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2020 – today
- 2024
[c64]Logan Engstrom, Axel Feldmann, Aleksander Madry:
DsDm: Model-Aware Dataset Selection with Datamodels. ICML 2024- [c63]Harshay Shah, Andrew Ilyas, Aleksander Madry:
Decomposing and Editing Predictions by Modeling Model Computation. ICML 2024 - [i77]Logan Engstrom, Axel Feldmann, Aleksander Madry:
DsDm: Model-Aware Dataset Selection with Datamodels. CoRR abs/2401.12926 (2024) - [i76]Benjamin Cohen-Wang, Joshua Vendrow, Aleksander Madry:
Ask Your Distribution Shift if Pre-Training is Right for You. CoRR abs/2403.00194 (2024) - [i75]Harshay Shah, Andrew Ilyas, Aleksander Madry:
Decomposing and Editing Predictions by Modeling Model Computation. CoRR abs/2404.11534 (2024) - [i74]Sarah H. Cen, Andrew Ilyas, Jennifer Allen, Hannah Li, Aleksander Madry:
Measuring Strategization in Recommendation: Users Adapt Their Behavior to Shape Future Content. CoRR abs/2405.05596 (2024) - [i73]Saachi Jain, Kimia Hamidieh, Kristian Georgiev, Andrew Ilyas, Marzyeh Ghassemi, Aleksander Madry:
Data Debiasing with Datamodels (D3M): Improving Subgroup Robustness via Data Selection. CoRR abs/2406.16846 (2024) - [i72]Benjamin Cohen-Wang, Harshay Shah, Kristian Georgiev, Aleksander Madry:
ContextCite: Attributing Model Generation to Context. CoRR abs/2409.00729 (2024) - [i71]Jun Shern Chan, Neil Chowdhury, Oliver Jaffe, James Aung, Dane Sherburn, Evan Mays, Giulio Starace, Kevin Liu, Leon Maksin, Tejal Patwardhan, Lilian Weng, Aleksander Madry:
MLE-bench: Evaluating Machine Learning Agents on Machine Learning Engineering. CoRR abs/2410.07095 (2024) - [i70]Aaron Hurst, Adam Lerer, Adam P. Goucher, Adam Perelman, Aditya Ramesh, Aidan Clark, AJ Ostrow, Akila Welihinda, Alan Hayes, Alec Radford, Aleksander Madry, Alex Baker-Whitcomb, Alex Beutel, Alex Borzunov, Alex Carney, Alex Chow, Alex Kirillov, Alex Nichol, Alex Paino, Alex Renzin, Alex Tachard Passos, Alexander Kirillov, Alexi Christakis, Alexis Conneau, Ali Kamali, Allan Jabri, Allison Moyer, Allison Tam, Amadou Crookes, Amin Tootoonchian, Ananya Kumar, Andrea Vallone, Andrej Karpathy, Andrew Braunstein, Andrew Cann, Andrew Codispoti, Andrew Galu, Andrew Kondrich, Andrew Tulloch, Andrey Mishchenko, Angela Baek, Angela Jiang, Antoine Pelisse, Antonia Woodford, Anuj Gosalia, Arka Dhar, Ashley Pantuliano, Avi Nayak, Avital Oliver, Barret Zoph, Behrooz Ghorbani, Ben Leimberger, Ben Rossen, Ben Sokolowsky, Ben Wang, Benjamin Zweig, Beth Hoover, Blake Samic, Bob McGrew, Bobby Spero, Bogo Giertler, Bowen Cheng, Brad Lightcap, Brandon Walkin, Brendan Quinn, Brian Guarraci, Brian Hsu, Bright Kellogg, Brydon Eastman, Camillo Lugaresi, Carroll L. Wainwright, Cary Bassin, Cary Hudson, Casey Chu, Chad Nelson, Chak Li, Chan Jun Shern, Channing Conger, Charlotte Barette, Chelsea Voss, Chen Ding, Cheng Lu, Chong Zhang, Chris Beaumont, Chris Hallacy, Chris Koch, Christian Gibson, Christina Kim, Christine Choi, Christine McLeavey, Christopher Hesse, Claudia Fischer, Clemens Winter, Coley Czarnecki, Colin Jarvis, Colin Wei, Constantin Koumouzelis, Dane Sherburn:
GPT-4o System Card. CoRR abs/2410.21276 (2024) - [i69]Kristian Georgiev, Roy Rinberg, Sung Min Park, Shivam Garg, Andrew Ilyas, Aleksander Madry, Seth Neel:
Attribute-to-Delete: Machine Unlearning via Datamodel Matching. CoRR abs/2410.23232 (2024) - 2023
- [j8]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) - [c62]Saachi Jain, Hadi Salman, Alaa Khaddaj, Eric Wong, Sung Min Park, Aleksander Madry:
A Data-Based Perspective on Transfer Learning. CVPR 2023: 3613-3622 - [c61]Guillaume Leclerc, Andrew Ilyas, Logan Engstrom, Sung Min Park, Hadi Salman, Aleksander Madry:
FFCV: Accelerating Training by Removing Data Bottlenecks. CVPR 2023: 12011-12020 - [c60]Saachi Jain, Hannah Lawrence, Ankur Moitra, Aleksander Madry:
Distilling Model Failures as Directions in Latent Space. ICLR 2023 - [c59]Alaa Khaddaj, Guillaume Leclerc, Aleksandar Makelov, Kristian Georgiev, Hadi Salman, Andrew Ilyas, Aleksander Madry:
Rethinking Backdoor Attacks. ICML 2023: 16216-16236 - [c58]Sung Min Park, Kristian Georgiev, Andrew Ilyas, Guillaume Leclerc, Aleksander Madry:
TRAK: Attributing Model Behavior at Scale. ICML 2023: 27074-27113 - [c57]Hadi Salman, Alaa Khaddaj, Guillaume Leclerc, Andrew Ilyas, Aleksander Madry:
Raising the Cost of Malicious AI-Powered Image Editing. ICML 2023: 29894-29918 - [c56]Harshay Shah, Sung Min Park, Andrew Ilyas, Aleksander Madry:
ModelDiff: A Framework for Comparing Learning Algorithms. ICML 2023: 30646-30688 - [i68]Hadi Salman, Alaa Khaddaj, Guillaume Leclerc, Andrew Ilyas, Aleksander Madry:
Raising the Cost of Malicious AI-Powered Image Editing. CoRR abs/2302.06588 (2023) - [i67]Joshua Vendrow, Saachi Jain, Logan Engstrom, Aleksander Madry:
Dataset Interfaces: Diagnosing Model Failures Using Controllable Counterfactual Generation. CoRR abs/2302.07865 (2023) - [i66]Sung Min Park, Kristian Georgiev, Andrew Ilyas, Guillaume Leclerc, Aleksander Madry:
TRAK: Attributing Model Behavior at Scale. CoRR abs/2303.14186 (2023) - [i65]Sarah H. Cen, Aleksander Madry, Devavrat Shah:
A User-Driven Framework for Regulating and Auditing Social Media. CoRR abs/2304.10525 (2023) - [i64]Guillaume Leclerc, Andrew Ilyas, Logan Engstrom, Sung Min Park, Hadi Salman, Aleksander Madry:
FFCV: Accelerating Training by Removing Data Bottlenecks. CoRR abs/2306.12517 (2023) - [i63]Alaa Khaddaj, Guillaume Leclerc, Aleksandar Makelov, Kristian Georgiev, Hadi Salman, Andrew Ilyas, Aleksander Madry:
Rethinking Backdoor Attacks. CoRR abs/2307.10163 (2023) - [i62]Kristian Georgiev, Joshua Vendrow, Hadi Salman, Sung Min Park, Aleksander Madry:
The Journey, Not the Destination: How Data Guides Diffusion Models. CoRR abs/2312.06205 (2023) - [i61]Sarah H. Cen, Andrew Ilyas, Aleksander Madry:
User Strategization and Trustworthy Algorithms. CoRR abs/2312.17666 (2023) - 2022
- [c55]Hadi Salman, Saachi Jain, Eric Wong, Aleksander Madry:
Certified Patch Robustness via Smoothed Vision Transformers. CVPR 2022: 15116-15126 - [c54]Saachi Jain, Hadi Salman, Eric Wong, Pengchuan Zhang, Vibhav Vineet, Sai Vemprala, Aleksander Madry:
Missingness Bias in Model Debugging. ICLR 2022 - [c53]Chong Guo, Michael J. Lee, Guillaume Leclerc, Joel Dapello, Yug Rao, Aleksander Madry, James J. DiCarlo:
Adversarially trained neural representations are already as robust as biological neural representations. ICML 2022: 8072-8081 - [c52]Andrew Ilyas, Sung Min Park, Logan Engstrom, Guillaume Leclerc, Aleksander Madry:
Datamodels: Understanding Predictions with Data and Data with Predictions. ICML 2022: 9525-9587 - [c51]Saachi Jain, Dimitris Tsipras, Aleksander Madry:
Combining Diverse Feature Priors. ICML 2022: 9802-9832 - [c50]Guillaume Leclerc, Hadi Salman, Andrew Ilyas, Sai Vemprala, Logan Engstrom, Vibhav Vineet, Kai Yuanqing Xiao, Pengchuan Zhang, Shibani Santurkar, Greg Yang, Ashish Kapoor, Aleksander Madry:
3DB: A Framework for Debugging Computer Vision Models. NeurIPS 2022 - [i60]Andrew Ilyas, Sung Min Park, Logan Engstrom, Guillaume Leclerc, Aleksander Madry:
Datamodels: Predicting Predictions from Training Data. CoRR abs/2202.00622 (2022) - [i59]Saachi Jain, Hadi Salman, Eric Wong, Pengchuan Zhang, Vibhav Vineet, Sai Vemprala, Aleksander Madry:
Missingness Bias in Model Debugging. CoRR abs/2204.08945 (2022) - [i58]Chong Guo, Michael J. Lee, Guillaume Leclerc, Joel Dapello, Yug Rao, Aleksander Madry, James J. DiCarlo:
Adversarially trained neural representations may already be as robust as corresponding biological neural representations. CoRR abs/2206.11228 (2022) - [i57]Saachi Jain, Hannah Lawrence, Ankur Moitra, Aleksander Madry:
Distilling Model Failures as Directions in Latent Space. CoRR abs/2206.14754 (2022) - [i56]Hadi Salman, Saachi Jain, Andrew Ilyas, Logan Engstrom, Eric Wong, Aleksander Madry:
When does Bias Transfer in Transfer Learning? CoRR abs/2207.02842 (2022) - [i55]Saachi Jain, Hadi Salman, Alaa Khaddaj, Eric Wong, Sung Min Park, Aleksander Madry:
A Data-Based Perspective on Transfer Learning. CoRR abs/2207.05739 (2022) - [i54]Harshay Shah, Sung Min Park, Andrew Ilyas, Aleksander Madry:
ModelDiff: A Framework for Comparing Learning Algorithms. CoRR abs/2211.12491 (2022) - 2021
- [c49]Kyriakos Axiotis, Aleksander Madry, Adrian Vladu:
Faster Sparse Minimum Cost Flow by Electrical Flow Localization. FOCS 2021: 528-539 - [c48]Shibani Santurkar, Dimitris Tsipras, Aleksander Madry:
BREEDS: Benchmarks for Subpopulation Shift. ICLR 2021 - [c47]Kai Yuanqing Xiao, Logan Engstrom, Andrew Ilyas, Aleksander Madry:
Noise or Signal: The Role of Image Backgrounds in Object Recognition. ICLR 2021 - [c46]Eric Wong, Shibani Santurkar, Aleksander Madry:
Leveraging Sparse Linear Layers for Debuggable Deep Networks. ICML 2021: 11205-11216 - [c45]Hadi Salman, Andrew Ilyas, Logan Engstrom, Sai Vemprala, Aleksander Madry, Ashish Kapoor:
Unadversarial Examples: Designing Objects for Robust Vision. NeurIPS 2021: 15270-15284 - [c44]Shibani Santurkar, Dimitris Tsipras, Mahalaxmi Elango, David Bau, Antonio Torralba, Aleksander Madry:
Editing a classifier by rewriting its prediction rules. NeurIPS 2021: 23359-23373 - [i53]Eric Wong, Shibani Santurkar, Aleksander Madry:
Leveraging Sparse Linear Layers for Debuggable Deep Networks. CoRR abs/2105.04857 (2021) - [i52]Guillaume Leclerc, Hadi Salman, Andrew Ilyas, Sai Vemprala, Logan Engstrom, Vibhav Vineet, Kai Yuanqing Xiao, Pengchuan Zhang, Shibani Santurkar, Greg Yang, Ashish Kapoor, Aleksander Madry:
3DB: A Framework for Debugging Computer Vision Models. CoRR abs/2106.03805 (2021) - [i51]Hadi Salman, Saachi Jain, Eric Wong, Aleksander Madry:
Certified Patch Robustness via Smoothed Vision Transformers. CoRR abs/2110.07719 (2021) - [i50]Saachi Jain, Dimitris Tsipras, Aleksander Madry:
Combining Diverse Feature Priors. CoRR abs/2110.08220 (2021) - [i49]Kyriakos Axiotis, Aleksander Madry, Adrian Vladu:
Faster Sparse Minimum Cost Flow by Electrical Flow Localization. CoRR abs/2111.10368 (2021) - [i48]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) - [i47]Sung Min Park, Kuo-An Wei, Kai Yuanqing Xiao, Jerry Li, Aleksander Madry:
On Distinctive Properties of Universal Perturbations. CoRR abs/2112.15329 (2021) - 2020
- [j7]Artur Czumaj, Jakub Lacki, Aleksander Madry, Slobodan Mitrovic, Krzysztof Onak, Piotr Sankowski:
Round Compression for Parallel Matching Algorithms. SIAM J. Comput. 49(5) (2020) - [c43]Kyriakos Axiotis, Aleksander Madry, Adrian Vladu:
Circulation Control for Faster Minimum Cost Flow in Unit-Capacity Graphs. FOCS 2020: 93-104 - [c42]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 - [c41]Andrew Ilyas, Logan Engstrom, Shibani Santurkar, Dimitris Tsipras, Firdaus Janoos, Larry Rudolph, Aleksander Madry:
A Closer Look at Deep Policy Gradients. ICLR 2020 - [c40]Logan Engstrom, Andrew Ilyas, Shibani Santurkar, Dimitris Tsipras, Jacob Steinhardt, Aleksander Madry:
Identifying Statistical Bias in Dataset Replication. ICML 2020: 2922-2932 - [c39]Dimitris Tsipras, Shibani Santurkar, Logan Engstrom, Andrew Ilyas, Aleksander Madry:
From ImageNet to Image Classification: Contextualizing Progress on Benchmarks. ICML 2020: 9625-9635 - [c38]Hadi Salman, Andrew Ilyas, Logan Engstrom, Ashish Kapoor, Aleksander Madry:
Do Adversarially Robust ImageNet Models Transfer Better? NeurIPS 2020 - [c37]Florian Tramèr, Nicholas Carlini, Wieland Brendel, Aleksander Madry:
On Adaptive Attacks to Adversarial Example Defenses. NeurIPS 2020 - [i46]Florian Tramèr, Nicholas Carlini, Wieland Brendel, Aleksander Madry:
On Adaptive Attacks to Adversarial Example Defenses. CoRR abs/2002.08347 (2020) - [i45]Guillaume Leclerc, Aleksander Madry:
The Two Regimes of Deep Network Training. CoRR abs/2002.10376 (2020) - [i44]Kyriakos Axiotis, Aleksander Madry, Adrian Vladu:
Circulation Control for Faster Minimum Cost Flow in Unit-Capacity Graphs. CoRR abs/2003.04863 (2020) - [i43]Logan Engstrom, Andrew Ilyas, Shibani Santurkar, Dimitris Tsipras, Jacob Steinhardt, Aleksander Madry:
Identifying Statistical Bias in Dataset Replication. CoRR abs/2005.09619 (2020) - [i42]Dimitris Tsipras, Shibani Santurkar, Logan Engstrom, Andrew Ilyas, Aleksander Madry:
From ImageNet to Image Classification: Contextualizing Progress on Benchmarks. CoRR abs/2005.11295 (2020) - [i41]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) - [i40]Kai Yuanqing Xiao, Logan Engstrom, Andrew Ilyas, Aleksander Madry:
Noise or Signal: The Role of Image Backgrounds in Object Recognition. CoRR abs/2006.09994 (2020) - [i39]Hadi Salman, Andrew Ilyas, Logan Engstrom, Ashish Kapoor, Aleksander Madry:
Do Adversarially Robust ImageNet Models Transfer Better? CoRR abs/2007.08489 (2020) - [i38]Shibani Santurkar, Dimitris Tsipras, Aleksander Madry:
BREEDS: Benchmarks for Subpopulation Shift. CoRR abs/2008.04859 (2020) - [i37]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) - [i36]Hadi Salman, Andrew Ilyas, Logan Engstrom, Sai Vemprala, Aleksander Madry, Ashish Kapoor:
Unadversarial Examples: Designing Objects for Robust Vision. CoRR abs/2012.12235 (2020)
2010 – 2019
- 2019
- [c36]Andrew Ilyas, Logan Engstrom, Aleksander Madry:
Prior Convictions: Black-box Adversarial Attacks with Bandits and Priors. ICLR (Poster) 2019 - [c35]Dimitris Tsipras, Shibani Santurkar, Logan Engstrom, Alexander Turner, Aleksander Madry:
Robustness May Be at Odds with Accuracy. ICLR (Poster) 2019 - [c34]Kai Yuanqing Xiao, Vincent Tjeng, Nur Muhammad (Mahi) Shafiullah, Aleksander Madry:
Training for Faster Adversarial Robustness Verification via Inducing ReLU Stability. ICLR (Poster) 2019 - [c33]Logan Engstrom, Brandon Tran, Dimitris Tsipras, Ludwig Schmidt, Aleksander Madry:
Exploring the Landscape of Spatial Robustness. ICML 2019: 1802-1811 - [c32]Andrew Ilyas, Shibani Santurkar, Dimitris Tsipras, Logan Engstrom, Brandon Tran, Aleksander Madry:
Adversarial Examples Are Not Bugs, They Are Features. NeurIPS 2019: 125-136 - [c31]Shibani Santurkar, Andrew Ilyas, Dimitris Tsipras, Logan Engstrom, Brandon Tran, Aleksander Madry:
Image Synthesis with a Single (Robust) Classifier. NeurIPS 2019: 1260-1271 - [i35]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) - [i34]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) - [i33]Logan Engstrom, Andrew Ilyas, Shibani Santurkar, Dimitris Tsipras, Brandon Tran, Aleksander Madry:
Learning Perceptually-Aligned Representations via Adversarial Robustness. CoRR abs/1906.00945 (2019) - [i32]Shibani Santurkar, Dimitris Tsipras, Brandon Tran, Andrew Ilyas, Logan Engstrom, Aleksander Madry:
Computer Vision with a Single (Robust) Classifier. CoRR abs/1906.09453 (2019) - [i31]Alexander Turner, Dimitris Tsipras, Aleksander Madry:
Label-Consistent Backdoor Attacks. CoRR abs/1912.02771 (2019) - 2018
- [c30]Aleksander Madry, Slobodan Mitrovic, Ludwig Schmidt:
A Fast Algorithm for Separated Sparsity via Perturbed Lagrangians. AISTATS 2018: 20-28 - [c29]Aleksander Madry, Aleksandar Makelov, Ludwig Schmidt, Dimitris Tsipras, Adrian Vladu:
Towards Deep Learning Models Resistant to Adversarial Attacks. ICLR (Poster) 2018 - [c28]Jerry Li, Aleksander Madry, John Peebles, Ludwig Schmidt:
On the Limitations of First-Order Approximation in GAN Dynamics. ICML 2018: 3011-3019 - [c27]Shibani Santurkar, Ludwig Schmidt, Aleksander Madry:
A Classification-Based Study of Covariate Shift in GAN Distributions. ICML 2018: 4487-4496 - [c26]Shibani Santurkar, Dimitris Tsipras, Andrew Ilyas, Aleksander Madry:
How Does Batch Normalization Help Optimization? NeurIPS 2018: 2488-2498 - [c25]Ludwig Schmidt, Shibani Santurkar, Dimitris Tsipras, Kunal Talwar, Aleksander Madry:
Adversarially Robust Generalization Requires More Data. NeurIPS 2018: 5019-5031 - [c24]Brandon Tran, Jerry Li, Aleksander Madry:
Spectral Signatures in Backdoor Attacks. NeurIPS 2018: 8011-8021 - [c23]Sébastien Bubeck, Michael B. Cohen, Yin Tat Lee, James R. Lee, Aleksander Madry:
k-server via multiscale entropic regularization. STOC 2018: 3-16 - [c22]Artur Czumaj, Jakub Lacki, Aleksander Madry, Slobodan Mitrovic, Krzysztof Onak, Piotr Sankowski:
Round compression for parallel matching algorithms. STOC 2018: 471-484 - [i30]Ludwig Schmidt, Shibani Santurkar, Dimitris Tsipras, Kunal Talwar, Aleksander Madry:
Adversarially Robust Generalization Requires More Data. CoRR abs/1804.11285 (2018) - [i29]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) - [i28]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) - [i27]Andrew Ilyas, Logan Engstrom, Aleksander Madry:
Prior Convictions: Black-Box Adversarial Attacks with Bandits and Priors. CoRR abs/1807.07978 (2018) - [i26]Kai Yuanqing Xiao, Vincent Tjeng, Nur Muhammad (Mahi) Shafiullah, Aleksander Madry:
Training for Faster Adversarial Robustness Verification via Inducing ReLU Stability. CoRR abs/1809.03008 (2018) - [i25]Brandon Tran, Jerry Li, Aleksander Madry:
Spectral Signatures in Backdoor Attacks. CoRR abs/1811.00636 (2018) - [i24]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
- [j6]Arash Asadpour, Michel X. Goemans, Aleksander Madry, Shayan Oveis Gharan, Amin Saberi:
An O(log n/log log n)-Approximation Algorithm for the Asymmetric Traveling Salesman Problem. Oper. Res. 65(4): 1043-1061 (2017) - [j5]Marco Chiesa, Ilya Nikolaevskiy, Slobodan Mitrovic, Andrei V. Gurtov, Aleksander Madry, Michael Schapira, Scott Shenker:
On the Resiliency of Static Forwarding Tables. IEEE/ACM Trans. Netw. 25(2): 1133-1146 (2017) - [c21]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 - [c20]Michael B. Cohen, Aleksander Madry, Piotr Sankowski, Adrian Vladu:
Negative-Weight Shortest Paths and Unit Capacity Minimum Cost Flow in Õ (m10/7 log W) Time (Extended Abstract). SODA 2017: 752-771 - [i23]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) - [i22]Aleksander Madry, Aleksandar Makelov, Ludwig Schmidt, Dimitris Tsipras, Adrian Vladu:
Towards Deep Learning Models Resistant to Adversarial Attacks. CoRR abs/1706.06083 (2017) - [i21]Jerry Li, Aleksander Madry, John Peebles, Ludwig Schmidt:
Towards Understanding the Dynamics of Generative Adversarial Networks. CoRR abs/1706.09884 (2017) - [i20]Artur Czumaj, Jakub Lacki, Aleksander Madry, Slobodan Mitrovic, Krzysztof Onak, Piotr Sankowski:
Round Compression for Parallel Matching Algorithms. CoRR abs/1707.03478 (2017) - [i19]Shibani Santurkar, Ludwig Schmidt, Aleksander Madry:
A Classification-Based Perspective on GAN Distributions. CoRR abs/1711.00970 (2017) - [i18]Sébastien Bubeck, Michael B. Cohen, James R. Lee, Yin Tat Lee, Aleksander Madry:
k-server via multiscale entropic regularization. CoRR abs/1711.01085 (2017) - [i17]Logan Engstrom, Dimitris Tsipras, Ludwig Schmidt, Aleksander Madry:
A Rotation and a Translation Suffice: Fooling CNNs with Simple Transformations. CoRR abs/1712.02779 (2017) - [i16]Aleksander Madry, Slobodan Mitrovic, Ludwig Schmidt:
A Fast Algorithm for Separated Sparsity via Perturbed Lagrangians. CoRR abs/1712.08130 (2017) - 2016
- [c19]Aleksander Madry:
Computing Maximum Flow with Augmenting Electrical Flows. FOCS 2016: 593-602 - [c18]Aleksander Madry:
Continuous Optimization: The "Right" Language for Graph Algorithms? (Invited Talk). FSTTCS 2016: 4:1-4:2 - [c17]Marco Chiesa, Andrei V. Gurtov, Aleksander Madry, Slobodan Mitrovic, Ilya Nikolaevskiy, Michael Schapira, Scott Shenker:
On the Resiliency of Randomized Routing Against Multiple Edge Failures. ICALP 2016: 134:1-134:15 - [c16]Marco Chiesa, Ilya Nikolaevskiy, Slobodan Mitrovic, Aurojit Panda, Andrei V. Gurtov, Aleksander Madry, Michael Schapira, Scott Shenker:
The quest for resilient (static) forwarding tables. INFOCOM 2016: 1-9 - [i15]Michael B. Cohen, Aleksander Madry, Piotr Sankowski, Adrian Vladu:
Negative-Weight Shortest Paths and Unit Capacity Minimum Cost Flow in Õ(m10/7 log W) Time. CoRR abs/1605.01717 (2016) - [i14]Aleksander Madry:
Computing Maximum Flow with Augmenting Electrical Flows. CoRR abs/1608.06016 (2016) - 2015
- [j4]Nikhil Bansal, Niv Buchbinder, Aleksander Madry, Joseph Naor:
A Polylogarithmic-Competitive Algorithm for the k-Server Problem. J. ACM 62(5): 40:1-40:49 (2015) - [j3]Christos Kalaitzis, Aleksander Madry, Alantha Newman, Lukás Polácek, Ola Svensson:
On the configuration LP for maximum budgeted allocation. Math. Program. 154(1-2): 427-462 (2015) - [c15]Aleksander Madry, Damian Straszak, Jakub Tarnawski:
Fast Generation of Random Spanning Trees and the Effective Resistance Metric. SODA 2015: 2019-2036 - [i13]Aleksander Madry, Damian Straszak, Jakub Tarnawski:
Fast Generation of Random Spanning Trees and the Effective Resistance Metric. CoRR abs/1501.00267 (2015) - 2014
- [c14]Christos Kalaitzis, Aleksander Madry, Alantha Newman, Lukas Polacek, Ola Svensson:
On the Configuration LP for Maximum Budgeted Allocation. IPCO 2014: 333-344 - [i12]Christos Kalaitzis, Aleksander Madry, Alantha Newman, Lukas Polacek, Ola Svensson:
On the Configuration LP for Maximum Budgeted Allocation. CoRR abs/1403.7519 (2014) - 2013
- [c13]Aleksander Madry:
Navigating Central Path with Electrical Flows: From Flows to Matchings, and Back. FOCS 2013: 253-262 - [c12]Hui Han Chin, Aleksander Madry, Gary L. Miller, Richard Peng:
Runtime guarantees for regression problems. ITCS 2013: 269-282 - [i11]Aleksander Madry:
Navigating Central Path with Electrical Flows: from Flows to Matchings, and Back. CoRR abs/1307.2205 (2013) - 2011
- [b1]Aleksander Madry:
New techniques for graph algorithms. Massachusetts Institute of Technology, Cambridge, MA, USA, 2011 - [j2]Yossi Azar, Aleksander Madry, Thomas Moscibroda, Debmalya Panigrahi, Aravind Srinivasan:
Maximum bipartite flow in networks with adaptive channel width. Theor. Comput. Sci. 412(24): 2577-2587 (2011) - [c11]Nikhil Bansal, Niv Buchbinder, Aleksander Madry, Joseph Naor:
A Polylogarithmic-Competitive Algorithm for the k-Server Problem. FOCS 2011: 267-276 - [c10]Aleksander Madry, Debmalya Panigrahi:
The Semi-stochastic Ski-rental Problem. FSTTCS 2011: 300-311 - [c9]Paul F. Christiano, Jonathan A. Kelner, Aleksander Madry, Daniel A. Spielman, Shang-Hua Teng:
Electrical flows, laplacian systems, and faster approximation of maximum flow in undirected graphs. STOC 2011: 273-282 - [i10]Aleksander Madry, Gary L. Miller, Richard Peng:
Electrical Flow Algorithms for Total Variation Minimization. CoRR abs/1110.1358 (2011) - [i9]Nikhil Bansal, Niv Buchbinder, Aleksander Madry, Joseph Naor:
A Polylogarithmic-Competitive Algorithm for the k-Server Problem. CoRR abs/1110.1580 (2011) - 2010
- [c8]Aleksander Madry:
Fast Approximation Algorithms for Cut-Based Problems in Undirected Graphs. FOCS 2010: 245-254 - [c7]Arash Asadpour, Michel X. Goemans, Aleksander Madry, Shayan Oveis Gharan, Amin Saberi:
An O(log n/ log log n)-approximation Algorithm for the Asymmetric Traveling Salesman Problem. SODA 2010: 379-389 - [c6]Aleksander Madry:
Faster approximation schemes for fractional multicommodity flow problems via dynamic graph algorithms. STOC 2010: 121-130 - [i8]Aleksander Madry:
Faster Approximation Schemes for Fractional Multicommodity Flow Problems via Dynamic Graph Algorithms. CoRR abs/1003.5907 (2010) - [i7]Aleksander Madry:
Fast Approximation Algorithms for Cut-based Problems in Undirected Graphs. CoRR abs/1008.1975 (2010) - [i6]Paul F. Christiano, Jonathan A. Kelner, Aleksander Madry, Daniel A. Spielman, Shang-Hua Teng:
Electrical Flows, Laplacian Systems, and Faster Approximation of Maximum Flow in Undirected Graphs. CoRR abs/1010.2921 (2010)
2000 – 2009
- 2009
- [c5]Katarzyna E. Paluch, Marcin Mucha, Aleksander Madry:
A 7/9 - Approximation Algorithm for the Maximum Traveling Salesman Problem. APPROX-RANDOM 2009: 298-311 - [c4]Jonathan A. Kelner, Aleksander Madry:
Faster Generation of Random Spanning Trees. FOCS 2009: 13-21 - [c3]Yossi Azar, Aleksander Madry, Thomas Moscibroda, Debmalya Panigrahi, Aravind Srinivasan:
Maximum Bipartite Flow in Networks with Adaptive Channel Width. ICALP (2) 2009: 351-362 - [i5]Jonathan A. Kelner, Aleksander Madry:
Faster generation of random spanning trees. CoRR abs/0908.1448 (2009) - 2008
- [c2]Andreas Jakoby, Maciej Liskiewicz, Aleksander Madry:
Susceptible Two-Party Quantum Computations. ICITS 2008: 121-136 - [c1]Marcin Bienkowski, Aleksander Madry:
Geometric Aspects of Online Packet Buffering: An Optimal Randomized Algorithm for Two Buffers. LATIN 2008: 252-263 - [i4]Katarzyna E. Paluch, Marcin Mucha, Aleksander Madry:
A 7/9 - Approximation Algorithm for the Maximum Traveling Salesman Problem. CoRR abs/0812.5101 (2008) - 2006
- [i3]Andreas Jakoby, Maciej Liskiewicz, Aleksander Madry:
Using Quantum Oblivious Transfer to Cheat Sensitive Quantum Bit Commitment. Complexity of Boolean Functions 2006 - [i2]Andreas Jakoby, Maciej Liskiewicz, Aleksander Madry:
Using quantum oblivious transfer to cheat sensitive quantum bit commitment. CoRR abs/quant-ph/0605150 (2006) - [i1]Andreas Jakoby, Maciej Liskiewicz, Aleksander Madry:
Using Quantum Oblivious Transfer to Cheat Sensitive Quantum Bit Commitment. Electron. Colloquium Comput. Complex. TR06 (2006) - 2005
- [j1]Aleksander Madry:
Data exchange: On the complexity of answering queries with inequalities. Inf. Process. Lett. 94(6): 253-257 (2005)
Coauthor Index
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