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2020 – today
- 2024
[c36]Adela Frances DePavia, Erasmo Tani, Ali Vakilian:
Learning-Based Algorithms for Graph Searching Problems. AISTATS 2024: 928-936- [c35]Ron Mosenzon, Ali Vakilian:
Scalable Algorithms for Individual Preference Stable Clustering. AISTATS 2024: 1108-1116 - [c34]Ce Jin, Michael Kapralov, Sepideh Mahabadi, Ali Vakilian:
Streaming Algorithms for Connectivity Augmentation. ICALP 2024: 93:1-93:20 - [i34]Lee Cohen, Saeed Sharifi-Malvajerdi, Kevin Stangl, Ali Vakilian, Juba Ziani:
Bayesian Strategic Classification. CoRR abs/2402.08758 (2024) - [i33]Ce Jin, Michael Kapralov, Sepideh Mahabadi, Ali Vakilian:
Streaming Algorithms for Connectivity Augmentation. CoRR abs/2402.10806 (2024) - [i32]Adela Frances DePavia, Erasmo Tani, Ali Vakilian:
Learning-Based Algorithms for Graph Searching Problems. CoRR abs/2402.17736 (2024) - [i31]Ron Mosenzon, Ali Vakilian:
Scalable Algorithms for Individual Preference Stable Clustering. CoRR abs/2403.10365 (2024) - [i30]Sayan Bandyapadhyay, Eden Chlamtác, Yury Makarychev, Ali Vakilian:
A Polynomial-Time Approximation for Pairwise Fair k-Median Clustering. CoRR abs/2405.10378 (2024) - [i29]Emily Diana, Saeed Sharifi-Malvajerdi, Ali Vakilian:
Minimax Group Fairness in Strategic Classification. CoRR abs/2410.02513 (2024) - 2023
- [c33]Eden Chlamtác, Yury Makarychev, Ali Vakilian:
Approximating Red-Blue Set Cover and Minimum Monotone Satisfying Assignment. APPROX/RANDOM 2023: 11:1-11:19 - [c32]Yi Li, Honghao Lin, Simin Liu, Ali Vakilian, David P. Woodruff:
Learning the Positions in CountSketch. ICLR 2023 - [c31]Lee Cohen, Saeed Sharifi-Malvajerdi, Kevin Stangl, Ali Vakilian, Juba Ziani:
Sequential Strategic Screening. ICML 2023: 6279-6295 - [c30]Sèdjro Salomon Hotegni, Sepideh Mahabadi, Ali Vakilian:
Approximation Algorithms for Fair Range Clustering. ICML 2023: 13270-13284 - [c29]Anders Aamand, Justin Y. Chen, Allen Liu, Sandeep Silwal, Pattara Sukprasert, Ali Vakilian, Fred Zhang:
Constant Approximation for Individual Preference Stable Clustering. NeurIPS 2023 - [c28]Anders Aamand, Justin Y. Chen, Huy Lê Nguyen, Sandeep Silwal, Ali Vakilian:
Improved Frequency Estimation Algorithms with and without Predictions. NeurIPS 2023 - [c27]Aditya Bhaskara, Sepideh Mahabadi, Ali Vakilian:
Tight Bounds for Volumetric Spanners and Applications. NeurIPS 2023 - [i28]Lee Cohen, Saeed Sharifi-Malvajerdi, Kevin Stangl, Ali Vakilian
, Juba Ziani:
Sequential Strategic Screening. CoRR abs/2301.13397 (2023) - [i27]Eden Chlamtác, Yury Makarychev, Ali Vakilian:
Approximating Red-Blue Set Cover. CoRR abs/2302.00213 (2023) - [i26]Yi Li, Honghao Lin, Simin Liu, Ali Vakilian, David P. Woodruff:
Learning the Positions in CountSketch. CoRR abs/2306.06611 (2023) - [i25]Sèdjro Salomon Hotegni, Sepideh Mahabadi, Ali Vakilian:
Approximation Algorithms for Fair Range Clustering. CoRR abs/2306.06778 (2023) - [i24]Anders Aamand, Justin Y. Chen, Allen Liu, Sandeep Silwal, Pattara Sukprasert, Ali Vakilian, Fred Zhang:
Constant Approximation for Individual Preference Stable Clustering. CoRR abs/2309.16840 (2023) - [i23]Aditya Bhaskara, Sepideh Mahabadi, Ali Vakilian:
Tight Bounds for Volumetric Spanners and Applications. CoRR abs/2310.00175 (2023) - [i22]Anders Aamand, Justin Y. Chen, Huy Lê Nguyen, Sandeep Silwal, Ali Vakilian:
Improved Frequency Estimation Algorithms with and without Predictions. CoRR abs/2312.07535 (2023) - 2022
- [c26]Ali Vakilian, Mustafa Yalçiner:
Improved Approximation Algorithms for Individually Fair Clustering. AISTATS 2022: 8758-8779 - [c25]Zhen Dai, Yury Makarychev, Ali Vakilian:
Fair Representation Clustering with Several Protected Classes. FAccT 2022: 814-823 - [c24]Avrim Blum, Kevin Stangl, Ali Vakilian:
Multi Stage Screening: Enforcing Fairness and Maximizing Efficiency in a Pre-Existing Pipeline. FAccT 2022: 1178-1193 - [c23]Saba Ahmadi, Pranjal Awasthi, Samir Khuller, Matthäus Kleindessner, Jamie Morgenstern, Pattara Sukprasert, Ali Vakilian:
Individual Preference Stability for Clustering. ICML 2022: 197-246 - [c22]Justin Y. Chen, Sandeep Silwal, Ali Vakilian, Fred Zhang:
Faster Fundamental Graph Algorithms via Learned Predictions. ICML 2022: 3583-3602 - [c21]Eden Chlamtác, Yury Makarychev, Ali Vakilian:
Approximating Fair Clustering with Cascaded Norm Objectives. SODA 2022: 2664-2683 - [i21]Zhen Dai, Yury Makarychev, Ali Vakilian:
Fair Representation Clustering with Several Protected Classes. CoRR abs/2202.01391 (2022) - [i20]Avrim Blum, Kevin Stangl, Ali Vakilian:
Multi Stage Screening: Enforcing Fairness and Maximizing Efficiency in a Pre-Existing Pipeline. CoRR abs/2203.07513 (2022) - [i19]Justin Y. Chen, Sandeep Silwal, Ali Vakilian, Fred Zhang:
Faster Fundamental Graph Algorithms via Learned Predictions. CoRR abs/2204.12055 (2022) - [i18]Saba Ahmadi, Pranjal Awasthi, Samir Khuller, Matthäus Kleindessner, Jamie Morgenstern, Pattara Sukprasert, Ali Vakilian:
Individual Preference Stability for Clustering. CoRR abs/2207.03600 (2022) - 2021
- [j3]Chandra Chekuri, Alina Ene, Ali Vakilian:
Node-weighted Network Design in Planar and Minor-closed Families of Graphs. ACM Trans. Algorithms 17(2): 14:1-14:25 (2021) - [c20]Yury Makarychev, Ali Vakilian:
Approximation Algorithms for Socially Fair Clustering. COLT 2021: 3246-3264 - [c19]Ilias Diakonikolas, Vasilis Kontonis, Christos Tzamos, Ali Vakilian, Nikos Zarifis:
Learning Online Algorithms with Distributional Advice. ICML 2021: 2687-2696 - [i17]Yury Makarychev, Ali Vakilian:
Approximation Algorithms for Socially Fair Clustering. CoRR abs/2103.02512 (2021) - [i16]Ali Vakilian, Mustafa Yalçiner:
Improved Approximation Algorithms for Individually Fair Clustering. CoRR abs/2106.14043 (2021) - [i15]Eden Chlamtác, Yury Makarychev, Ali Vakilian:
Approximating Fair Clustering with Cascaded Norm Objectives. CoRR abs/2111.04804 (2021) - 2020
- [c18]Sepideh Mahabadi, Ali Vakilian:
Individual Fairness for k-Clustering. ICML 2020: 6586-6596 - [c17]Christoph Grunau, Slobodan Mitrovic, Ronitt Rubinfeld, Ali Vakilian:
Improved Local Computation Algorithm for Set Cover via Sparsification. SODA 2020: 2993-3011 - [i14]Sepideh Mahabadi, Ali Vakilian:
(Individual) Fairness for k-Clustering. CoRR abs/2002.06742 (2020) - [i13]Simin Liu, Tianrui Liu, Ali Vakilian, Yulin Wan, David P. Woodruff:
On Learned Sketches for Randomized Numerical Linear Algebra. CoRR abs/2007.09890 (2020)
2010 – 2019
- 2019
- [c16]Piotr Indyk, Ali Vakilian, Tal Wagner, David P. Woodruff:
Sample-Optimal Low-Rank Approximation of Distance Matrices. COLT 2019: 1723-1751 - [c15]Erik D. Demaine, Timothy D. Goodrich, Kyle Kloster, Brian Lavallee, Quanquan C. Liu, Blair D. Sullivan, Ali Vakilian, Andrew van der Poel:
Structural Rounding: Approximation Algorithms for Graphs Near an Algorithmically Tractable Class. ESA 2019: 37:1-37:15 - [c14]Chen-Yu Hsu, Piotr Indyk, Dina Katabi, Ali Vakilian:
Learning-Based Frequency Estimation Algorithms. ICLR (Poster) 2019 - [c13]Arturs Backurs, Piotr Indyk, Krzysztof Onak, Baruch Schieber, Ali Vakilian, Tal Wagner:
Scalable Fair Clustering. ICML 2019: 405-413 - [c12]Merav Parter, Ronitt Rubinfeld, Ali Vakilian, Anak Yodpinyanee:
Local Computation Algorithms for Spanners. ITCS 2019: 58:1-58:21 - [c11]Piotr Indyk, Ali Vakilian, Yang Yuan:
Learning-Based Low-Rank Approximations. NeurIPS 2019: 7400-7410 - [c10]Piotr Indyk, Ali Vakilian:
Tight Trade-offs for the Maximum k-Coverage Problem in the General Streaming Model. PODS 2019: 200-217 - [i12]Arturs Backurs, Piotr Indyk, Krzysztof Onak, Baruch Schieber, Ali Vakilian, Tal Wagner:
Scalable Fair Clustering. CoRR abs/1902.03519 (2019) - [i11]Piotr Indyk, Sepideh Mahabadi, Ronitt Rubinfeld, Ali Vakilian, Anak Yodpinyanee:
Set Cover in Sub-linear Time. CoRR abs/1902.03534 (2019) - [i10]Merav Parter, Ronitt Rubinfeld, Ali Vakilian, Anak Yodpinyanee:
Local Computation Algorithms for Spanners. CoRR abs/1902.08266 (2019) - [i9]Piotr Indyk, Ali Vakilian, Tal Wagner, David P. Woodruff:
Sample-Optimal Low-Rank Approximation of Distance Matrices. CoRR abs/1906.00339 (2019) - [i8]Anders Aamand, Piotr Indyk, Ali Vakilian:
(Learned) Frequency Estimation Algorithms under Zipfian Distribution. CoRR abs/1908.05198 (2019) - [i7]Chandra Chekuri, Alina Ene, Ali Vakilian:
Node-Weighted Network Design in Planar and Minor-Closed Families of Graphs. CoRR abs/1910.07616 (2019) - [i6]Piotr Indyk, Ali Vakilian, Yang Yuan:
Learning-Based Low-Rank Approximations. CoRR abs/1910.13984 (2019) - [i5]Christoph Grunau, Slobodan Mitrovic, Ronitt Rubinfeld, Ali Vakilian:
Improved Local Computation Algorithm for Set Cover via Sparsification. CoRR abs/1910.14154 (2019) - 2018
- [j2]Yodsawalai Chodpathumwan, Ali Vakilian, Arash Termehchy, Amir Nayyeri:
Cost-effective conceptual design using taxonomies. VLDB J. 27(3): 369-394 (2018) - [c9]Piotr Indyk, Sepideh Mahabadi, Ronitt Rubinfeld, Ali Vakilian, Anak Yodpinyanee:
Set Cover in Sub-linear Time. SODA 2018: 2467-2486 - [i4]Erik D. Demaine, Timothy D. Goodrich, Kyle Kloster, Brian Lavallee, Quanquan C. Liu, Blair D. Sullivan, Ali Vakilian, Andrew van der Poel:
Structural Rounding: Approximation Algorithms for Graphs Near an Algorithmically Tractable Class. CoRR abs/1806.02771 (2018) - 2017
- [c8]Piotr Indyk, Sepideh Mahabadi, Ronitt Rubinfeld, Jonathan R. Ullman, Ali Vakilian, Anak Yodpinyanee:
Fractional Set Cover in the Streaming Model. APPROX-RANDOM 2017: 12:1-12:20 - [c7]Ali Vakilian, Yodsawalai Chodpathumwan, Arash Termehchy, Amir Nayyeri:
Cost-Effective Conceptual Design Over Taxonomies. WebDB 2017: 35-40 - 2016
- [c6]Sariel Har-Peled, Piotr Indyk, Sepideh Mahabadi, Ali Vakilian:
Towards Tight Bounds for the Streaming Set Cover Problem. PODS 2016: 371-383 - 2015
- [j1]Arash Termehchy, Ali Vakilian, Yodsawalai Chodpathumwan, Marianne Winslett:
Cost-Effective Conceptual Design for Information Extraction. ACM Trans. Database Syst. 40(2): 12:1-12:39 (2015) - [i3]Ali Vakilian, Yodsawalai Chodpathumwan, Arash Termehchy, Amir Nayyeri:
Cost-Effective Conceptual Design Using Taxonomies. CoRR abs/1503.05656 (2015) - [i2]Piotr Indyk, Sepideh Mahabadi, Ali Vakilian:
Towards Tight Bounds for the Streaming Set Cover Problem. CoRR abs/1509.00118 (2015) - 2014
- [c5]Arash Termehchy, Ali Vakilian, Yodsawalai Chodpathumwan, Marianne Winslett:
Which concepts are worth extracting? SIGMOD Conference 2014: 779-790 - [c4]Alina Ene, Ali Vakilian:
Improved approximation algorithms for degree-bounded network design problems with node connectivity requirements. STOC 2014: 754-763 - [c3]Erik D. Demaine, Piotr Indyk, Sepideh Mahabadi, Ali Vakilian:
On Streaming and Communication Complexity of the Set Cover Problem. DISC 2014: 484-498 - 2013
- [i1]Alina Ene, Nitish Korula, Ali Vakilian:
Improved Approximation Algorithms for Connected Domatic Partitions and Related Problems. CoRR abs/1305.4308 (2013) - 2012
- [c2]Chandra Chekuri, Alina Ene, Ali Vakilian:
Prize-Collecting Survivable Network Design in Node-Weighted Graphs. APPROX-RANDOM 2012: 98-109 - [c1]Chandra Chekuri, Alina Ene, Ali Vakilian:
Node-Weighted Network Design in Planar and Minor-Closed Families of Graphs. ICALP (1) 2012: 206-217
Coauthor Index
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