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ORCIDMaria-Florina Balcan
Nina Balcan – Maria-Florina Popa
Person information
- affiliation: Georgia Institute of Technology , School of Computer Science
- affiliation: Carnegie Mellon University, Computer Science Department
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Journal Articles
- 2023
[j29]Maria-Florina Balcan, Avrim Blum, Dravyansh Sharma, Hongyang Zhang:
An Analysis of Robustness of Non-Lipschitz Networks. J. Mach. Learn. Res. 24: 98:1-98:43 (2023)- 2020
- [j28]Maria-Florina Balcan, Nika Haghtalab, Colin White:
k-center Clustering under Perturbation Resilience. ACM Trans. Algorithms 16(2): 22:1-22:39 (2020) - [j27]Maria-Florina Balcan, Avrim Blum, Vaishnavh Nagarajan:
Lifelong learning in costly feature spaces. Theor. Comput. Sci. 808: 14-37 (2020) - 2019
- [j26]Maria-Florina Balcan, Yingyu Liang, Zhao Song, David P. Woodruff, Hongyang Zhang:
Non-Convex Matrix Completion and Related Problems via Strong Duality. J. Mach. Learn. Res. 20: 102:1-102:56 (2019) - 2018
- [j25]Maria-Florina Balcan, Nicholas J. A. Harvey:
Submodular Functions: Learnability, Structure, and Optimization. SIAM J. Comput. 47(3): 703-754 (2018) - 2017
- [j24]Pranjal Awasthi, Maria-Florina Balcan, Philip M. Long:
The Power of Localization for Efficiently Learning Linear Separators with Noise. J. ACM 63(6): 50:1-50:27 (2017) - [j23]Nan Du, Yingyu Liang, Maria-Florina Balcan, Manuel Gomez-Rodriguez, Hongyuan Zha, Le Song:
Scalable Influence Maximization for Multiple Products in Continuous-Time Diffusion Networks. J. Mach. Learn. Res. 18: 2:1-2:45 (2017) - [j22]Pranjal Awasthi, Maria-Florina Balcan, Konstantin Voevodski
:
Local algorithms for interactive clustering. J. Mach. Learn. Res. 18: 3:1-3:35 (2017) - [j21]Maria-Florina Balcan, Mark Braverman:
Nash Equilibria in Perturbation-Stable Games. Theory Comput. 13(1): 1-31 (2017) - 2016
- [j20]Maria-Florina Balcan, Yingyu Liang:
Clustering under Perturbation Resilience. SIAM J. Comput. 45(1): 102-155 (2016) - 2015
- [j19]Maria-Florina Balcan, Vitaly Feldman:
Statistical Active Learning Algorithms for Noise Tolerance and Differential Privacy. Algorithmica 72(1): 282-315 (2015) - 2014
- [j18]Maria-Florina Balcan, Yingyu Liang, Pramod Gupta:
Robust hierarchical clustering. J. Mach. Learn. Res. 15(1): 3831-3871 (2014) - [j17]Maria-Florina Balcan, Sara Krehbiel, Georgios Piliouras, Jinwoo Shin:
Near-Optimality in Covering Games by Exposing Global Information. ACM Trans. Economics and Comput. 2(4): 13:1-13:22 (2014) - 2013
- [j16]Maria-Florina Balcan, Avrim Blum, Anupam Gupta:
Clustering under approximation stability. J. ACM 60(2): 8:1-8:34 (2013) - [j15]Maria-Florina Balcan, Avrim Blum, Yishay Mansour:
Circumventing the Price of Anarchy: Leading Dynamics to Good Behavior. SIAM J. Comput. 42(1): 230-264 (2013) - [j14]Maria-Florina Balcan, Mark Braverman, Daniel A. Spielman:
Special Section on the Fiftieth Annual IEEE Symposium on Foundations of Computer Science (FOCS 2009). SIAM J. Comput. 42(6): 2286 (2013) - [j13]Maria-Florina Balcan, Avrim Blum, Yishay Mansour:
The Price of Uncertainty. ACM Trans. Economics and Comput. 1(3): 15:1-15:29 (2013) - 2012
- [j12]Konstantin Voevodski, Maria-Florina Balcan, Heiko Röglin, Shang-Hua Teng, Yu Xia:
Active Clustering of Biological Sequences. J. Mach. Learn. Res. 13: 203-225 (2012) - 2011
- [j11]Maria-Florina Balcan:
Leading dynamics to good behavior. SIGecom Exch. 10(2): 19-22 (2011) - 2010
- [j10]Maria-Florina Balcan, Avrim Blum:
A discriminative model for semi-supervised learning. J. ACM 57(3): 19:1-19:46 (2010) - [j9]Maria-Florina Balcan, Steve Hanneke, Jennifer Wortman Vaughan:
The true sample complexity of active learning. Mach. Learn. 80(2-3): 111-139 (2010) - 2009
- [j8]Maria-Florina Balcan, Alina Beygelzimer, John Langford:
Agnostic active learning. J. Comput. Syst. Sci. 75(1): 78-89 (2009) - 2008
- [j7]Maria-Florina Balcan, Avrim Blum, Jason D. Hartline, Yishay Mansour:
Reducing mechanism design to algorithm design via machine learning. J. Comput. Syst. Sci. 74(8): 1245-1270 (2008) - [j6]Maria-Florina Balcan, Avrim Blum, Nathan Srebro:
A theory of learning with similarity functions. Mach. Learn. 72(1-2): 89-112 (2008) - [j5]Maria-Florina Balcan, Nikhil Bansal, Alina Beygelzimer, Don Coppersmith, John Langford, Gregory B. Sorkin:
Robust reductions from ranking to classification. Mach. Learn. 72(1-2): 139-153 (2008) - [j4]Maria-Florina Balcan, Avrim Blum, Yishay Mansour:
Item pricing for revenue maximization. SIGecom Exch. 7(3) (2008) - 2007
- [j3]Maria-Florina Balcan, Avrim Blum:
Mechanism design, machine learning, and pricing problems. SIGecom Exch. 7(1): 34-36 (2007) - [j2]Maria-Florina Balcan, Avrim Blum:
Approximation Algorithms and Online Mechanisms for Item Pricing. Theory Comput. 3(1): 179-195 (2007) - 2006
- [j1]Maria-Florina Balcan, Avrim Blum, Santosh S. Vempala:
Kernels as features: On kernels, margins, and low-dimensional mappings. Mach. Learn. 65(1): 79-94 (2006)
Conference and Workshop Papers
- 2023
- [c121]Maria-Florina Balcan, Rattana Pukdee, Pradeep Ravikumar, Hongyang Zhang:
Nash Equilibria and Pitfalls of Adversarial Training in Adversarial Robustness Games. AISTATS 2023: 9607-9636 - [c120]Rattana Pukdee, Dylan Sam, Pradeep Kumar Ravikumar, Nina Balcan:
Label Propagation with Weak Supervision. ICLR 2023 - [c119]Maria-Florina Balcan, Steve Hanneke, Rattana Pukdee, Dravyansh Sharma:
Reliable learning in challenging environments. NeurIPS 2023 - [c118]Maria-Florina Balcan, Anh Nguyen, Dravyansh Sharma:
New Bounds for Hyperparameter Tuning of Regression Problems Across Instances. NeurIPS 2023 - [c117]Misha Khodak, Ilya Osadchiy, Keegan Harris, Maria-Florina Balcan, Kfir Y. Levy, Ron Meir, Steven Z. Wu:
Meta-Learning Adversarial Bandit Algorithms. NeurIPS 2023 - [c116]Siddharth Prasad, Maria-Florina Balcan, Tuomas Sandholm:
Bicriteria Multidimensional Mechanism Design with Side Information. NeurIPS 2023 - [c115]Rattana Pukdee, Dylan Sam, J. Zico Kolter, Maria-Florina Balcan, Pradeep Ravikumar:
Learning with Explanation Constraints. NeurIPS 2023 - 2022
- [c114]Maria-Florina Balcan, Avrim Blum, Steve Hanneke, Dravyansh Sharma:
Robustly-reliable learners under poisoning attacks. COLT 2022: 4498-4534 - [c113]Maria-Florina Balcan, Siddharth Prasad, Tuomas Sandholm, Ellen Vitercik:
Improved Sample Complexity Bounds for Branch-And-Cut. CP 2022: 3:1-3:19 - [c112]Maria-Florina Balcan, Misha Khodak, Dravyansh Sharma, Ameet Talwalkar:
Provably tuning the ElasticNet across instances. NeurIPS 2022 - [c111]Maria-Florina Balcan, Siddharth Prasad, Tuomas Sandholm:
Maximizing Revenue under Market Shrinkage and Market Uncertainty. NeurIPS 2022 - [c110]Maria-Florina Balcan, Siddharth Prasad, Tuomas Sandholm, Ellen Vitercik:
Structural Analysis of Branch-and-Cut and the Learnability of Gomory Mixed Integer Cuts. NeurIPS 2022 - [c109]Misha Khodak, Maria-Florina Balcan, Ameet Talwalkar, Sergei Vassilvitskii:
Learning Predictions for Algorithms with Predictions. NeurIPS 2022 - [c108]Maria-Florina Balcan:
Generalization Guarantees for Data-Driven Mechanism Design (Invited Talk). STACS 2022: 2:1-2:1 - 2021
- [c107]Maria-Florina Balcan, Tuomas Sandholm, Ellen Vitercik:
Generalization in Portfolio-Based Algorithm Selection. AAAI 2021: 12225-12232 - [c106]Liam Li, Mikhail Khodak, Nina Balcan, Ameet Talwalkar:
Geometry-Aware Gradient Algorithms for Neural Architecture Search. ICLR 2021 - [c105]Maria-Florina Balcan, Siddharth Prasad, Tuomas Sandholm:
Learning Within an Instance for Designing High-Revenue Combinatorial Auctions. IJCAI 2021: 31-37 - [c104]Maria-Florina Balcan, Siddharth Prasad, Tuomas Sandholm, Ellen Vitercik:
Sample Complexity of Tree Search Configuration: Cutting Planes and Beyond. NeurIPS 2021: 4015-4027 - [c103]Maria-Florina Balcan, Dravyansh Sharma:
Data driven semi-supervised learning. NeurIPS 2021: 14782-14794 - [c102]Maria-Florina Balcan, Mikhail Khodak, Dravyansh Sharma, Ameet Talwalkar:
Learning-to-learn non-convex piecewise-Lipschitz functions. NeurIPS 2021: 15056-15069 - [c101]Mikhail Khodak, Renbo Tu, Tian Li, Liam Li, Maria-Florina Balcan, Virginia Smith, Ameet Talwalkar:
Federated Hyperparameter Tuning: Challenges, Baselines, and Connections to Weight-Sharing. NeurIPS 2021: 19184-19197 - [c100]Maria-Florina Balcan, Dan F. DeBlasio, Travis Dick, Carl Kingsford, Tuomas Sandholm, Ellen Vitercik:
How much data is sufficient to learn high-performing algorithms? generalization guarantees for data-driven algorithm design. STOC 2021: 919-932 - 2020
- [c99]Maria-Florina Balcan, Tuomas Sandholm, Ellen Vitercik:
Learning to Optimize Computational Resources: Frugal Training with Generalization Guarantees. AAAI 2020: 3227-3234 - [c98]Dravyansh Sharma, Maria-Florina Balcan, Travis Dick:
Learning piecewise Lipschitz functions in changing environments. AISTATS 2020: 3567-3577 - [c97]Maria-Florina Balcan, Travis Dick, Manuel Lang:
Learning to Link. ICLR 2020 - [c96]Maria-Florina Balcan, Tuomas Sandholm, Ellen Vitercik:
Refined bounds for algorithm configuration: The knife-edge of dual class approximability. ICML 2020: 580-590 - [c95]Maria-Florina Balcan, Siddharth Prasad, Tuomas Sandholm:
Efficient Algorithms for Learning Revenue-Maximizing Two-Part Tariffs. IJCAI 2020: 332-338 - [c94]Travis Dick, Wesley Pegden, Maria-Florina Balcan:
Semi-bandit Optimization in the Dispersed Setting. UAI 2020: 909-918 - 2019
- [c93]Maria-Florina Balcan, Tuomas Sandholm, Ellen Vitercik:
Estimating Approximate Incentive Compatibility. EC 2019: 867 - [c92]Pranjal Awasthi, Ainesh Bakshi, Maria-Florina Balcan, Colin White, David P. Woodruff:
Robust Communication-Optimal Distributed Clustering Algorithms. ICALP 2019: 18:1-18:16 - [c91]Maria-Florina Balcan, Mikhail Khodak, Ameet Talwalkar:
Provable Guarantees for Gradient-Based Meta-Learning. ICML 2019: 424-433 - [c90]Maria-Florina Balcan, Travis Dick, Ritesh Noothigattu, Ariel D. Procaccia:
Envy-Free Classification. NeurIPS 2019: 1238-1248 - [c89]Mikhail Khodak, Maria-Florina Balcan, Ameet Talwalkar:
Adaptive Gradient-Based Meta-Learning Methods. NeurIPS 2019: 5915-5926 - [c88]Maria-Florina Balcan, Yi Li, David P. Woodruff, Hongyang Zhang:
Testing Matrix Rank, Optimally. SODA 2019: 727-746 - 2018
- [c87]Maria-Florina Balcan, Avrim Blum, Shang-Tse Chen:
Diversified Strategies for Mitigating Adversarial Attacks in Multiagent Systems. AAMAS 2018: 407-415 - [c86]Maria-Florina Balcan, Travis Dick, Ellen Vitercik:
Dispersion for Data-Driven Algorithm Design, Online Learning, and Private Optimization. FOCS 2018: 603-614 - [c85]Maria-Florina Balcan, Travis Dick, Tuomas Sandholm, Ellen Vitercik:
Learning to Branch. ICML 2018: 353-362 - [c84]Maria-Florina Balcan, Yingyu Liang, David P. Woodruff, Hongyang Zhang:
Matrix Completion and Related Problems via Strong Duality. ITCS 2018: 5:1-5:22 - [c83]Maria-Florina Balcan, Travis Dick, Colin White:
Data-Driven Clustering via Parameterized Lloyd's Families. NeurIPS 2018: 10664-10674 - [c82]Maria-Florina Balcan, Tuomas Sandholm, Ellen Vitercik:
A General Theory of Sample Complexity for Multi-Item Profit Maximization. EC 2018: 173-174 - 2017
- [c81]Maria-Florina Balcan, Travis Dick, Yishay Mansour:
Label Efficient Learning by Exploiting Multi-Class Output Codes. AAAI 2017: 1735-1741 - [c80]Travis Dick, Mu Li, Venkata Krishna Pillutla, Colin White, Maria-Florina Balcan, Alexander J. Smola:
Data Driven Resource Allocation for Distributed Learning. AAAI Workshops 2017 - [c79]Travis Dick, Mu Li, Venkata Krishna Pillutla, Colin White, Nina Balcan, Alexander J. Smola:
Data Driven Resource Allocation for Distributed Learning. AISTATS 2017: 662-671 - [c78]Maria-Florina Balcan, Avrim Blum, Vaishnavh Nagarajan:
Lifelong Learning in Costly Feature Spaces. ALT 2017: 250-287 - [c77]Maria-Florina Balcan, Vaishnavh Nagarajan, Ellen Vitercik, Colin White:
Learning-Theoretic Foundations of Algorithm Configuration for Combinatorial Partitioning Problems. COLT 2017: 213-274 - [c76]Daniel McNamara, Maria-Florina Balcan:
Performance guarantees for transferring representations. ICLR (Workshop) 2017 - [c75]Maria-Florina Balcan, Travis Dick, Yingyu Liang, Wenlong Mou, Hongyang Zhang:
Differentially Private Clustering in High-Dimensional Euclidean Spaces. ICML 2017: 322-331 - [c74]Daniel McNamara, Maria-Florina Balcan:
Risk Bounds for Transferring Representations With and Without Fine-Tuning. ICML 2017: 2373-2381 - [c73]Maria-Florina Balcan, Hongyang Zhang:
Sample and Computationally Efficient Learning Algorithms under S-Concave Distributions. NIPS 2017: 4796-4805 - 2016
- [c72]Shang-Tse Chen, Maria-Florina Balcan, Duen Horng Chau:
Communication Efficient Distributed Agnostic Boosting. AISTATS 2016: 1299-1307 - [c71]Gautam Dasarathy, Aarti Singh, Maria-Florina Balcan, Jong Hyuk Park:
Active Learning Algorithms for Graphical Model Selection. AISTATS 2016: 1356-1364 - [c70]Pranjal Awasthi, Maria-Florina Balcan, Nika Haghtalab, Hongyang Zhang:
Learning and 1-bit Compressed Sensing under Asymmetric Noise. COLT 2016: 152-192 - [c69]Maria-Florina Balcan, Simon Shaolei Du, Yining Wang, Adams Wei Yu:
An Improved Gap-Dependency Analysis of the Noisy Power Method. COLT 2016: 284-309 - [c68]Maria-Florina Balcan, Ellen Vitercik, Colin White:
Learning Combinatorial Functions from Pairwise Comparisons. COLT 2016: 310-335 - [c67]Maria-Florina Balcan, Nika Haghtalab, Colin White:
k-Center Clustering Under Perturbation Resilience. ICALP 2016: 68:1-68:14 - [c66]Maria-Florina Balcan, Yingyu Liang, Le Song, David P. Woodruff, Bo Xie:
Communication Efficient Distributed Kernel Principal Component Analysis. KDD 2016: 725-734 - [c65]Maria-Florina Balcan, Tuomas Sandholm, Ellen Vitercik:
Sample Complexity of Automated Mechanism Design. NIPS 2016: 2083-2091 - [c64]Maria-Florina Balcan, Hongyang Zhang:
Noise-Tolerant Life-Long Matrix Completion via Adaptive Sampling. NIPS 2016: 2955-2963 - 2015
- [c63]Maria-Florina Balcan:
Learning Submodular Functions with Applications to Multi-Agent Systems. AAMAS 2015: 3 - [c62]Pranjal Awasthi, Maria-Florina Balcan, Nika Haghtalab, Ruth Urner:
Efficient Learning of Linear Separators under Bounded Noise. COLT 2015: 167-190 - [c61]Maria-Florina Balcan, Avrim Blum, Santosh S. Vempala:
Efficient Representations for Lifelong Learning and Autoencoding. COLT 2015: 191-210 - [c60]Maria-Florina Balcan, Ariel D. Procaccia, Yair Zick:
Learning Cooperative Games. IJCAI 2015: 475-481 - [c59]Aurélien Bellet, Yingyu Liang, Alireza Bagheri Garakani, Maria-Florina Balcan, Fei Sha:
A Distributed Frank-Wolfe Algorithm for Communication-Efficient Sparse Learning. SDM 2015: 478-486 - [c58]Maria-Florina Balcan, Avrim Blum, Nika Haghtalab, Ariel D. Procaccia:
Commitment Without Regrets: Online Learning in Stackelberg Security Games. EC 2015: 61-78 - 2014
- [c57]Maria-Florina Balcan, Christopher Berlind:
A New Perspective on Learning Linear Separators with Large \(L_qL_p\) Margins. AISTATS 2014: 68-76 - [c56]Pranjal Awasthi, Maria-Florina Balcan, Konstantin Voevodski:
Local algorithms for interactive clustering. ICML 2014: 550-558 - [c55]Nan Du, Yingyu Liang, Maria-Florina Balcan, Le Song:
Influence Function Learning in Information Diffusion Networks. ICML 2014: 2016-2024 - [c54]Maria-Florina Balcan, Christopher Berlind, Avrim Blum, Emma Cohen, Kaushik Patnaik, Le Song:
Active Learning and Best-Response Dynamics. NIPS 2014: 2222-2230 - [c53]Bo Dai, Bo Xie, Niao He, Yingyu Liang, Anant Raj, Maria-Florina Balcan, Le Song:
Scalable Kernel Methods via Doubly Stochastic Gradients. NIPS 2014: 3041-3049 - [c52]Yingyu Liang, Maria-Florina Balcan, Vandana Kanchanapally, David P. Woodruff:
Improved Distributed Principal Component Analysis. NIPS 2014: 3113-3121 - [c51]Nan Du, Yingyu Liang, Maria-Florina Balcan, Le Song:
Learning Time-Varying Coverage Functions. NIPS 2014: 3374-3382 - [c50]Pranjal Awasthi, Maria-Florina Balcan, Philip M. Long:
The power of localization for efficiently learning linear separators with noise. STOC 2014: 449-458 - [c49]Maria-Florina Balcan, Amit Daniely, Ruta Mehta, Ruth Urner, Vijay V. Vazirani:
Learning Economic Parameters from Revealed Preferences. WINE 2014: 338-353 - 2013
- [c48]Maria-Florina Balcan, Philip M. Long:
Active and passive learning of linear separators under log-concave distributions. COLT 2013: 288-316 - [c47]Nina Balcan, Christopher Berlind, Steven Ehrlich, Yingyu Liang:
Efficient Semi-supervised and Active Learning of Disjunctions. ICML (1) 2013: 633-641 - [c46]Nina Balcan, Avrim Blum, Yishay Mansour:
Exploiting Ontology Structures and Unlabeled Data for Learning. ICML (3) 2013: 1112-1120 - [c45]Maria-Florina Balcan, Vitaly Feldman:
Statistical Active Learning Algorithms. NIPS 2013: 1295-1303 - [c44]Maria-Florina Balcan, Steven Ehrlich, Yingyu Liang:
Distributed k-means and k-median clustering on general communication topologies. NIPS 2013: 1995-2003 - [c43]Maria-Florina Balcan, Yingyu Liang:
Modeling and Detecting Community Hierarchies. SIMBAD 2013: 160-175 - [c42]Maria-Florina Balcan, Christian Borgs, Mark Braverman, Jennifer T. Chayes, Shang-Hua Teng:
Finding Endogenously Formed Communities. SODA 2013: 767-783 - 2012
- [c41]Maria-Florina Balcan, Sara Krehbiel, Georgios Piliouras, Jinwoo Shin:
Minimally invasive mechanism design: Distributed covering with carefully chosen advice. CDC 2012: 2690-2695 - [c40]Maria-Florina Balcan, Eric Blais, Avrim Blum, Liu Yang:
Active Property Testing. FOCS 2012: 21-30 - [c39]Maria-Florina Balcan, Yingyu Liang:
Clustering under Perturbation Resilience. ICALP (1) 2012: 63-74 - [c38]Maria-Florina Balcan, Nicholas J. A. Harvey:
Learning Submodular Functions. ECML/PKDD (2) 2012: 846-849 - [c37]Maria-Florina Balcan, Florin Constantin, Satoru Iwata, Lei Wang:
Learning Valuation Functions. COLT 2012: 4.1-4.24 - [c36]Maria-Florina Balcan, Steve Hanneke:
Robust Interactive Learning. COLT 2012: 20.1-20.34 - [c35]Maria-Florina Balcan, Avrim Blum, Shai Fine, Yishay Mansour:
Distributed Learning, Communication Complexity and Privacy. COLT 2012: 26.1-26.22 - 2011
- [c34]Alireza Fathi, Maria-Florina Balcan, Xiaofeng Ren, James M. Rehg:
Combining Self Training and Active Learning for Video Segmentation. BMVC 2011: 1-11 - [c33]Maria-Florina Balcan, Florin Constantin, Georgios Piliouras, Jeff S. Shamma:
Game couplings: Learning dynamics and applications. CDC/ECC 2011: 2441-2446 - [c32]Konstantin Voevodski, Maria-Florina Balcan, Heiko Röglin, Shang-Hua Teng, Yu Xia:
Min-sum Clustering of Protein Sequences with Limited Distance Information. SIMBAD 2011: 192-206 - [c31]Maria-Florina Balcan, Nicholas J. A. Harvey:
Learning submodular functions. STOC 2011: 793-802 - [c30]Maria-Florina Balcan, Florin Constantin, Steven Ehrlich:
The Snowball Effect of Uncertainty in Potential Games. WINE 2011: 1-12 - 2010
- [c29]Maria-Florina Balcan, Pramod Gupta:
Robust Hierarchical Clustering. COLT 2010: 282-294 - [c28]Maria-Florina Balcan, Avrim Blum, Yishay Mansour:
Circumventing the Price of Anarchy: Leading Dynamics to Good Behavior. ICS 2010: 200-213 - [c27]Pranjal Awasthi, Maria-Florina Balcan, Avrim Blum, Or Sheffet, Santosh S. Vempala:
On Nash-Equilibria of Approximation-Stable Games. SAGT 2010: 78-89 - [c26]Aaron Roth, Maria-Florina Balcan, Adam Kalai, Yishay Mansour:
On the Equilibria of Alternating Move Games. SODA 2010: 805-816 - [c25]Konstantin Voevodski, Maria-Florina Balcan, Heiko Röglin, Shang-Hua Teng, Yu Xia:
Efficient Clustering with Limited Distance Information. UAI 2010: 632-640 - [c24]Maria-Florina Balcan, Florin Constantin:
Sequential Item Pricing for Unlimited Supply. WINE 2010: 50-62 - 2009
- [c23]Maria-Florina Balcan, Heiko Röglin, Shang-Hua Teng:
Agnostic Clustering. ALT 2009: 384-398 - [c22]Maria-Florina Balcan:
Better Guarantees for Sparsest Cut Clustering. COLT 2009 - [c21]Maria-Florina Balcan, Mark Braverman:
Finding Low Error Clusterings. COLT 2009 - [c20]Maria-Florina Balcan, Avrim Blum, Yishay Mansour:
The price of uncertainty. EC 2009: 285-294 - [c19]Maria-Florina Balcan, Avrim Blum, Yishay Mansour:
Improved equilibria via public service advertising. SODA 2009: 728-737 - [c18]Maria-Florina Balcan, Avrim Blum, Anupam Gupta:
Approximate clustering without the approximation. SODA 2009: 1068-1077 - 2008
- [c17]Maria-Florina Balcan, Avrim Blum:
Clustering with Interactive Feedback. ALT 2008: 316-328 - [c16]Maria-Florina Balcan, Steve Hanneke, Jennifer Wortman:
The True Sample Complexity of Active Learning. COLT 2008: 45-56 - [c15]Maria-Florina Balcan, Avrim Blum, Nathan Srebro:
Improved Guarantees for Learning via Similarity Functions. COLT 2008: 287-298 - [c14]Maria-Florina Balcan, Avrim Blum, Yishay Mansour:
Item pricing for revenue maximization. EC 2008: 50-59 - [c13]Maria-Florina Balcan, Avrim Blum, Santosh S. Vempala:
A discriminative framework for clustering via similarity functions. STOC 2008: 671-680 - 2007
- [c12]Maria-Florina Balcan, Andrei Z. Broder, Tong Zhang:
Margin Based Active Learning. COLT 2007: 35-50 - [c11]Maria-Florina Balcan, Nikhil Bansal, Alina Beygelzimer, Don Coppersmith, John Langford, Gregory B. Sorkin:
Robust Reductions from Ranking to Classification. COLT 2007: 604-619 - [c10]Avrim Blum, Maria-Florina Balcan:
Open Problems in Efficient Semi-supervised PAC Learning. COLT 2007: 622-624 - [c9]Maria-Florina Balcan, Avrim Blum, T.-H. Hubert Chan, MohammadTaghi Hajiaghayi:
A Theory of Loss-Leaders: Making Money by Pricing Below Cost. WINE 2007: 293-299 - 2006
- [c8]Maria-Florina Balcan, Alina Beygelzimer, John Langford:
Agnostic active learning. ICML 2006: 65-72 - [c7]Maria-Florina Balcan, Avrim Blum:
On a theory of learning with similarity functions. ICML 2006: 73-80 - [c6]Maria-Florina Balcan, Avrim Blum:
Approximation algorithms and online mechanisms for item pricing. EC 2006: 29-35 - 2005
- [c5]Maria-Florina Balcan, Avrim Blum:
A PAC-Style Model for Learning from Labeled and Unlabeled Data. COLT 2005: 111-126 - [c4]Maria-Florina Balcan, Avrim Blum, Jason D. Hartline, Yishay Mansour:
Mechanism Design via Machine Learning. FOCS 2005: 605-614 - 2004
- [c3]Maria-Florina Balcan, Avrim Blum, Santosh S. Vempala:
On Kernels, Margins, and Low-Dimensional Mappings. ALT 2004: 194-205 - [c2]Maria-Florina Balcan, Avrim Blum, Ke Yang:
Co-Training and Expansion: Towards Bridging Theory and Practice. NIPS 2004: 89-96 - 2001
- [c1]Ergina Kavallieratou, Doru-Cristian Balcan, Maria-Florina Popa, Nikos Fakotakis:
Handwritten text localization in skewed documents. ICIP (1) 2001: 1102-1105
Parts in Books or Collections
- 2020
- [p3]Maria-Florina Balcan, Nika Haghtalab:
Noise in Classification. Beyond the Worst-Case Analysis of Algorithms 2020: 361-381 - [p2]Maria-Florina Balcan:
Data-Driven Algorithm Design. Beyond the Worst-Case Analysis of Algorithms 2020: 626-645 - 2006
- [p1]Maria-Florina Balcan, Avrim Blum:
An Augmented PAC Model for Semi-Supervised Learning. Semi-Supervised Learning 2006: 396-419
Editorship
- 2020
- [e3]Hugo Larochelle, Marc'Aurelio Ranzato, Raia Hadsell, Maria-Florina Balcan, Hsuan-Tien Lin:
Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, NeurIPS 2020, December 6-12, 2020, virtual. 2020 [contents] - 2016
- [e2]Maria-Florina Balcan, Kilian Q. Weinberger:
Proceedings of the 33nd International Conference on Machine Learning, ICML 2016, New York City, NY, USA, June 19-24, 2016. JMLR Workshop and Conference Proceedings 48, JMLR.org 2016 [contents] - 2014
- [e1]Maria-Florina Balcan, Vitaly Feldman, Csaba Szepesvári:
Proceedings of The 27th Conference on Learning Theory, COLT 2014, Barcelona, Spain, June 13-15, 2014. JMLR Workshop and Conference Proceedings 35, JMLR.org 2014 [contents]
Reference Works
- 2016
- [r1]Maria-Florina Balcan, Ruth Urner:
Active Learning - Modern Learning Theory. Encyclopedia of Algorithms 2016: 8-13
Informal and Other Publications
- 2024
- [i91]Siddharth Prasad, Ellen Vitercik, Maria-Florina Balcan, Tuomas Sandholm:
New Sequence-Independent Lifting Techniques for Cutting Planes and When They Induce Facets. CoRR abs/2401.13773 (2024) - [i90]Runtian Zhai, Rattana Pukdee, Roger Jin, Maria-Florina Balcan, Pradeep Ravikumar:
Spectrally Transformed Kernel Regression. CoRR abs/2402.00645 (2024) - [i89]Keegan Harris, Zhiwei Steven Wu, Maria-Florina Balcan:
Regret Minimization in Stackelberg Games with Side Information. CoRR abs/2402.08576 (2024) - 2023
- [i88]Maria-Florina Balcan, Hedyeh Beyhaghi:
Learning Revenue Maximizing Menus of Lotteries and Two-Part Tariffs. CoRR abs/2302.11700 (2023) - [i87]Maria-Florina Balcan, Siddharth Prasad, Tuomas Sandholm:
Bicriteria Multidimensional Mechanism Design with Side Information. CoRR abs/2302.14234 (2023) - [i86]Rattana Pukdee, Dylan Sam, J. Zico Kolter, Maria-Florina Balcan, Pradeep Ravikumar:
Learning with Explanation Constraints. CoRR abs/2303.14496 (2023) - [i85]Maria-Florina Balcan, Steve Hanneke, Rattana Pukdee, Dravyansh Sharma:
Reliable Learning for Test-time Attacks and Distribution Shift. CoRR abs/2304.03370 (2023) - [i84]Mikhail Khodak, Ilya Osadchiy, Keegan Harris, Maria-Florina Balcan, Kfir Y. Levy, Ron Meir, Zhiwei Steven Wu:
Meta-Learning Adversarial Bandit Algorithms. CoRR abs/2307.02295 (2023) - [i83]Mikhail Khodak, Edmond Chow, Maria-Florina Balcan, Ameet Talwalkar:
Learning to Relax: Setting Solver Parameters Across a Sequence of Linear System Instances. CoRR abs/2310.02246 (2023) - 2022
- [i82]Mikhail Khodak, Maria-Florina Balcan, Ameet Talwalkar, Sergei Vassilvitskii:
Learning Predictions for Algorithms with Predictions. CoRR abs/2202.09312 (2022) - [i81]Maria-Florina Balcan, Avrim Blum, Steve Hanneke, Dravyansh Sharma:
Robustly-reliable learners under poisoning attacks. CoRR abs/2203.04160 (2022) - [i80]Maria-Florina Balcan, Christopher Seiler, Dravyansh Sharma:
Faster algorithms for learning to link, align sequences, and price two-part tariffs. CoRR abs/2204.03569 (2022) - [i79]Maria-Florina Balcan, Siddharth Prasad, Tuomas Sandholm, Ellen Vitercik:
Structural Analysis of Branch-and-Cut and the Learnability of Gomory Mixed Integer Cuts. CoRR abs/2204.07312 (2022) - [i78]Maria-Florina Balcan, Keegan Harris, Mikhail Khodak, Zhiwei Steven Wu:
Meta-Learning Adversarial Bandits. CoRR abs/2205.14128 (2022) - [i77]Maria-Florina Balcan, Mikhail Khodak, Dravyansh Sharma, Ameet Talwalkar:
Provably tuning the ElasticNet across instances. CoRR abs/2207.10199 (2022) - [i76]Rattana Pukdee, Dylan Sam, Maria-Florina Balcan, Pradeep Ravikumar:
Label Propagation with Weak Supervision. CoRR abs/2210.03594 (2022) - [i75]Maria-Florina Balcan, Rattana Pukdee, Pradeep Ravikumar, Hongyang Zhang:
Nash Equilibria and Pitfalls of Adversarial Training in Adversarial Robustness Games. CoRR abs/2210.12606 (2022) - 2021
- [i74]Maria-Florina Balcan, Dravyansh Sharma:
Data driven algorithms for limited labeled data learning. CoRR abs/2103.10547 (2021) - [i73]Maria-Florina Balcan, Siddharth Prasad, Tuomas Sandholm, Ellen Vitercik:
Sample Complexity of Tree Search Configuration: Cutting Planes and Beyond. CoRR abs/2106.04033 (2021) - [i72]Mikhail Khodak, Renbo Tu, Tian Li, Liam Li, Maria-Florina Balcan, Virginia Smith, Ameet Talwalkar:
Federated Hyperparameter Tuning: Challenges, Baselines, and Connections to Weight-Sharing. CoRR abs/2106.04502 (2021) - [i71]Maria-Florina Balcan, Mikhail Khodak, Dravyansh Sharma, Ameet Talwalkar:
Learning-to-learn non-convex piecewise-Lipschitz functions. CoRR abs/2108.08770 (2021) - [i70]Maria-Florina Balcan, Siddharth Prasad, Tuomas Sandholm, Ellen Vitercik:
Improved Learning Bounds for Branch-and-Cut. CoRR abs/2111.11207 (2021) - 2020
- [i69]Liam Li, Mikhail Khodak, Maria-Florina Balcan, Ameet Talwalkar:
Geometry-Aware Gradient Algorithms for Neural Architecture Search. CoRR abs/2004.07802 (2020) - [i68]Maria-Florina Balcan, Tuomas Sandholm, Ellen Vitercik:
Refined bounds for algorithm configuration: The knife-edge of dual class approximability. CoRR abs/2006.11827 (2020) - [i67]Maria-Florina Balcan, Nika Haghtalab:
Noise in Classification. CoRR abs/2010.05080 (2020) - [i66]Maria-Florina Balcan, Avrim Blum, Dravyansh Sharma, Hongyang Zhang:
On the Power of Abstention and Data-Driven Decision Making for Adversarial Robustness. CoRR abs/2010.06154 (2020) - [i65]Maria-Florina Balcan:
Data-driven Algorithm Design. CoRR abs/2011.07177 (2020) - [i64]Kaiwen Wang, Travis Dick, Maria-Florina Balcan:
Scalable and Provably Accurate Algorithms for Differentially Private Distributed Decision Tree Learning. CoRR abs/2012.10602 (2020) - [i63]Maria-Florina Balcan, Tuomas Sandholm, Ellen Vitercik:
Generalization in portfolio-based algorithm selection. CoRR abs/2012.13315 (2020) - 2019
- [i62]Maria-Florina Balcan, Tuomas Sandholm, Ellen Vitercik:
Estimating Approximate Incentive Compatibility. CoRR abs/1902.09413 (2019) - [i61]Mikhail Khodak, Maria-Florina Balcan, Ameet Talwalkar:
Provable Guarantees for Gradient-Based Meta-Learning. CoRR abs/1902.10644 (2019) - [i60]Maria-Florina Balcan, Travis Dick, Wesley Pegden:
Semi-bandit Optimization in the Dispersed Setting. CoRR abs/1904.09014 (2019) - [i59]Maria-Florina Balcan, Tuomas Sandholm, Ellen Vitercik:
Learning to Optimize Computational Resources: Frugal Training with Generalization Guarantees. CoRR abs/1905.10819 (2019) - [i58]Mikhail Khodak, Maria-Florina Balcan, Ameet Talwalkar:
Adaptive Gradient-Based Meta-Learning Methods. CoRR abs/1906.02717 (2019) - [i57]Maria-Florina Balcan, Travis Dick, Manuel Lang:
Learning to Link. CoRR abs/1907.00533 (2019) - [i56]Maria-Florina Balcan, Travis Dick, Dravyansh Sharma:
Online optimization of piecewise Lipschitz functions in changing environments. CoRR abs/1907.09137 (2019) - [i55]Maria-Florina Balcan, Dan F. DeBlasio, Travis Dick, Carl Kingsford, Tuomas Sandholm, Ellen Vitercik:
How much data is sufficient to learn high-performing algorithms? CoRR abs/1908.02894 (2019) - 2018
- [i54]Maria-Florina Balcan, Travis Dick, Tuomas Sandholm, Ellen Vitercik:
Learning to Branch. CoRR abs/1803.10150 (2018) - [i53]Maria-Florina Balcan, Travis Dick, Colin White:
Data-Driven Clustering via Parameterized Lloyd's Families. CoRR abs/1809.06987 (2018) - [i52]Maria-Florina Balcan, Travis Dick, Ritesh Noothigattu, Ariel D. Procaccia:
Envy-Free Classification. CoRR abs/1809.08700 (2018) - [i51]Maria-Florina Balcan, Yi Li, David P. Woodruff, Hongyang Zhang:
Testing Matrix Rank, Optimally. CoRR abs/1810.08171 (2018) - 2017
- [i50]Pranjal Awasthi, Maria-Florina Balcan, Colin White:
General and Robust Communication-Efficient Algorithms for Distributed Clustering. CoRR abs/1703.00830 (2017) - [i49]Maria-Florina Balcan, Hongyang Zhang:
S-Concave Distributions: Towards Broader Distributions for Noise-Tolerant and Sample-Efficient Learning Algorithms. CoRR abs/1703.07758 (2017) - [i48]Maria-Florina Balcan, Yingyu Liang, David P. Woodruff, Hongyang Zhang:
Optimal Sample Complexity for Matrix Completion and Related Problems via 𝓁s2-Regularization. CoRR abs/1704.08683 (2017) - [i47]Maria-Florina Balcan, Tuomas Sandholm, Ellen Vitercik:
Sample Complexity of Multi-Item Profit Maximization. CoRR abs/1705.00243 (2017) - [i46]Maria-Florina Balcan, Colin White:
Clustering under Local Stability: Bridging the Gap between Worst-Case and Beyond Worst-Case Analysis. CoRR abs/1705.07157 (2017) - [i45]Maria-Florina Balcan, Avrim Blum, Vaishnavh Nagarajan:
Lifelong Learning in Costly Feature Spaces. CoRR abs/1706.10271 (2017) - [i44]Maria-Florina Balcan, Travis Dick, Ellen Vitercik:
Private and Online Optimization of Piecewise Lipschitz Functions. CoRR abs/1711.03091 (2017) - 2016
- [i43]Gautam Dasarathy, Aarti Singh, Maria-Florina Balcan, Jong Hyuk Park:
Active Learning Algorithms for Graphical Model Selection. CoRR abs/1602.00354 (2016) - [i42]Maria-Florina Balcan, Simon S. Du, Yining Wang, Adams Wei Yu:
An Improved Gap-Dependency Analysis of the Noisy Power Method. CoRR abs/1602.07046 (2016) - [i41]Maria-Florina Balcan, Ellen Vitercik, Colin White:
Learning Combinatorial Functions from Pairwise Comparisons. CoRR abs/1605.09227 (2016) - [i40]Maria-Florina Balcan, Tuomas Sandholm, Ellen Vitercik:
Sample Complexity of Automated Mechanism Design. CoRR abs/1606.04145 (2016) - [i39]Maria-Florina Balcan, Vaishnavh Nagarajan, Ellen Vitercik, Colin White:
Learning the best algorithm for max-cut, clustering, and other partitioning problems. CoRR abs/1611.04535 (2016) - [i38]Maria-Florina Balcan, Hongyang Zhang:
Noise-Tolerant Life-Long Matrix Completion via Adaptive Sampling. CoRR abs/1612.00100 (2016) - [i37]Nan Du, Yingyu Liang, Maria-Florina Balcan, Manuel Gomez-Rodriguez, Hongyuan Zha, Le Song:
Scalable Influence Maximization for Multiple Products in Continuous-Time Diffusion Networks. CoRR abs/1612.02712 (2016) - [i36]Maria-Florina Balcan, Shai Ben-David, Ruth Urner, Ulrike von Luxburg:
Foundations of Unsupervised Learning (Dagstuhl Seminar 16382). Dagstuhl Reports 6(9): 94-109 (2016) - 2015
- [i35]Pranjal Awasthi, Maria-Florina Balcan, Nika Haghtalab, Ruth Urner:
Efficient Learning of Linear Separators under Bounded Noise. CoRR abs/1503.03594 (2015) - [i34]Maria-Florina Balcan, Yingyu Liang, Le Song, David P. Woodruff, Bo Xie:
Distributed Kernel Principal Component Analysis. CoRR abs/1503.06858 (2015) - [i33]Maria-Florina Balcan, Ariel D. Procaccia, Yair Zick:
Learning Cooperative Games. CoRR abs/1505.00039 (2015) - [i32]Maria-Florina Balcan, Nika Haghtalab, Colin White:
Symmetric and Asymmetric $k$-center Clustering under Stability. CoRR abs/1505.03924 (2015) - [i31]Shang-Tse Chen, Maria-Florina Balcan, Duen Horng Chau:
Communication Efficient Distributed Agnostic Boosting. CoRR abs/1506.06318 (2015) - [i30]Maria-Florina Balcan, Travis Dick, Yishay Mansour:
On the geometry of output-code multi-class learning. CoRR abs/1511.03225 (2015) - [i29]Travis Dick, Mu Li, Venkata Krishna Pillutla, Colin White, Maria-Florina Balcan, Alexander J. Smola:
Data Driven Resource Allocation for Distributed Learning. CoRR abs/1512.04848 (2015) - 2014
- [i28]Maria-Florina Balcan, Yingyu Liang, Pramod Gupta:
Robust Hierarchical Clustering. CoRR abs/1401.0247 (2014) - [i27]Aurélien Bellet, Yingyu Liang, Alireza Bagheri Garakani, Maria-Florina Balcan, Fei Sha:
Distributed Frank-Wolfe Algorithm: A Unified Framework for Communication-Efficient Sparse Learning. CoRR abs/1404.2644 (2014) - [i26]Maria-Florina Balcan, Christopher Berlind, Avrim Blum, Emma Cohen, Kaushik Patnaik, Le Song:
Active Learning and Best-Response Dynamics. CoRR abs/1406.6633 (2014) - [i25]Bo Dai, Bo Xie, Niao He, Yingyu Liang, Anant Raj, Maria-Florina Balcan, Le Song:
Scalable Kernel Methods via Doubly Stochastic Gradients. CoRR abs/1407.5599 (2014) - [i24]Maria-Florina Balcan, Amit Daniely, Ruta Mehta, Ruth Urner, Vijay V. Vazirani:
Learning Economic Parameters from Revealed Preferences. CoRR abs/1407.7937 (2014) - [i23]Konstantin Voevodski, Maria-Florina Balcan, Heiko Röglin, Shang-Hua Teng, Yu Xia:
Efficient Clustering with Limited Distance Information. CoRR abs/1408.2045 (2014) - [i22]Maria-Florina Balcan, Vandana Kanchanapally, Yingyu Liang, David P. Woodruff:
Improved Distributed Principal Component Analysis. CoRR abs/1408.5823 (2014) - [i21]Maria-Florina Balcan, Avrim Blum, Santosh S. Vempala:
Efficient Representations for Life-Long Learning and Autoencoding. CoRR abs/1411.1490 (2014) - [i20]Maria-Florina Balcan, Bodo Manthey, Heiko Röglin, Tim Roughgarden:
Analysis of Algorithms Beyond the Worst Case (Dagstuhl Seminar 14372). Dagstuhl Reports 4(9): 30-49 (2014) - 2013
- [i19]Maria-Florina Balcan, Steven Ehrlich, Yingyu Liang:
Distributed Clustering on Graphs. CoRR abs/1306.0604 (2013) - [i18]Maria-Florina Balcan, Vitaly Feldman:
Statistical Active Learning Algorithms. CoRR abs/1307.3102 (2013) - [i17]Pranjal Awasthi, Maria-Florina Balcan, Philip M. Long:
The Power of Localization for Efficiently Learning Linear Separators with Malicious Noise. CoRR abs/1307.8371 (2013) - [i16]Nan Du, Yingyu Liang, Maria-Florina Balcan, Le Song:
Continuous-Time Influence Maximization for Multiple Items. CoRR abs/1312.2164 (2013) - [i15]Pranjal Awasthi, Maria-Florina Balcan, Konstantin Voevodski:
Local algorithms for interactive clustering. CoRR abs/1312.6724 (2013) - 2012
- [i14]Maria-Florina Balcan, Christian Borgs, Mark Braverman, Jennifer T. Chayes, Shang-Hua Teng:
I Like Her more than You: Self-determined Communities. CoRR abs/1201.4899 (2012) - [i13]Maria-Florina Balcan, Avrim Blum, Shai Fine, Yishay Mansour:
Distributed Learning, Communication Complexity and Privacy. CoRR abs/1204.3514 (2012) - [i12]Maria-Florina Balcan, Philip M. Long:
Active and passive learning of linear separators under log-concave distributions. CoRR abs/1211.1082 (2012) - 2011
- [i11]Konstantin Voevodski, Maria-Florina Balcan, Heiko Röglin, Shang-Hua Teng, Yu Xia:
Clustering Protein Sequences Given the Approximation Stability of the Min-Sum Objective Function. CoRR abs/1101.3620 (2011) - [i10]Maria-Florina Balcan, Florin Constantin, Satoru Iwata, Lei Wang:
Learning Valuation Functions. CoRR abs/1108.5669 (2011) - [i9]Maria-Florina Balcan, Sara Krehbiel, Georgios Piliouras, Jinwoo Shin:
Near Optimality in Covering and Packing Games by Exposing Global Information. CoRR abs/1109.3606 (2011) - [i8]Maria-Florina Balcan, Eric Blais, Avrim Blum, Liu Yang:
Active Testing. CoRR abs/1111.0897 (2011) - [i7]Maria-Florina Balcan, Steve Hanneke:
Robust Interactive Learning. CoRR abs/1111.1422 (2011) - [i6]Maria-Florina Balcan, Yingyu Liang:
Clustering under Perturbation Resilience. CoRR abs/1112.0826 (2011) - 2010
- [i5]Maria-Florina Balcan, Mark Braverman:
Approximate Nash Equilibria under Stability Conditions. CoRR abs/1008.1827 (2010) - [i4]Maria-Florina Balcan, Nicholas J. A. Harvey:
Learning Submodular Functions. CoRR abs/1008.2159 (2010) - [i3]Maria-Florina Balcan, Florin Constantin:
Sequential item pricing for unlimited supply. CoRR abs/1009.4606 (2010) - [i2]Konstantin Voevodski, Maria-Florina Balcan, Heiko Röglin, Shang-Hua Teng, Yu Xia:
Efficient Clustering with Limited Distance Information. CoRR abs/1009.5168 (2010) - 2007
- [i1]Maria-Florina Balcan:
Item Pricing for Revenue Maximization in Combinatorial Auctions. Computational Social Systems and the Internet 2007
Coauthor Index
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