform for Linear Relative Positional Encodings in Transformers. CoRR (2023)
Edith Cohen, Jelani Nelson, Tamás Sarlós, Uri Stemmer
Tricking the Hashing Trick: A Tight Lower Bound on the Robustness of CountSketch to Adaptive Inputs. AAAI (2023)
Krzysztof Choromanski, Arijit Sehanobish, Han Lin, Yunfan Zhao, Eli Berger, Tetiana Parshakova, Alvin Pan, David Watkins, Tianyi Zhang, Valerii Likhosherstov, Somnath Basu Roy Chowdhury, Avinava Dubey, Deepali Jain, Tamás Sarlós, Snigdha Chaturvedi, Adrian Weller
Efficient Graph Field Integrators Meet Point Clouds. CoRR (2023)
Edith Cohen, Xin Lyu, Jelani Nelson, Tamás Sarlós, Uri Stemmer
Generalized Private Selection and Testing with High Confidence. ITCS (2023)
Edith Cohen, Xin Lyu, Jelani Nelson, Tamás Sarlós, Uri Stemmer
Hot PATE: Private Aggregation of Distributions for Diverse Task. CoRR (2023)
Valerii Likhosherstov, Krzysztof Marcin Choromanski, Kumar Avinava Dubey, Frederick Liu, Tamás Sarlós, Adrian Weller
Dense-Exponential Random Features: Sharp Positive Estimators of the Gaussian Kernel. NeurIPS (2023)
Tamás Sarlós, Xingyou Song, David P. Woodruff, Richard Zhang
Hardness of Low Rank Approximation of Entrywise Transformed Matrix Products. NeurIPS (2023)
Edith Cohen, Xin Lyu, Jelani Nelson, Tamás Sarlós, Uri Stemmer
Õptimal Differentially Private Learning of Thresholds and Quasi-Concave Optimization. CoRR (2022)
Edith Cohen, Xin Lyu, Jelani Nelson, Tamás Sarlós, Uri Stemmer
Generalized Private Selection and Testing with High Confidence. CoRR (2022)
Krzysztof Choromanski, Han Lin, Haoxian Chen, Tianyi Zhang, Arijit Sehanobish, Valerii Likhosherstov, Jack Parker-Holder, Tamás Sarlós, Adrian Weller, Thomas Weingarten
From block-Toeplitz matrices to differential equations on graphs: towards a general theory for scalable masked Transformers. ICML (2022)
Edith Cohen, Xin Lyu, Jelani Nelson, Tamás Sarlós, Moshe Shechner, Uri Stemmer
On the Robustness of CountSketch to Adaptive Inputs. CoRR (2022)
Edith Cohen, Xin Lyu, Jelani Nelson, Tamás Sarlós, Moshe Shechner, Uri Stemmer
On the Robustness of CountSketch to Adaptive Inputs. ICML (2022)
Valerii Likhosherstov, Krzysztof Choromanski, Avinava Dubey, Frederick Liu, Tamás Sarlós, Adrian Weller
Chefs' Random Tables: Non-Trigonometric Random Features. CoRR (2022)
Edith Cohen, Jelani Nelson, Tamás Sarlós, Uri Stemmer
Tricking the Hashing Trick: A Tight Lower Bound on the Robustness of CountSketch to Adaptive Inputs. CoRR (2022)
Valerii Likhosherstov, Krzysztof Marcin Choromanski, Kumar Avinava Dubey, Frederick Liu, Tamás Sarlós, Adrian Weller
Chefs' Random Tables: Non-Trigonometric Random Features. NeurIPS (2022)
Xingyou Song, Krzysztof Choromanski, Jack Parker-Holder, Yunhao Tang, Daiyi Peng, Deepali Jain, Wenbo Gao, Aldo Pacchiano, Tamás Sarlós, Yuxiang Yang
ES-ENAS: Combining Evolution Strategies with Neural Architecture Search at No Extra Cost for Reinforcement Learning. CoRR (2021)
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
Rethinking Attention with Performers. ICLR (2021)
Edith Cohen, Ofir Geri, Tamás Sarlós, Uri Stemmer
Differentially Private Weighted Sampling. AISTATS (2021)
Edith Cohen, Ofir Geri, Tamás Sarlós, Uri Stemmer
Differentially Private Weighted Sampling. CoRR (2020)
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
Stochastic Flows and Geometric Optimization on the Orthogonal Group. ICML (2020)
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
Stochastic Flows and Geometric Optimization on the Orthogonal Group. CoRR (2020)
Krzysztof Choromanski, Valerii Likhosherstov, David Dohan, Xingyou Song, Jared Davis, Tamás Sarlós, David Belanger, Lucy J. Colwell, Adrian Weller
Masked Language Modeling for Proteins via Linearly Scalable Long-Context Transformers. CoRR (2020)
Krzysztof Choromanski, Valerii Likhosherstov, David Dohan, Xingyou Song, Andreea Gane, Tamás Sarlós, Peter Hawkins, Jared Davis, Afroz Mohiuddin, Lukasz Kaiser, David Belanger, Lucy J. Colwell, Adrian Weller
Rethinking Attention with Performers. CoRR (2020)
Ashok Cutkosky, Tamás Sarlós
Matrix-Free Preconditioning in Online Learning. ICML (2019)
Mark Rowland, Jiri Hron, Yunhao Tang, Krzysztof Choromanski, Tamás Sarlós, Adrian Weller
Orthogonal Estimation of Wasserstein Distances. CoRR (2019)
Ashok Cutkosky, Tamás Sarlós
Matrix-Free Preconditioning in Online Learning. CoRR (2019)
Michela Meister, Tamás Sarlós, David P. Woodruff
Tight Dimensionality Reduction for Sketching Low Degree Polynomial Kernels. NeurIPS (2019)
Mark Rowland, Jiri Hron, Yunhao Tang, Krzysztof Choromanski, Tamás Sarlós, Adrian Weller
Orthogonal Estimation of Wasserstein Distances. AISTATS (2019)
Xingyou Song, Krzysztof Choromanski, Jack Parker-Holder, Yunhao Tang, Wenbo Gao, Aldo Pacchiano, Tamás Sarlós, Deepali Jain, Yuxiang Yang
Reinforcement Learning with Chromatic Networks. CoRR (2019)
Mark Rowland, Krzysztof Choromanski, François Chalus, Aldo Pacchiano, Tamás Sarlós, Richard E. Turner, Adrian Weller
Geometrically Coupled Monte Carlo Sampling. NeurIPS (2018)
Krzysztof Choromanski, Mark Rowland, Tamás Sarlós, Vikas Sindhwani, Richard E. Turner, Adrian Weller
The Geometry of Random Features. AISTATS (2018)
Zachary Friggstad, Sreenivas Gollapudi, Kostas Kollias, Tamás Sarlós, Chaitanya Swamy, Andrew Tomkins
Orienteering Algorithms for Generating Travel Itineraries. WSDM (2018)
Mariusz Bojarski, Anna Choromanska, Krzysztof Choromanski, Francois Fagan, Cédric Gouy-Pailler, Anne Morvan, Nourhan Sakr, Tamás Sarlós, Jamal Atif
Structured adaptive and random spinners for fast machine learning computations. AISTATS (2017)
Anirban Dasgupta, Ravi Kumar, Tamás Sarlós
Caching with Dual Costs. WWW (Companion Volume) (2017)
Ravi Kumar, Maithra Raghu, Tamás Sarlós, Andrew Tomkins
Linear Additive Markov Processes. WWW (2017)
Ravi Kumar, Maithra Raghu, Tamás Sarlós, Andrew Tomkins
Linear Additive Markov Processes. CoRR (2017)
Krzysztof Choromanski, Francois Fagan, Cédric Gouy-Pailler, Anne Morvan, Tamás Sarlós, Jamal Atif
TripleSpin - a generic compact paradigm for fast machine learning computations. CoRR (2016)
Mariusz Bojarski, Anna Choromanska, Krzysztof Choromanski, Francois Fagan, Cédric Gouy-Pailler, Anne Morvan, Nourhan Sakr, Tamás Sarlós, Jamal Atif
Structured adaptive and random spinners for fast machine learning computations. CoRR (2016)
Flavio Chierichetti, Anirban Dasgupta, Ravi Kumar, Silvio Lattanzi, Tamás Sarlós
On Sampling Nodes in a Network. WWW (2016)
Anirban Dasgupta, Ravi Kumar, Tamás Sarlós
On estimating the average degree. WWW (2014)
Quoc Viet Le, Tamás Sarlós, Alexander Johannes Smola
Fastfood: Approximate Kernel Expansions in Loglinear Time. CoRR (2014)
Quoc V. Le, Tamás Sarlós, Alexander J. Smola
Fastfood - Computing Hilbert Space Expansions in loglinear time. ICML (3) (2013)
Nilesh N. Dalvi, Vibhor Rastogi, Anirban Dasgupta, Anish Das Sarma, Tamás Sarlós
Optimal hashing schemes for entity matching. WWW (2013)
Maxim Gurevich, Tamás Sarlós
Permutation indexing: fast approximate retrieval from large corpora. CIKM (2013)
Flavio Chierichetti, Ravi Kumar, Prabhakar Raghavan, Tamás Sarlós
Are web users really Markovian? WWW (2012)
Benjamin Moseley, Anirban Dasgupta, Ravi Kumar, Tamás Sarlós
On scheduling in map-reduce and flow-shops. SPAA (2011)
Theodoros Lappas, Kunal Punera, Tamás Sarlós
Mining tags using social endorsement networks. SIGIR (2011)
Petros Drineas, Michael W. Mahoney, S. Muthukrishnan, Tamás Sarlós
Faster least squares approximation. Numerische Mathematik 117 (2) (2011)
Anirban Dasgupta, Ravi Kumar, Tamás Sarlós
Fast locality-sensitive hashing. KDD (2011)
Anirban Dasgupta, Ravi Kumar, Tamás Sarlós
A Sparse Johnson--Lindenstrauss Transform CoRR (2010)
Anirban Dasgupta, Ravi Kumar, Tamás Sarlós
A sparse Johnson: Lindenstrauss transform. STOC (2010)
Petros Drineas, Michael W. Mahoney, S. Muthukrishnan, Tamás Sarlós
Faster Least Squares Approximation CoRR (2007)
András A. Benczúr, István Bíró, Károly Csalogány, Tamás Sarlós
Web Spam Detection via Commercial Intent Analysis. AIRWeb (2007)
Tamás Sarlós, András A. Benczúr, Károly Csalogány, Dániel Fogaras, Balázs Rácz
To randomize or not to randomize: space optimal summaries for hyperlink analysis. WWW (2006)
András A. Benczúr, Károly Csalogány, Tamás Sarlós
Link-Based Similarity Search to Fight Web Spam. AIRWeb (2006)
Tamás Sarlós
Improved Approximation Algorithms for Large Matrices via Random Projections. FOCS (2006)
Dániel Fogaras, Balázs Rácz, Károly Csalogány, Tamás Sarlós
Towards Scaling Fully Personalized PageRank: Algorithms, Lower Bounds, and Experiments. Internet Math. 2 (3) (2005)
András A. Benczúr, Károly Csalogány, Tamás Sarlós, Máté Uher
SpamRank -- Fully Automatic Link Spam Detection. AIRWeb (2005)
András A. Benczúr, Károly Csalogány, Tamás Sarlós
On the feasibility of low-rank approximation for personalized PageRank. WWW (Special interest tracks and posters) (2005)
András A. Benczúr, Tamás Sarlós, Máté Uher, Eszter Windhager
Searching a Small National Domain - Preliminary Report. WWW (Posters) (2003)