default search action
Google
Google Scholar
Semantic Scholar
Internet Archive Scholar
CiteSeerX
ORCIDThomas Steinke 0002
Person information
- affiliation: Google, Mountain View, CA, USA
- affiliation: IBM Almaden Research Center, San Jose, CA, USA
- affiliation (PhD 2016): Harvard University, School of Engineering and Applied Sciences, Cambridge, MA, USA
- affiliation: University of Canterbury, Department of Mathematics and Statistics, Christchurch, New Zealand
Other persons with the same name
- Thomas Steinke 0001
![[0000-0002-0338-8042]](/post-https-dblp.org/img/orcid-mark.12x12.png "0000-0002-0338-8042")
— Zuse Institute Berlin (ZIB), Germany - Thomas Steinke 0003 — California Polytechnic State University, San Jose, CA, USA
SPARQL queries 
Refine list
refinements active!
zoomed in on ?? of ?? records
view refined list in
export refined list as
showing all ?? records
2020 – today
- 2025
[c49]Christopher A. Choquette-Choo, Arun Ganesh, Saminul Haque, Thomas Steinke, Abhradeep Guha Thakurta:
Near-Exact Privacy Amplification for Matrix Mechanisms. ICLR 2025- [c48]Milad Nasr, Thomas Steinke, Borja Balle, Christopher A. Choquette-Choo, Arun Ganesh, Matthew Jagielski, Jamie Hayes, Abhradeep Guha Thakurta, Adam Smith, Andreas Terzis:
The Last Iterate Advantage: Empirical Auditing and Principled Heuristic Analysis of Differentially Private SGD. ICLR 2025 - [c47]Christian Janos Lebeda, Matthew Regehr, Gautam Kamath, Thomas Steinke:
Avoiding Pitfalls for Privacy Accounting of Subsampled Mechanisms Under Composition. SaTML 2025: 996-1006 - [c46]Borja Balle, James Bell-Clark, Albert Cheu, Adrià Gascón, Jonathan Katz, Mariana Raykova, Phillipp Schoppmann, Thomas Steinke:
Hash-Prune-Invert: Improved Differentially Private Heavy-Hitter Detection in the Two-Server Model. SP 2025: 2903-2918 - [c45]Ephraim Linder, Sofya Raskhodnikova, Adam Smith, Thomas Steinke:
Privately Evaluating Untrusted Black-Box Functions. STOC 2025: 2350-2361 - [i61]Ephraim Linder, Sofya Raskhodnikova, Adam Smith, Thomas Steinke:
Privately Evaluating Untrusted Black-Box Functions. CoRR abs/2503.19268 (2025) - [i60]Arun Ganesh, Brendan McMahan, Milad Nasr, Thomas Steinke, Abhradeep Thakurta:
Hush! Protecting Secrets During Model Training: An Indistinguishability Approach. CoRR abs/2506.00201 (2025) - [i59]Krishna Pillutla, Jalaj Upadhyay, Christopher A. Choquette-Choo, Krishnamurthy Dvijotham, Arun Ganesh, Monika Henzinger, Jonathan Katz, Ryan McKenna, H. Brendan McMahan, Keith Rush, Thomas Steinke, Abhradeep Thakurta:
Correlated Noise Mechanisms for Differentially Private Learning. CoRR abs/2506.08201 (2025) - [i58]Günter F. Steinke, Thomas Steinke:
Privately Estimating Black-Box Statistics. CoRR abs/2510.00322 (2025) - 2024
- [j10]Bing Zhang, Vadym Doroshenko, Peter Kairouz, Thomas Steinke, Abhradeep Thakurta, Ziyin Ma, Eidan Cohen, Himani Apte, Jodi Spacek:
Differentially Private Stream Processing at Scale. Proc. VLDB Endow. 17(12): 4145-4158 (2024) - [c44]Christopher A. Choquette-Choo, Krishnamurthy Dj Dvijotham, Krishna Pillutla, Arun Ganesh, Thomas Steinke, Abhradeep Guha Thakurta:
Correlated Noise Provably Beats Independent Noise for Differentially Private Learning. ICLR 2024 - [c43]Christopher A. Choquette-Choo, Arun Ganesh, Thomas Steinke, Abhradeep Guha Thakurta:
Privacy Amplification for Matrix Mechanisms. ICLR 2024 - [c42]Nicholas Carlini, Daniel Paleka, Krishnamurthy Dj Dvijotham, Thomas Steinke, Jonathan Hayase, A. Feder Cooper, Katherine Lee, Matthew Jagielski, Milad Nasr, Arthur Conmy, Eric Wallace, David Rolnick, Florian Tramèr:
Stealing part of a production language model. ICML 2024: 5680-5705 - [c41]Maryam Aliakbarpour, Rose Silver, Thomas Steinke, Jonathan R. Ullman:
Differentially Private Medians and Interior Points for Non-Pathological Data. ITCS 2024: 3:1-3:21 - [c40]Mahdi Haghifam, Thomas Steinke, Jonathan R. Ullman:
Private Geometric Median. NeurIPS 2024 - [i57]Nicholas Carlini, Daniel Paleka, Krishnamurthy (Dj) Dvijotham, Thomas Steinke, Jonathan Hayase, A. Feder Cooper, Katherine Lee, Matthew Jagielski, Milad Nasr, Arthur Conmy, Eric Wallace, David Rolnick, Florian Tramèr:
Stealing Part of a Production Language Model. CoRR abs/2403.06634 (2024) - [i56]Krishnamurthy Dvijotham, H. Brendan McMahan, Krishna Pillutla, Thomas Steinke, Abhradeep Thakurta:
Efficient and Near-Optimal Noise Generation for Streaming Differential Privacy. CoRR abs/2404.16706 (2024) - [i55]Christian Janos Lebeda, Matthew Regehr, Gautam Kamath, Thomas Steinke:
Avoiding Pitfalls for Privacy Accounting of Subsampled Mechanisms under Composition. CoRR abs/2405.20769 (2024) - [i54]Mahdi Haghifam, Thomas Steinke, Jonathan R. Ullman:
Private Geometric Median. CoRR abs/2406.07407 (2024) - [i53]Thomas Steinke, Milad Nasr, Arun Ganesh, Borja Balle, Christopher A. Choquette-Choo, Matthew Jagielski, Jamie Hayes, Abhradeep Guha Thakurta, Adam Smith, Andreas Terzis:
The Last Iterate Advantage: Empirical Auditing and Principled Heuristic Analysis of Differentially Private SGD. CoRR abs/2410.06186 (2024) - [i52]Christopher A. Choquette-Choo, Arun Ganesh, Saminul Haque, Thomas Steinke, Abhradeep Thakurta:
Near Exact Privacy Amplification for Matrix Mechanisms. CoRR abs/2410.06266 (2024) - [i51]Borja Balle, James Bell, Albert Cheu, Adrià Gascón, Jonathan Katz, Mariana Raykova, Phillipp Schoppmann, Thomas Steinke:
Hash-Prune-Invert: Improved Differentially Private Heavy-Hitter Detection in the Two-Server Model. IACR Cryptol. ePrint Arch. 2024: 2024 (2024) - 2023
- [c39]Arun Ganesh, Mahdi Haghifam, Milad Nasr, Sewoong Oh, Thomas Steinke, Om Thakkar, Abhradeep Guha Thakurta, Lun Wang:
Why Is Public Pretraining Necessary for Private Model Training? ICML 2023: 10611-10627 - [c38]Badih Ghazi, Ravi Kumar, Pasin Manurangsi, Thomas Steinke:
Algorithms with More Granular Differential Privacy Guarantees. ITCS 2023: 54:1-54:24 - [c37]Thomas Steinke, Alexander Knop:
Counting Distinct Elements Under Person-Level Differential Privacy. NeurIPS 2023 - [c36]Thomas Steinke, Milad Nasr, Matthew Jagielski:
Privacy Auditing with One (1) Training Run. NeurIPS 2023 - [c35]Arun Ganesh, Mahdi Haghifam, Thomas Steinke, Abhradeep Guha Thakurta:
Faster Differentially Private Convex Optimization via Second-Order Methods. NeurIPS 2023 - [c34]Milad Nasr, Jamie Hayes, Thomas Steinke, Borja Balle, Florian Tramèr, Matthew Jagielski, Nicholas Carlini, Andreas Terzis:
Tight Auditing of Differentially Private Machine Learning. USENIX Security Symposium 2023: 1631-1648 - [i50]Gautam Kamath, Argyris Mouzakis, Matthew Regehr, Vikrant Singhal, Thomas Steinke, Jonathan R. Ullman:
A Bias-Variance-Privacy Trilemma for Statistical Estimation. CoRR abs/2301.13334 (2023) - [i49]Milad Nasr, Jamie Hayes, Thomas Steinke, Borja Balle, Florian Tramèr, Matthew Jagielski, Nicholas Carlini, Andreas Terzis:
Tight Auditing of Differentially Private Machine Learning. CoRR abs/2302.07956 (2023) - [i48]Arun Ganesh, Mahdi Haghifam, Milad Nasr, Sewoong Oh, Thomas Steinke, Om Thakkar, Abhradeep Thakurta, Lun Wang:
Why Is Public Pretraining Necessary for Private Model Training? CoRR abs/2302.09483 (2023) - [i47]Bing Zhang, Vadym Doroshenko, Peter Kairouz, Thomas Steinke, Abhradeep Thakurta, Ziyin Ma, Himani Apte, Jodi Spacek:
Differentially Private Stream Processing at Scale. CoRR abs/2303.18086 (2023) - [i46]Thomas Steinke, Milad Nasr, Matthew Jagielski:
Privacy Auditing with One (1) Training Run. CoRR abs/2305.08846 (2023) - [i45]Arun Ganesh, Mahdi Haghifam, Thomas Steinke, Abhradeep Thakurta:
Faster Differentially Private Convex Optimization via Second-Order Methods. CoRR abs/2305.13209 (2023) - [i44]Maryam Aliakbarpour, Rose Silver, Thomas Steinke, Jonathan R. Ullman:
Differentially Private Medians and Interior Points for Non-Pathological Data. CoRR abs/2305.13440 (2023) - [i43]Alexander Knop, Thomas Steinke:
Counting Distinct Elements Under Person-Level Differential Privacy. CoRR abs/2308.12947 (2023) - [i42]Christopher A. Choquette-Choo, Krishnamurthy Dvijotham, Krishna Pillutla, Arun Ganesh, Thomas Steinke, Abhradeep Thakurta:
Correlated Noise Provably Beats Independent Noise for Differentially Private Learning. CoRR abs/2310.06771 (2023) - [i41]Christopher A. Choquette-Choo, Arun Ganesh, Thomas Steinke, Abhradeep Thakurta:
Privacy Amplification for Matrix Mechanisms. CoRR abs/2310.15526 (2023) - 2022
- [j9]Clément L. Canonne, Gautam Kamath, Thomas Steinke:
Discrete Gaussian for Differential Privacy. J. Priv. Confidentiality 12(1) (2022) - [c33]Gautam Kamath, Argyris Mouzakis, Vikrant Singhal, Thomas Steinke, Jonathan R. Ullman:
A Private and Computationally-Efficient Estimator for Unbounded Gaussians. COLT 2022: 544-572 - [c32]Nicolas Papernot, Thomas Steinke:
Hyperparameter Tuning with Renyi Differential Privacy. ICLR 2022 - [c31]Ehsan Amid, Arun Ganesh, Rajiv Mathews, Swaroop Ramaswamy, Shuang Song, Thomas Steinke, Vinith M. Suriyakumar, Om Thakkar, Abhradeep Thakurta:
Public Data-Assisted Mirror Descent for Private Model Training. ICML 2022: 517-535 - [i40]Florian Tramèr, Andreas Terzis, Thomas Steinke, Shuang Song, Matthew Jagielski, Nicholas Carlini:
Debugging Differential Privacy: A Case Study for Privacy Auditing. CoRR abs/2202.12219 (2022) - [i39]Badih Ghazi, Ravi Kumar, Pasin Manurangsi, Thomas Steinke:
Algorithms with More Granular Differential Privacy Guarantees. CoRR abs/2209.04053 (2022) - [i38]Thomas Steinke:
Composition of Differential Privacy & Privacy Amplification by Subsampling. CoRR abs/2210.00597 (2022) - 2021
- [j8]Raef Bassily, Kobbi Nissim, Adam D. Smith, Thomas Steinke, Uri Stemmer, Jonathan R. Ullman:
Algorithmic Stability for Adaptive Data Analysis. SIAM J. Comput. 50(3) (2021) - [j7]Mark Bun, Gautam Kamath, Thomas Steinke, Zhiwei Steven Wu:
Private Hypothesis Selection. IEEE Trans. Inf. Theory 67(3): 1981-2000 (2021) - [c30]Shuang Song, Thomas Steinke, Om Thakkar, Abhradeep Thakurta:
Evading the Curse of Dimensionality in Unconstrained Private GLMs. AISTATS 2021: 2638-2646 - [c29]Peter Grünwald, Thomas Steinke, Lydia Zakynthinou:
PAC-Bayes, MAC-Bayes and Conditional Mutual Information: Fast rate bounds that handle general VC classes. COLT 2021: 2217-2247 - [c28]Peter Kairouz, Ziyu Liu, Thomas Steinke:
The Distributed Discrete Gaussian Mechanism for Federated Learning with Secure Aggregation. ICML 2021: 5201-5212 - [c27]Terrance Liu, Giuseppe Vietri, Thomas Steinke, Jonathan R. Ullman, Zhiwei Steven Wu:
Leveraging Public Data for Practical Private Query Release. ICML 2021: 6968-6977 - [c26]Vikrant Singhal, Thomas Steinke:
Privately Learning Subspaces. NeurIPS 2021: 1312-1324 - [i37]Peter Kairouz, Ziyu Liu, Thomas Steinke:
The Distributed Discrete Gaussian Mechanism for Federated Learning with Secure Aggregation. CoRR abs/2102.06387 (2021) - [i36]Terrance Liu, Giuseppe Vietri, Thomas Steinke, Jonathan R. Ullman, Zhiwei Steven Wu:
Leveraging Public Data for Practical Private Query Release. CoRR abs/2102.08598 (2021) - [i35]Zeyu Ding, Daniel Kifer, Sayed M. Saghaian N. E., Thomas Steinke, Yuxin Wang, Yingtai Xiao, Danfeng Zhang:
The Permute-and-Flip Mechanism is Identical to Report-Noisy-Max with Exponential Noise. CoRR abs/2105.07260 (2021) - [i34]Vikrant Singhal, Thomas Steinke:
Privately Learning Subspaces. CoRR abs/2106.00001 (2021) - [i33]Peter Grünwald, Thomas Steinke, Lydia Zakynthinou:
PAC-Bayes, MAC-Bayes and Conditional Mutual Information: Fast rate bounds that handle general VC classes. CoRR abs/2106.09683 (2021) - [i32]Nicolas Papernot, Thomas Steinke:
Hyperparameter Tuning with Renyi Differential Privacy. CoRR abs/2110.03620 (2021) - [i31]Gautam Kamath, Argyris Mouzakis, Vikrant Singhal, Thomas Steinke, Jonathan R. Ullman:
A Private and Computationally-Efficient Estimator for Unbounded Gaussians. CoRR abs/2111.04609 (2021) - [i30]Ehsan Amid, Arun Ganesh, Rajiv Mathews, Swaroop Ramaswamy, Shuang Song, Thomas Steinke, Vinith M. Suriyakumar, Om Thakkar, Abhradeep Thakurta:
Public Data-Assisted Mirror Descent for Private Model Training. CoRR abs/2112.00193 (2021) - 2020
- [c25]Thomas Steinke, Lydia Zakynthinou:
Reasoning About Generalization via Conditional Mutual Information. COLT 2020: 3437-3452 - [c24]Thomas Steinke, Lydia Zakynthinou:
Open Problem: Information Complexity of VC Learning. COLT 2020: 3857-3863 - [c23]Giuseppe Vietri, Grace Tian, Mark Bun, Thomas Steinke, Zhiwei Steven Wu:
New Oracle-Efficient Algorithms for Private Synthetic Data Release. ICML 2020: 9765-9774 - [c22]Clément L. Canonne, Gautam Kamath, Thomas Steinke:
The Discrete Gaussian for Differential Privacy. NeurIPS 2020 - [i29]Thomas Steinke, Lydia Zakynthinou:
Reasoning About Generalization via Conditional Mutual Information. CoRR abs/2001.09122 (2020) - [i28]Clément L. Canonne, Gautam Kamath, Thomas Steinke:
The Discrete Gaussian for Differential Privacy. CoRR abs/2004.00010 (2020) - [i27]Giuseppe Vietri, Grace Tian, Mark Bun, Thomas Steinke, Zhiwei Steven Wu:
New Oracle-Efficient Algorithms for Private Synthetic Data Release. CoRR abs/2007.05453 (2020) - [i26]Thomas Steinke:
Multi-Central Differential Privacy. CoRR abs/2009.05401 (2020)
2010 – 2019
- 2019
- [j6]Stacey Truex, Nathalie Baracaldo, Ali Anwar, Thomas Steinke, Heiko Ludwig, Rui Zhang, Yi Zhou:
A Hybrid Approach to Privacy-Preserving Federated Learning - (Extended Abstract). Inform. Spektrum 42(5): 356-357 (2019) - [j5]Mark Bun, Thomas Steinke, Jonathan R. Ullman:
Make Up Your Mind: The Price of Online Queries in Differential Privacy. J. Priv. Confidentiality 9(1) (2019) - [c21]Stacey Truex, Nathalie Baracaldo, Ali Anwar, Thomas Steinke, Heiko Ludwig, Rui Zhang, Yi Zhou:
A Hybrid Approach to Privacy-Preserving Federated Learning. AISec@CCS 2019: 1-11 - [c20]Mark Bun, Gautam Kamath, Thomas Steinke, Zhiwei Steven Wu:
Private Hypothesis Selection. NeurIPS 2019: 156-167 - [c19]Mark Bun, Thomas Steinke:
Average-Case Averages: Private Algorithms for Smooth Sensitivity and Mean Estimation. NeurIPS 2019: 181-191 - [c18]Jaroslaw Blasiok, Mark Bun, Aleksandar Nikolov, Thomas Steinke:
Towards Instance-Optimal Private Query Release. SODA 2019: 2480-2497 - [i25]Mark Bun, Gautam Kamath, Thomas Steinke, Zhiwei Steven Wu:
Private Hypothesis Selection. CoRR abs/1905.13229 (2019) - [i24]Mark Bun, Thomas Steinke:
Average-Case Averages: Private Algorithms for Smooth Sensitivity and Mean Estimation. CoRR abs/1906.02830 (2019) - 2018
- [c17]Vitaly Feldman, Thomas Steinke:
Calibrating Noise to Variance in Adaptive Data Analysis. COLT 2018: 535-544 - [c16]Jonathan R. Ullman, Adam D. Smith, Kobbi Nissim, Uri Stemmer, Thomas Steinke:
The Limits of Post-Selection Generalization. NeurIPS 2018: 6402-6411 - [c15]Mark Bun, Cynthia Dwork, Guy N. Rothblum, Thomas Steinke:
Composable and versatile privacy via truncated CDP. STOC 2018: 74-86 - [i23]Kobbi Nissim, Adam D. Smith, Thomas Steinke, Uri Stemmer, Jonathan R. Ullman:
The Limits of Post-Selection Generalization. CoRR abs/1806.06100 (2018) - [i22]Jaroslaw Blasiok, Mark Bun, Aleksandar Nikolov, Thomas Steinke:
Towards Instance-Optimal Private Query Release. CoRR abs/1811.03763 (2018) - [i21]Stacey Truex, Nathalie Baracaldo, Ali Anwar, Thomas Steinke, Heiko Ludwig, Rui Zhang:
A Hybrid Approach to Privacy-Preserving Federated Learning. CoRR abs/1812.03224 (2018) - 2017
- [j4]Thomas Steinke, Salil P. Vadhan, Andrew Wan:
Pseudorandomness and Fourier-Growth Bounds for Width-3 Branching Programs. Theory Comput. 13(1): 1-50 (2017) - [c14]Vitaly Feldman, Thomas Steinke:
Generalization for Adaptively-chosen Estimators via Stable Median. COLT 2017: 728-757 - [c13]Thomas Steinke, Jonathan R. Ullman:
Tight Lower Bounds for Differentially Private Selection. FOCS 2017: 552-563 - [c12]Mark Bun, Thomas Steinke, Jonathan R. Ullman:
Make Up Your Mind: The Price of Online Queries in Differential Privacy. SODA 2017: 1306-1325 - [i20]Thomas Steinke, Jonathan R. Ullman:
Subgaussian Tail Bounds via Stability Arguments. CoRR abs/1701.03493 (2017) - [i19]Thomas Steinke, Jonathan R. Ullman:
Tight Lower Bounds for Differentially Private Selection. CoRR abs/1704.03024 (2017) - [i18]Vitaly Feldman, Thomas Steinke:
Generalization for Adaptively-chosen Estimators via Stable Median. CoRR abs/1706.05069 (2017) - [i17]Vitaly Feldman, Thomas Steinke:
Calibrating Noise to Variance in Adaptive Data Analysis. CoRR abs/1712.07196 (2017) - 2016
- [j3]Thomas Steinke, Jonathan R. Ullman:
Between Pure and Approximate Differential Privacy. J. Priv. Confidentiality 7(2) (2016) - [c11]Thomas Steinke, Jonathan R. Ullman:
Interactive fingerprinting codes and the hardness of preventing false discovery. ITA 2016: 1-41 - [c10]Raef Bassily, Kobbi Nissim, Adam D. Smith, Thomas Steinke, Uri Stemmer, Jonathan R. Ullman:
Algorithmic stability for adaptive data analysis. STOC 2016: 1046-1059 - [c9]Mark Bun, Thomas Steinke:
Concentrated Differential Privacy: Simplifications, Extensions, and Lower Bounds. TCC (B1) 2016: 635-658 - [i16]Mark Bun, Thomas Steinke, Jonathan R. Ullman:
Make Up Your Mind: The Price of Online Queries in Differential Privacy. CoRR abs/1604.04618 (2016) - [i15]Mark Bun, Thomas Steinke:
Concentrated Differential Privacy: Simplifications, Extensions, and Lower Bounds. CoRR abs/1605.02065 (2016) - [i14]Mark Bun, Thomas Steinke:
Concentrated Differential Privacy: Simplifications, Extensions, and Lower Bounds. IACR Cryptol. ePrint Arch. 2016: 816 (2016) - 2015
- [c8]Mark Bun, Thomas Steinke:
Weighted Polynomial Approximations: Limits for Learning and Pseudorandomness. APPROX-RANDOM 2015: 625-644 - [c7]Thomas Steinke, Jonathan R. Ullman:
Interactive Fingerprinting Codes and the Hardness of Preventing False Discovery. COLT 2015: 1588-1628 - [c6]Cynthia Dwork, Adam D. Smith, Thomas Steinke, Jonathan R. Ullman, Salil P. Vadhan:
Robust Traceability from Trace Amounts. FOCS 2015: 650-669 - [i13]Thomas Steinke, Jonathan R. Ullman:
Between Pure and Approximate Differential Privacy. CoRR abs/1501.06095 (2015) - [i12]Sitan Chen, Thomas Steinke, Salil P. Vadhan:
Pseudorandomness for Read-Once, Constant-Depth Circuits. CoRR abs/1504.04675 (2015) - [i11]Raef Bassily, Kobbi Nissim, Adam D. Smith, Thomas Steinke, Uri Stemmer, Jonathan R. Ullman:
Algorithmic Stability for Adaptive Data Analysis. CoRR abs/1511.02513 (2015) - 2014
- [j2]Varun Kanade, Thomas Steinke:
Learning Hurdles for Sleeping Experts. ACM Trans. Comput. Theory 6(3): 11:1-11:16 (2014) - [c5]Thomas Steinke, Salil P. Vadhan, Andrew Wan:
Pseudorandomness and Fourier Growth Bounds for Width-3 Branching Programs. APPROX-RANDOM 2014: 885-899 - [i10]Thomas Steinke, Salil P. Vadhan, Andrew Wan:
Pseudorandomness and Fourier Growth Bounds for Width 3 Branching Programs. CoRR abs/1405.7028 (2014) - [i9]Thomas Steinke, Jonathan R. Ullman:
Interactive Fingerprinting Codes and the Hardness of Preventing False Discovery. CoRR abs/1410.1228 (2014) - [i8]Mark Bun, Thomas Steinke:
Weighted Polynomial Approximations: Limits for Learning and Pseudorandomness. CoRR abs/1412.2457 (2014) - [i7]Mark Bun, Thomas Steinke:
Weighted Polynomial Approximations: Limits for Learning and Pseudorandomness. Electron. Colloquium Comput. Complex. TR14: Article TR14-166 (2014) - [i6]Thomas Steinke:
Pseudorandomness and Fourier Growth Bounds for Width 3 Branching Programs. Electron. Colloquium Comput. Complex. TR14: Article TR14-076 (2014) - 2013
- [j1]Raazesh Sainudiin, Thomas Steinke:
A Rigorous Extension of the Schönhage-Strassen Integer Multiplication Algorithm Using Complex Interval Arithmetic. Reliab. Comput. 18: 97-116 (2013) - [c4]Omer Reingold, Thomas Steinke, Salil P. Vadhan:
Pseudorandomness for Regular Branching Programs via Fourier Analysis. APPROX-RANDOM 2013: 655-670 - [i5]Omer Reingold, Thomas Steinke, Salil P. Vadhan:
Pseudorandomness for Regular Branching Programs via Fourier Analysis. CoRR abs/1306.3004 (2013) - [i4]Omer Reingold, Thomas Steinke, Salil P. Vadhan:
Pseudorandomness for Regular Branching Programs via Fourier Analysis. Electron. Colloquium Comput. Complex. TR13: Article TR13-086 (2013) - 2012
- [c3]Justin Thaler, Michael Mitzenmacher, Thomas Steinke:
Hierarchical Heavy Hitters with the Space Saving Algorithm. ALENEX 2012: 160-174 - [c2]Varun Kanade, Thomas Steinke:
Learning hurdles for sleeping experts. ITCS 2012: 11-18 - [i3]Thomas Steinke:
Pseudorandomness for Permutation Branching Programs Without the Group Theory. Electron. Colloquium Comput. Complex. TR12: Article TR12-083 (2012) - 2011
- [i2]Michael Mitzenmacher, Thomas Steinke, Justin Thaler:
Hierarchical Heavy Hitters with the Space Saving Algorithm. CoRR abs/1102.5540 (2011) - [i1]Varun Kanade, Thomas Steinke:
Learning Hurdles for Sleeping Experts. Electron. Colloquium Comput. Complex. TR11: Article TR11-115 (2011) - 2010
- [c1]Thomas Steinke, Raazesh Sainudiin:
A Rigorous Extension of the Schönhage-Strassen Integer Multiplication Algorithm Using Complex Interval Arithmetic. CCA 2010: 151-159
Coauthor Index
manage site settings
To protect your privacy, all features that rely on external API calls from your browser are turned off by default. You need to opt-in for them to become active. All settings here will be stored as cookies with your web browser. For more information see our F.A.Q.
Unpaywalled article links
Add open access links from 
to the list of external document links (if available).
Privacy notice: By enabling the option above, your browser will contact the API of unpaywall.org to load hyperlinks to open access articles. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Unpaywall privacy policy.
Archived links via Wayback Machine
For web page which are no longer available, try to retrieve content from the 
of the Internet Archive (if available).
Privacy notice: By enabling the option above, your browser will contact the API of archive.org to check for archived content of web pages that are no longer available. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Internet Archive privacy policy.
Reference lists
Add a list of references from 
, 
, and 
to record detail pages.
load references from crossref.org and opencitations.net
Privacy notice: By enabling the option above, your browser will contact the APIs of crossref.org, opencitations.net, and semanticscholar.org to load article reference information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Crossref privacy policy and the OpenCitations privacy policy, as well as the AI2 Privacy Policy covering Semantic Scholar.
Citation data
Add a list of citing articles from and to record detail pages.
load citations from opencitations.net
Privacy notice: By enabling the option above, your browser will contact the API of opencitations.net and semanticscholar.org to load citation information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the OpenCitations privacy policy as well as the AI2 Privacy Policy covering Semantic Scholar.
OpenAlex data
Load additional information about publications from 
.
Privacy notice: By enabling the option above, your browser will contact the API of openalex.org to load additional information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the information given by OpenAlex.
last updated on 2026-05-08 22:39 CEST by the dblp team
all metadata released as open data under CC0 1.0 license
see also: Terms of Use | Privacy Policy | Imprint
dblp was originally created in 1993 at:
since 2018, dblp has been operated and maintained by:
the dblp computer science bibliography is funded and supported by:
