default search action
Google
Google Scholar
Semantic Scholar
Internet Archive Scholar
CiteSeerX
ORCIDDimitris Tsipras
Person information
SPARQL queries 
Refine list
refinements active!
zoomed in on ?? of ?? records
view refined list in
export refined list as
2020 – today
- 2023
[j3]Micah Goldblum
, Dimitris Tsipras, Chulin Xie, Xinyun Chen, Avi Schwarzschild, Dawn Song, Aleksander Madry, Bo Li, Tom Goldstein:
Dataset Security for Machine Learning: Data Poisoning, Backdoor Attacks, and Defenses. IEEE Trans. Pattern Anal. Mach. Intell. 45(2): 1563-1580 (2023)- [j2]Percy Liang, Rishi Bommasani, Tony Lee, Dimitris Tsipras, Dilara Soylu, Michihiro Yasunaga, Yian Zhang, Deepak Narayanan, Yuhuai Wu, Ananya Kumar, Benjamin Newman, Binhang Yuan, Bobby Yan, Ce Zhang, Christian Cosgrove, Christopher D. Manning, Christopher Ré, Diana Acosta-Navas, Drew A. Hudson, Eric Zelikman, Esin Durmus, Faisal Ladhak, Frieda Rong, Hongyu Ren, Huaxiu Yao, Jue Wang, Keshav Santhanam, Laurel J. Orr, Lucia Zheng, Mert Yüksekgönül, Mirac Suzgun, Nathan Kim, Neel Guha, Niladri S. Chatterji, Omar Khattab, Peter Henderson, Qian Huang, Ryan Chi, Sang Michael Xie, Shibani Santurkar, Surya Ganguli, Tatsunori Hashimoto, Thomas Icard, Tianyi Zhang, Vishrav Chaudhary, William Wang, Xuechen Li, Yifan Mai, Yuhui Zhang, Yuta Koreeda:
Holistic Evaluation of Language Models. Trans. Mach. Learn. Res. 2023 (2023) - 2022
- [c17]Saachi Jain, Dimitris Tsipras, Aleksander Madry:
Combining Diverse Feature Priors. ICML 2022: 9802-9832 - [c16]Shivam Garg, Dimitris Tsipras, Percy Liang, Gregory Valiant:
What Can Transformers Learn In-Context? A Case Study of Simple Function Classes. NeurIPS 2022 - [i21]Shivam Garg, Dimitris Tsipras, Percy Liang, Gregory Valiant:
What Can Transformers Learn In-Context? A Case Study of Simple Function Classes. CoRR abs/2208.01066 (2022) - [i20]Percy Liang, Rishi Bommasani, Tony Lee, Dimitris Tsipras, Dilara Soylu, Michihiro Yasunaga, Yian Zhang, Deepak Narayanan, Yuhuai Wu, Ananya Kumar, Benjamin Newman, Binhang Yuan, Bobby Yan, Ce Zhang, Christian Cosgrove, Christopher D. Manning, Christopher Ré, Diana Acosta-Navas, Drew A. Hudson, Eric Zelikman, Esin Durmus, Faisal Ladhak, Frieda Rong, Hongyu Ren, Huaxiu Yao, Jue Wang, Keshav Santhanam, Laurel J. Orr, Lucia Zheng, Mert Yüksekgönül, Mirac Suzgun, Nathan Kim, Neel Guha, Niladri S. Chatterji, Omar Khattab, Peter Henderson, Qian Huang, Ryan Chi, Sang Michael Xie, Shibani Santurkar, Surya Ganguli, Tatsunori Hashimoto, Thomas Icard, Tianyi Zhang, Vishrav Chaudhary, William Wang, Xuechen Li, Yifan Mai, Yuhui Zhang, Yuta Koreeda:
Holistic Evaluation of Language Models. CoRR abs/2211.09110 (2022) - 2021
- [b1]Dimitris Tsipras:
Learning Through the Lens of Robustness. Massachusetts Institute of Technology, USA, 2021 - [c15]Shibani Santurkar, Dimitris Tsipras, Aleksander Madry:
BREEDS: Benchmarks for Subpopulation Shift. ICLR 2021 - [c14]Shibani Santurkar, Dimitris Tsipras, Mahalaxmi Elango, David Bau, Antonio Torralba, Aleksander Madry:
Editing a classifier by rewriting its prediction rules. NeurIPS 2021: 23359-23373 - [i19]Saachi Jain, Dimitris Tsipras, Aleksander Madry:
Combining Diverse Feature Priors. CoRR abs/2110.08220 (2021) - [i18]Shibani Santurkar, Dimitris Tsipras, Mahalaxmi Elango, David Bau, Antonio Torralba, Aleksander Madry:
Editing a classifier by rewriting its prediction rules. CoRR abs/2112.01008 (2021) - 2020
- [c13]Logan Engstrom, Andrew Ilyas, Shibani Santurkar, Dimitris Tsipras, Firdaus Janoos, Larry Rudolph, Aleksander Madry:
Implementation Matters in Deep RL: A Case Study on PPO and TRPO. ICLR 2020 - [c12]Andrew Ilyas, Logan Engstrom, Shibani Santurkar, Dimitris Tsipras, Firdaus Janoos, Larry Rudolph, Aleksander Madry:
A Closer Look at Deep Policy Gradients. ICLR 2020 - [c11]Logan Engstrom, Andrew Ilyas, Shibani Santurkar, Dimitris Tsipras, Jacob Steinhardt, Aleksander Madry:
Identifying Statistical Bias in Dataset Replication. ICML 2020: 2922-2932 - [c10]Dimitris Tsipras, Shibani Santurkar, Logan Engstrom, Andrew Ilyas, Aleksander Madry:
From ImageNet to Image Classification: Contextualizing Progress on Benchmarks. ICML 2020: 9625-9635 - [i17]Logan Engstrom, Andrew Ilyas, Shibani Santurkar, Dimitris Tsipras, Jacob Steinhardt, Aleksander Madry:
Identifying Statistical Bias in Dataset Replication. CoRR abs/2005.09619 (2020) - [i16]Dimitris Tsipras, Shibani Santurkar, Logan Engstrom, Andrew Ilyas, Aleksander Madry:
From ImageNet to Image Classification: Contextualizing Progress on Benchmarks. CoRR abs/2005.11295 (2020) - [i15]Logan Engstrom, Andrew Ilyas, Shibani Santurkar, Dimitris Tsipras, Firdaus Janoos, Larry Rudolph, Aleksander Madry:
Implementation Matters in Deep Policy Gradients: A Case Study on PPO and TRPO. CoRR abs/2005.12729 (2020) - [i14]Shibani Santurkar, Dimitris Tsipras, Aleksander Madry:
BREEDS: Benchmarks for Subpopulation Shift. CoRR abs/2008.04859 (2020) - [i13]Micah Goldblum, Dimitris Tsipras, Chulin Xie, Xinyun Chen, Avi Schwarzschild, Dawn Song, Aleksander Madry, Bo Li, Tom Goldstein:
Dataset Security for Machine Learning: Data Poisoning, Backdoor Attacks, and Defenses. CoRR abs/2012.10544 (2020)
2010 – 2019
- 2019
- [c9]Dimitris Tsipras, Shibani Santurkar, Logan Engstrom, Alexander Turner, Aleksander Madry:
Robustness May Be at Odds with Accuracy. ICLR (Poster) 2019 - [c8]Logan Engstrom, Brandon Tran, Dimitris Tsipras, Ludwig Schmidt, Aleksander Madry:
Exploring the Landscape of Spatial Robustness. ICML 2019: 1802-1811 - [c7]Andrew Ilyas, Shibani Santurkar, Dimitris Tsipras, Logan Engstrom, Brandon Tran, Aleksander Madry:
Adversarial Examples Are Not Bugs, They Are Features. NeurIPS 2019: 125-136 - [c6]Shibani Santurkar, Andrew Ilyas, Dimitris Tsipras, Logan Engstrom, Brandon Tran, Aleksander Madry:
Image Synthesis with a Single (Robust) Classifier. NeurIPS 2019: 1260-1271 - [i12]Nicholas Carlini, Anish Athalye, Nicolas Papernot, Wieland Brendel, Jonas Rauber, Dimitris Tsipras, Ian J. Goodfellow, Aleksander Madry, Alexey Kurakin:
On Evaluating Adversarial Robustness. CoRR abs/1902.06705 (2019) - [i11]Andrew Ilyas, Shibani Santurkar, Dimitris Tsipras, Logan Engstrom, Brandon Tran, Aleksander Madry:
Adversarial Examples Are Not Bugs, They Are Features. CoRR abs/1905.02175 (2019) - [i10]Logan Engstrom, Andrew Ilyas, Shibani Santurkar, Dimitris Tsipras, Brandon Tran, Aleksander Madry:
Learning Perceptually-Aligned Representations via Adversarial Robustness. CoRR abs/1906.00945 (2019) - [i9]Shibani Santurkar, Dimitris Tsipras, Brandon Tran, Andrew Ilyas, Logan Engstrom, Aleksander Madry:
Computer Vision with a Single (Robust) Classifier. CoRR abs/1906.09453 (2019) - [i8]Alexander Turner, Dimitris Tsipras, Aleksander Madry:
Label-Consistent Backdoor Attacks. CoRR abs/1912.02771 (2019) - 2018
- [c5]Aleksander Madry, Aleksandar Makelov, Ludwig Schmidt, Dimitris Tsipras, Adrian Vladu:
Towards Deep Learning Models Resistant to Adversarial Attacks. ICLR (Poster) 2018 - [c4]Shibani Santurkar, Dimitris Tsipras, Andrew Ilyas, Aleksander Madry:
How Does Batch Normalization Help Optimization? NeurIPS 2018: 2488-2498 - [c3]Ludwig Schmidt, Shibani Santurkar, Dimitris Tsipras, Kunal Talwar, Aleksander Madry:
Adversarially Robust Generalization Requires More Data. NeurIPS 2018: 5019-5031 - [i7]Ludwig Schmidt, Shibani Santurkar, Dimitris Tsipras, Kunal Talwar, Aleksander Madry:
Adversarially Robust Generalization Requires More Data. CoRR abs/1804.11285 (2018) - [i6]Shibani Santurkar, Dimitris Tsipras, Andrew Ilyas, Aleksander Madry:
How Does Batch Normalization Help Optimization? (No, It Is Not About Internal Covariate Shift). CoRR abs/1805.11604 (2018) - [i5]Dimitris Tsipras, Shibani Santurkar, Logan Engstrom, Alexander Turner, Aleksander Madry:
There Is No Free Lunch In Adversarial Robustness (But There Are Unexpected Benefits). CoRR abs/1805.12152 (2018) - [i4]Andrew Ilyas, Logan Engstrom, Shibani Santurkar, Dimitris Tsipras, Firdaus Janoos, Larry Rudolph, Aleksander Madry:
Are Deep Policy Gradient Algorithms Truly Policy Gradient Algorithms? CoRR abs/1811.02553 (2018) - 2017
- [c2]Michael B. Cohen, Aleksander Madry, Dimitris Tsipras, Adrian Vladu:
Matrix Scaling and Balancing via Box Constrained Newton's Method and Interior Point Methods. FOCS 2017: 902-913 - [i3]Michael B. Cohen, Aleksander Madry, Dimitris Tsipras, Adrian Vladu:
Matrix Scaling and Balancing via Box Constrained Newton's Method and Interior Point Methods. CoRR abs/1704.02310 (2017) - [i2]Aleksander Madry, Aleksandar Makelov, Ludwig Schmidt, Dimitris Tsipras, Adrian Vladu:
Towards Deep Learning Models Resistant to Adversarial Attacks. CoRR abs/1706.06083 (2017) - [i1]Logan Engstrom, Dimitris Tsipras, Ludwig Schmidt, Aleksander Madry:
A Rotation and a Translation Suffice: Fooling CNNs with Simple Transformations. CoRR abs/1712.02779 (2017) - 2016
- [j1]Dimitris Fotakis, Dimitris Tsipras, Christos Tzamos, Emmanouil Zampetakis:
Efficient Money Burning in General Domains. Theory Comput. Syst. 59(4): 619-640 (2016) - 2015
- [c1]Dimitris Fotakis, Dimitris Tsipras, Christos Tzamos, Emmanouil Zampetakis:
Efficient Money Burning in General Domains. SAGT 2015: 85-97
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 2024-08-10 00:25 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:
