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2020 – today
- 2024
[c41]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: 2278-2286- [c40]Edith Cohen, Xin Lyu, Jelani Nelson, Tamás Sarlós, Uri Stemmer:
Lower Bounds for Differential Privacy Under Continual Observation and Online Threshold Queries. COLT 2024: 1200-1222 - [c39]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: 6920-6927 - [i28]Edith Cohen, Xin Lyu, Jelani Nelson, Tamás Sarlós, Uri Stemmer:
Lower Bounds for Differential Privacy Under Continual Observation and Online Threshold Queries. CoRR abs/2403.00028 (2024) - [i27]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 abs/2406.15881 (2024) - [i26]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: 373 (2024) - 2023
- [c38]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: 7235-7243 - [c37]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: 5978-6004 - [c36]Edith Cohen, Xin Lyu, Jelani Nelson, Tamás Sarlós, Uri Stemmer:
Generalized Private Selection and Testing with High Confidence. ITCS 2023: 39:1-39:23 - [c35]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 - [c34]Tamás Sarlós, Xingyou Song, David P. Woodruff, Richard Zhang:
Hardness of Low Rank Approximation of Entrywise Transformed Matrix Products. NeurIPS 2023 - [c33]Edith Cohen, Xin Lyu, Jelani Nelson, Tamás Sarlós, Uri Stemmer:
Optimal Differentially Private Learning of Thresholds and Quasi-Concave Optimization. STOC 2023: 472-482 - [i25]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 abs/2302.00787 (2023) - [i24]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 abs/2302.00942 (2023) - [i23]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 abs/2302.01925 (2023) - [i22]Tamás Sarlós, Xingyou Song, David P. Woodruff, Qiuyi Zhang:
Hardness of Low Rank Approximation of Entrywise Transformed Matrix Products. CoRR abs/2311.01960 (2023) - [i21]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 abs/2312.01990 (2023) - [i20]Edith Cohen, Xin Lyu, Jelani Nelson, Tamás Sarlós, Uri Stemmer:
Hot PATE: Private Aggregation of Distributions for Diverse Task. CoRR abs/2312.02132 (2023) - 2022
- [c32]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: 3962-3983 - [c31]Edith Cohen, Xin Lyu, Jelani Nelson, Tamás Sarlós, Moshe Shechner, Uri Stemmer:
On the Robustness of CountSketch to Adaptive Inputs. ICML 2022: 4112-4140 - [c30]Valerii Likhosherstov, Krzysztof Marcin Choromanski, Kumar Avinava Dubey, Frederick Liu, Tamás Sarlós, Adrian Weller:
Chefs' Random Tables: Non-Trigonometric Random Features. NeurIPS 2022 - [i19]Edith Cohen, Xin Lyu, Jelani Nelson, Tamás Sarlós, Moshe Shechner, Uri Stemmer:
On the Robustness of CountSketch to Adaptive Inputs. CoRR abs/2202.13736 (2022) - [i18]Valerii Likhosherstov, Krzysztof Choromanski, Avinava Dubey, Frederick Liu, Tamás Sarlós, Adrian Weller:
Chefs' Random Tables: Non-Trigonometric Random Features. CoRR abs/2205.15317 (2022) - [i17]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 abs/2207.00956 (2022) - [i16]Edith Cohen, Xin Lyu, Jelani Nelson, Tamás Sarlós, Uri Stemmer:
Õptimal Differentially Private Learning of Thresholds and Quasi-Concave Optimization. CoRR abs/2211.06387 (2022) - [i15]Edith Cohen, Xin Lyu, Jelani Nelson, Tamás Sarlós, Uri Stemmer:
Generalized Private Selection and Testing with High Confidence. CoRR abs/2211.12063 (2022) - 2021
- [c29]Edith Cohen, Ofir Geri, Tamás Sarlós, Uri Stemmer:
Differentially Private Weighted Sampling. AISTATS 2021: 2404-2412 - [c28]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 - [i14]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 abs/2101.07415 (2021) - 2020
- [c27]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: 1918-1928 - [i13]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 abs/2003.13563 (2020) - [i12]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 abs/2006.03555 (2020) - [i11]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 abs/2009.14794 (2020) - [i10]Edith Cohen, Ofir Geri, Tamás Sarlós, Uri Stemmer:
Differentially Private Weighted Sampling. CoRR abs/2010.13048 (2020)
2010 – 2019
- 2019
- [c26]Mark Rowland, Jiri Hron, Yunhao Tang, Krzysztof Choromanski, Tamás Sarlós, Adrian Weller:
Orthogonal Estimation of Wasserstein Distances. AISTATS 2019: 186-195 - [c25]Ashok Cutkosky, Tamás Sarlós:
Matrix-Free Preconditioning in Online Learning. ICML 2019: 1455-1464 - [c24]Michela Meister, Tamás Sarlós, David P. Woodruff:
Tight Dimensionality Reduction for Sketching Low Degree Polynomial Kernels. NeurIPS 2019: 9470-9481 - [i9]Mark Rowland, Jiri Hron, Yunhao Tang, Krzysztof Choromanski, Tamás Sarlós, Adrian Weller:
Orthogonal Estimation of Wasserstein Distances. CoRR abs/1903.03784 (2019) - [i8]Ashok Cutkosky, Tamás Sarlós:
Matrix-Free Preconditioning in Online Learning. CoRR abs/1905.12721 (2019) - [i7]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 abs/1907.06511 (2019) - 2018
- [c23]Krzysztof Choromanski, Mark Rowland, Tamás Sarlós, Vikas Sindhwani, Richard E. Turner, Adrian Weller:
The Geometry of Random Features. AISTATS 2018: 1-9 - [c22]Mark Rowland, Krzysztof Choromanski, François Chalus, Aldo Pacchiano, Tamás Sarlós, Richard E. Turner, Adrian Weller:
Geometrically Coupled Monte Carlo Sampling. NeurIPS 2018: 195-205 - [c21]Zachary Friggstad, Sreenivas Gollapudi, Kostas Kollias, Tamás Sarlós, Chaitanya Swamy, Andrew Tomkins:
Orienteering Algorithms for Generating Travel Itineraries. WSDM 2018: 180-188 - 2017
- [c20]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: 1020-1029 - [c19]Ravi Kumar, Maithra Raghu, Tamás Sarlós, Andrew Tomkins:
Linear Additive Markov Processes. WWW 2017: 411-419 - [c18]Anirban Dasgupta, Ravi Kumar, Tamás Sarlós:
Caching with Dual Costs. WWW (Companion Volume) 2017: 643-652 - [i6]Ravi Kumar, Maithra Raghu, Tamás Sarlós, Andrew Tomkins:
Linear Additive Markov Processes. CoRR abs/1704.01255 (2017) - 2016
- [c17]Flavio Chierichetti, Anirban Dasgupta, Ravi Kumar, Silvio Lattanzi, Tamás Sarlós:
On Sampling Nodes in a Network. WWW 2016: 471-481 - [i5]Krzysztof Choromanski, Francois Fagan, Cédric Gouy-Pailler, Anne Morvan, Tamás Sarlós, Jamal Atif:
TripleSpin - a generic compact paradigm for fast machine learning computations. CoRR abs/1605.09046 (2016) - [i4]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 abs/1610.06209 (2016) - 2014
- [c16]Anirban Dasgupta, Ravi Kumar, Tamás Sarlós:
On estimating the average degree. WWW 2014: 795-806 - [i3]Quoc Viet Le, Tamás Sarlós, Alexander Johannes Smola:
Fastfood: Approximate Kernel Expansions in Loglinear Time. CoRR abs/1408.3060 (2014) - 2013
- [c15]Maxim Gurevich, Tamás Sarlós:
Permutation indexing: fast approximate retrieval from large corpora. CIKM 2013: 1771-1776 - [c14]Quoc V. Le, Tamás Sarlós, Alexander J. Smola:
Fastfood - Computing Hilbert Space Expansions in loglinear time. ICML (3) 2013: 244-252 - [c13]Nilesh N. Dalvi, Vibhor Rastogi, Anirban Dasgupta, Anish Das Sarma, Tamás Sarlós:
Optimal hashing schemes for entity matching. WWW 2013: 295-306 - 2012
- [c12]Flavio Chierichetti, Ravi Kumar, Prabhakar Raghavan, Tamás Sarlós:
Are web users really Markovian? WWW 2012: 609-618 - 2011
- [j2]Petros Drineas, Michael W. Mahoney, S. Muthukrishnan, Tamás Sarlós:
Faster least squares approximation. Numerische Mathematik 117(2): 219-249 (2011) - [c11]Anirban Dasgupta, Ravi Kumar, Tamás Sarlós:
Fast locality-sensitive hashing. KDD 2011: 1073-1081 - [c10]Theodoros Lappas, Kunal Punera, Tamás Sarlós:
Mining tags using social endorsement networks. SIGIR 2011: 195-204 - [c9]Benjamin Moseley, Anirban Dasgupta, Ravi Kumar, Tamás Sarlós:
On scheduling in map-reduce and flow-shops. SPAA 2011: 289-298 - 2010
- [c8]Anirban Dasgupta, Ravi Kumar, Tamás Sarlós:
A sparse Johnson: Lindenstrauss transform. STOC 2010: 341-350 - [i2]Anirban Dasgupta, Ravi Kumar, Tamás Sarlós:
A Sparse Johnson--Lindenstrauss Transform. CoRR abs/1004.4240 (2010)
2000 – 2009
- 2007
- [c7]András A. Benczúr, István Bíró, Károly Csalogány, Tamás Sarlós:
Web Spam Detection via Commercial Intent Analysis. AIRWeb 2007: 89-92 - [i1]Petros Drineas, Michael W. Mahoney, S. Muthukrishnan, Tamás Sarlós:
Faster Least Squares Approximation. CoRR abs/0710.1435 (2007) - 2006
- [c6]András A. Benczúr, Károly Csalogány, Tamás Sarlós:
Link-Based Similarity Search to Fight Web Spam. AIRWeb 2006: 9-16 - [c5]Tamás Sarlós:
Improved Approximation Algorithms for Large Matrices via Random Projections. FOCS 2006: 143-152 - [c4]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: 297-306 - 2005
- [j1]Dániel Fogaras, Balázs Rácz, Károly Csalogány, Tamás Sarlós:
Towards Scaling Fully Personalized PageRank: Algorithms, Lower Bounds, and Experiments. Internet Math. 2(3): 333-358 (2005) - [c3]András A. Benczúr, Károly Csalogány, Tamás Sarlós, Máté Uher:
SpamRank -- Fully Automatic Link Spam Detection. AIRWeb 2005: 25-38 - [c2]András A. Benczúr, Károly Csalogány, Tamás Sarlós:
On the feasibility of low-rank approximation for personalized PageRank. WWW (Special interest tracks and posters) 2005: 972-973 - 2003
- [c1]András A. Benczúr, Tamás Sarlós, Máté Uher, Eszter Windhager:
Searching a Small National Domain - Preliminary Report. WWW (Posters) 2003
Coauthor Index
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last updated on 2024-10-07 21:25 CEST by the dblp team
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