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2020 – today
- 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 - [i66]Hadi Salman, Alaa Khaddaj, Guillaume Leclerc, Andrew Ilyas, Aleksander Madry:
Raising the Cost of Malicious AI-Powered Image Editing. CoRR abs/2302.06588 (2023) - [i65]Joshua Vendrow, Saachi Jain, Logan Engstrom, Aleksander Madry:
Dataset Interfaces: Diagnosing Model Failures Using Controllable Counterfactual Generation. CoRR abs/2302.07865 (2023) - [i64]Sung Min Park, Kristian Georgiev, Andrew Ilyas, Guillaume Leclerc, Aleksander Madry:
TRAK: Attributing Model Behavior at Scale. CoRR abs/2303.14186 (2023) - [i63]Sarah H. Cen, Aleksander Madry, Devavrat Shah:
A User-Driven Framework for Regulating and Auditing Social Media. CoRR abs/2304.10525 (2023) - [i62]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) - [i61]Alaa Khaddaj, Guillaume Leclerc, Aleksandar Makelov, Kristian Georgiev, Hadi Salman, Andrew Ilyas, Aleksander Madry:
Rethinking Backdoor Attacks. CoRR abs/2307.10163 (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]