Tamás Sarlós

75 papers A* 27A 9B 1Journal 31Unranked 7

Year	Rank	Type	Title / Venue / Authors
2026	A*	`conf`	One Attack to Rule Them All: Tight Quadratic Bounds for Adaptive Queries on Cardinality Sketches. SODA Edith Cohen, Jelani Nelson, Tamás Sarlós, Mihir Singhal, Uri Stemmer
2025	A	`conf`	Linear Elastic Caching via Ski Rental. CIDR Ravi Kumar, Todd Lipcon, Manish Purohit, Tamás Sarlós
2024	A*	`conf`	Fast Tree-Field Integrators: From Low Displacement Rank to Topological Transformers. NeurIPS Krzysztof Marcin Choromanski, Arijit Sehanobish, Somnath Basu Roy Chowdhury, Han Lin, Kumar Avinava Dubey, Tamás Sarlós, Snigdha Chaturvedi
2024	J	`jnl`	Fast Tree-Field Integrators: From Low Displacement Rank to Topological Transformers. CoRR Krzysztof Choromanski, Arijit Sehanobish, Somnath Basu Roy Chowdhury, Han Lin, Avinava Dubey, Tamás Sarlós, Snigdha Chaturvedi
2024	A	`conf`	Learning a Fourier Transform for Linear Relative Positional Encodings in Transformers. AISTATS Krzysztof Choromanski, Shanda Li, Valerii Likhosherstov, Kumar Avinava Dubey, Shengjie Luo, Di He, Yiming Yang, Tamás Sarlós, Thomas Weingarten, Adrian Weller
2024	A*	`conf`	Lower Bounds for Differential Privacy Under Continual Observation and Online Threshold Queries. COLT Edith Cohen, Xin Lyu, Jelani Nelson, Tamás Sarlós, Uri Stemmer
2024	J	`jnl`	Lower Bounds for Differential Privacy Under Continual Observation and Online Threshold Queries. CoRR Edith Cohen, Xin Lyu, Jelani Nelson, Tamás Sarlós, Uri Stemmer
2024	J	`jnl`	Lower Bounds for Differential Privacy Under Continual Observation and Online Threshold Queries. IACR Cryptol. ePrint Arch. Edith Cohen, Xin Lyu, Jelani Nelson, Tamás Sarlós, Uri Stemmer
2024	J	`jnl`	One Attack to Rule Them All: Tight Quadratic Bounds for Adaptive Queries on Cardinality Sketches. CoRR Edith Cohen, Jelani Nelson, Tamás Sarlós, Mihir Singhal, Uri Stemmer
2024	A*	`conf`	SARA-RT: Scaling up Robotics Transformers with Self-Adaptive Robust Attention. ICRA 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
2023	A*	`conf`	Dense-Exponential Random Features: Sharp Positive Estimators of the Gaussian Kernel. NeurIPS Valerii Likhosherstov, Krzysztof Marcin Choromanski, Kumar Avinava Dubey, Frederick Liu, Tamás Sarlós, Adrian Weller
2023	A*	`conf`	Efficient Graph Field Integrators Meet Point Clouds. ICML 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
2023	J	`jnl`	Efficient Graph Field Integrators Meet Point Clouds. CoRR 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
2023	J	`jnl`	FAVOR#: Sharp Attention Kernel Approximations via New Classes of Positive Random Features. CoRR Valerii Likhosherstov, Krzysztof Choromanski, Avinava Dubey, Frederick Liu, Tamás Sarlós, Adrian Weller
2023	A	`conf`	Generalized Private Selection and Testing with High Confidence. ITCS Edith Cohen, Xin Lyu, Jelani Nelson, Tamás Sarlós, Uri Stemmer
2023	A*	`conf`	Hardness of Low Rank Approximation of Entrywise Transformed Matrix Products. NeurIPS Tamás Sarlós, Xingyou Song, David P. Woodruff, Richard Zhang
2023	J	`jnl`	Hardness of Low Rank Approximation of Entrywise Transformed Matrix Products. CoRR Tamás Sarlós, Xingyou Song, David P. Woodruff, Qiuyi Zhang
2023	J	`jnl`	Hot PATE: Private Aggregation of Distributions for Diverse Task. CoRR Edith Cohen, Xin Lyu, Jelani Nelson, Tamás Sarlós, Uri Stemmer
2023	J	`jnl`	Learning a Fourier Transform for Linear Relative Positional Encodings in Transformers. CoRR Krzysztof Marcin Choromanski, Shanda Li, Valerii Likhosherstov, Kumar Avinava Dubey, Shengjie Luo, Di He, Yiming Yang, Tamás Sarlós, Thomas Weingarten, Adrian Weller
2023	A*	`conf`	Optimal Differentially Private Learning of Thresholds and Quasi-Concave Optimization. STOC Edith Cohen, Xin Lyu, Jelani Nelson, Tamás Sarlós, Uri Stemmer
2023	J	`jnl`	SARA-RT: Scaling up Robotics Transformers with Self-Adaptive Robust Attention. CoRR 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
2023	A*	`conf`	Tricking the Hashing Trick: A Tight Lower Bound on the Robustness of CountSketch to Adaptive Inputs. AAAI Edith Cohen, Jelani Nelson, Tamás Sarlós, Uri Stemmer
2022	A*	`conf`	Chefs' Random Tables: Non-Trigonometric Random Features. NeurIPS Valerii Likhosherstov, Krzysztof Marcin Choromanski, Kumar Avinava Dubey, Frederick Liu, Tamás Sarlós, Adrian Weller
2022	J	`jnl`	Chefs' Random Tables: Non-Trigonometric Random Features. CoRR Valerii Likhosherstov, Krzysztof Choromanski, Avinava Dubey, Frederick Liu, Tamás Sarlós, Adrian Weller
2022	A*	`conf`	From block-Toeplitz matrices to differential equations on graphs: towards a general theory for scalable masked Transformers. ICML Krzysztof Choromanski, Han Lin, Haoxian Chen, Tianyi Zhang, Arijit Sehanobish, Valerii Likhosherstov, Jack Parker-Holder, Tamás Sarlós, Adrian Weller, Thomas Weingarten
2022	J	`jnl`	Generalized Private Selection and Testing with High Confidence. CoRR Edith Cohen, Xin Lyu, Jelani Nelson, Tamás Sarlós, Uri Stemmer
2022	A*	`conf`	On the Robustness of CountSketch to Adaptive Inputs. ICML Edith Cohen, Xin Lyu, Jelani Nelson, Tamás Sarlós, Moshe Shechner, Uri Stemmer
2022	J	`jnl`	On the Robustness of CountSketch to Adaptive Inputs. CoRR Edith Cohen, Xin Lyu, Jelani Nelson, Tamás Sarlós, Moshe Shechner, Uri Stemmer
2022	J	`jnl`	Tricking the Hashing Trick: A Tight Lower Bound on the Robustness of CountSketch to Adaptive Inputs. CoRR Edith Cohen, Jelani Nelson, Tamás Sarlós, Uri Stemmer
2022	J	`jnl`	Õptimal Differentially Private Learning of Thresholds and Quasi-Concave Optimization. CoRR Edith Cohen, Xin Lyu, Jelani Nelson, Tamás Sarlós, Uri Stemmer
2021	A	`conf`	Differentially Private Weighted Sampling. AISTATS Edith Cohen, Ofir Geri, Tamás Sarlós, Uri Stemmer
2021	J	`jnl`	ES-ENAS: Combining Evolution Strategies with Neural Architecture Search at No Extra Cost for Reinforcement Learning. CoRR Xingyou Song, Krzysztof Choromanski, Jack Parker-Holder, Yunhao Tang, Daiyi Peng, Deepali Jain, Wenbo Gao, Aldo Pacchiano, Tamás Sarlós, Yuxiang Yang
2021	A*	`conf`	Rethinking Attention with Performers. ICLR 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
2020	J	`jnl`	Differentially Private Weighted Sampling. CoRR Edith Cohen, Ofir Geri, Tamás Sarlós, Uri Stemmer
2020	J	`jnl`	Masked Language Modeling for Proteins via Linearly Scalable Long-Context Transformers. CoRR Krzysztof Choromanski, Valerii Likhosherstov, David Dohan, Xingyou Song, Jared Davis, Tamás Sarlós, David Belanger, Lucy J. Colwell, Adrian Weller
2020	J	`jnl`	Rethinking Attention with Performers. CoRR 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
2020	A*	`conf`	Stochastic Flows and Geometric Optimization on the Orthogonal Group. ICML 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
2020	J	`jnl`	Stochastic Flows and Geometric Optimization on the Orthogonal Group. CoRR 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
2019	A*	`conf`	Matrix-Free Preconditioning in Online Learning. ICML Ashok Cutkosky, Tamás Sarlós
2019	J	`jnl`	Matrix-Free Preconditioning in Online Learning. CoRR Ashok Cutkosky, Tamás Sarlós
2019	A	`conf`	Orthogonal Estimation of Wasserstein Distances. AISTATS Mark Rowland, Jiri Hron, Yunhao Tang, Krzysztof Choromanski, Tamás Sarlós, Adrian Weller
2019	J	`jnl`	Orthogonal Estimation of Wasserstein Distances. CoRR Mark Rowland, Jiri Hron, Yunhao Tang, Krzysztof Choromanski, Tamás Sarlós, Adrian Weller
2019	J	`jnl`	Reinforcement Learning with Chromatic Networks. CoRR Xingyou Song, Krzysztof Choromanski, Jack Parker-Holder, Yunhao Tang, Wenbo Gao, Aldo Pacchiano, Tamás Sarlós, Deepali Jain, Yuxiang Yang
2019	A*	`conf`	Tight Dimensionality Reduction for Sketching Low Degree Polynomial Kernels. NeurIPS Michela Meister, Tamás Sarlós, David P. Woodruff
2018	A*	`conf`	Geometrically Coupled Monte Carlo Sampling. NeurIPS Mark Rowland, Krzysztof Choromanski, François Chalus, Aldo Pacchiano, Tamás Sarlós, Richard E. Turner, Adrian Weller
2018	A	`conf`	Orienteering Algorithms for Generating Travel Itineraries. WSDM Zachary Friggstad, Sreenivas Gollapudi, Kostas Kollias, Tamás Sarlós, Chaitanya Swamy, Andrew Tomkins
2018	A	`conf`	The Geometry of Random Features. AISTATS Krzysztof Choromanski, Mark Rowland, Tamás Sarlós, Vikas Sindhwani, Richard E. Turner, Adrian Weller
2017	—	`conf`	Caching with Dual Costs. WWW (Companion Volume) Anirban Dasgupta, Ravi Kumar, Tamás Sarlós
2017	A*	`conf`	Linear Additive Markov Processes. WWW Ravi Kumar, Maithra Raghu, Tamás Sarlós, Andrew Tomkins
2017	J	`jnl`	Linear Additive Markov Processes. CoRR Ravi Kumar, Maithra Raghu, Tamás Sarlós, Andrew Tomkins
2017	A	`conf`	Structured adaptive and random spinners for fast machine learning computations. AISTATS Mariusz Bojarski, Anna Choromanska, Krzysztof Choromanski, Francois Fagan, Cédric Gouy-Pailler, Anne Morvan, Nourhan Sakr, Tamás Sarlós, Jamal Atif
2016	A*	`conf`	On Sampling Nodes in a Network. WWW Flavio Chierichetti, Anirban Dasgupta, Ravi Kumar, Silvio Lattanzi, Tamás Sarlós
2016	J	`jnl`	Structured adaptive and random spinners for fast machine learning computations. CoRR Mariusz Bojarski, Anna Choromanska, Krzysztof Choromanski, Francois Fagan, Cédric Gouy-Pailler, Anne Morvan, Nourhan Sakr, Tamás Sarlós, Jamal Atif
2016	J	`jnl`	TripleSpin - a generic compact paradigm for fast machine learning computations. CoRR Krzysztof Choromanski, Francois Fagan, Cédric Gouy-Pailler, Anne Morvan, Tamás Sarlós, Jamal Atif
2014	J	`jnl`	Fastfood: Approximate Kernel Expansions in Loglinear Time. CoRR Quoc Viet Le, Tamás Sarlós, Alexander Johannes Smola
2014	A*	`conf`	On estimating the average degree. WWW Anirban Dasgupta, Ravi Kumar, Tamás Sarlós
2013	—	`conf`	Fastfood - Computing Hilbert Space Expansions in loglinear time. ICML (3) Quoc V. Le, Tamás Sarlós, Alexander J. Smola
2013	A*	`conf`	Optimal hashing schemes for entity matching. WWW Nilesh N. Dalvi, Vibhor Rastogi, Anirban Dasgupta, Anish Das Sarma, Tamás Sarlós
2013	A	`conf`	Permutation indexing: fast approximate retrieval from large corpora. CIKM Maxim Gurevich, Tamás Sarlós
2012	A*	`conf`	Are web users really Markovian? WWW Flavio Chierichetti, Ravi Kumar, Prabhakar Raghavan, Tamás Sarlós
2011	A*	`conf`	Fast locality-sensitive hashing. KDD Anirban Dasgupta, Ravi Kumar, Tamás Sarlós
2011	J	`jnl`	Faster least squares approximation. Numerische Mathematik Petros Drineas, Michael W. Mahoney, S. Muthukrishnan, Tamás Sarlós
2011	A*	`conf`	Mining tags using social endorsement networks. SIGIR Theodoros Lappas, Kunal Punera, Tamás Sarlós
2011	B	`conf`	On scheduling in map-reduce and flow-shops. SPAA Benjamin Moseley, Anirban Dasgupta, Ravi Kumar, Tamás Sarlós
2010	J	`jnl`	A Sparse Johnson--Lindenstrauss Transform CoRR Anirban Dasgupta, Ravi Kumar, Tamás Sarlós
2010	A*	`conf`	A sparse Johnson: Lindenstrauss transform. STOC Anirban Dasgupta, Ravi Kumar, Tamás Sarlós
2007	J	`jnl`	Faster Least Squares Approximation CoRR Petros Drineas, Michael W. Mahoney, S. Muthukrishnan, Tamás Sarlós
2007	—	`conf`	Web Spam Detection via Commercial Intent Analysis. AIRWeb András A. Benczúr, István Bíró, Károly Csalogány, Tamás Sarlós
2006	A*	`conf`	Improved Approximation Algorithms for Large Matrices via Random Projections. FOCS Tamás Sarlós
2006	—	`conf`	Link-Based Similarity Search to Fight Web Spam. AIRWeb András A. Benczúr, Károly Csalogány, Tamás Sarlós
2006	A*	`conf`	To randomize or not to randomize: space optimal summaries for hyperlink analysis. WWW Tamás Sarlós, András A. Benczúr, Károly Csalogány, Dániel Fogaras, Balázs Rácz
2005	—	`conf`	On the feasibility of low-rank approximation for personalized PageRank. WWW (Special interest tracks and posters) András A. Benczúr, Károly Csalogány, Tamás Sarlós
2005	—	`conf`	SpamRank -- Fully Automatic Link Spam Detection. AIRWeb András A. Benczúr, Károly Csalogány, Tamás Sarlós, Máté Uher
2005	J	`jnl`	Towards Scaling Fully Personalized PageRank: Algorithms, Lower Bounds, and Experiments. Internet Math. Dániel Fogaras, Balázs Rácz, Károly Csalogány, Tamás Sarlós
2003	—	`conf`	Searching a Small National Domain - Preliminary Report. WWW (Posters) András A. Benczúr, Tamás Sarlós, Máté Uher, Eszter Windhager