Maria-Florina Balcan

According to our database1, Maria-Florina Balcan authored at least 178 papers between 2001 and 2019.

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2019
How much data is sufficient to learn high-performing algorithms?
CoRR, 2019

Online optimization of piecewise Lipschitz functions in changing environments.
CoRR, 2019

Learning to Link.
CoRR, 2019

Adaptive Gradient-Based Meta-Learning Methods.
CoRR, 2019

Learning to Optimize Computational Resources: Frugal Training with Generalization Guarantees.
CoRR, 2019

Semi-bandit Optimization in the Dispersed Setting.
CoRR, 2019

Provable Guarantees for Gradient-Based Meta-Learning.
CoRR, 2019

Estimating Approximate Incentive Compatibility.
CoRR, 2019

Testing Matrix Rank, Optimally.
Proceedings of the Thirtieth Annual ACM-SIAM Symposium on Discrete Algorithms, 2019

Provable Guarantees for Gradient-Based Meta-Learning.
Proceedings of the 36th International Conference on Machine Learning, 2019

Robust Communication-Optimal Distributed Clustering Algorithms.
Proceedings of the 46th International Colloquium on Automata, Languages, and Programming, 2019

Estimating Approximate Incentive Compatibility.
Proceedings of the 2019 ACM Conference on Economics and Computation, 2019

2018
Submodular Functions: Learnability, Structure, and Optimization.
SIAM J. Comput., 2018

Testing Matrix Rank, Optimally.
CoRR, 2018

Envy-Free Classification.
CoRR, 2018

Data-Driven Clustering via Parameterized Lloyd's Families.
CoRR, 2018

Learning to Branch.
CoRR, 2018

A General Theory of Sample Complexity for Multi-Item Profit Maximization.
Proceedings of the 2018 ACM Conference on Economics and Computation, 2018

Data-Driven Clustering via Parameterized Lloyd's Families.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Matrix Completion and Related Problems via Strong Duality.
Proceedings of the 9th Innovations in Theoretical Computer Science Conference, 2018

Learning to Branch.
Proceedings of the 35th International Conference on Machine Learning, 2018

Dispersion for Data-Driven Algorithm Design, Online Learning, and Private Optimization.
Proceedings of the 59th IEEE Annual Symposium on Foundations of Computer Science, 2018

Diversified Strategies for Mitigating Adversarial Attacks in Multiagent Systems.
Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems, 2018

2017
Nash Equilibria in Perturbation-Stable Games.
Theory of Computing, 2017

Scalable Influence Maximization for Multiple Products in Continuous-Time Diffusion Networks.
J. Mach. Learn. Res., 2017

Local algorithms for interactive clustering.
J. Mach. Learn. Res., 2017

The Power of Localization for Efficiently Learning Linear Separators with Noise.
J. ACM, 2017

Private and Online Optimization of Piecewise Lipschitz Functions.
CoRR, 2017

S-Concave Distributions: Towards Broader Distributions for Noise-Tolerant and Sample-Efficient Learning Algorithms.
CoRR, 2017

Clustering under Local Stability: Bridging the Gap between Worst-Case and Beyond Worst-Case Analysis.
CoRR, 2017

Sample Complexity of Multi-Item Profit Maximization.
CoRR, 2017

Optimal Sample Complexity for Matrix Completion and Related Problems via 𝓁s2-Regularization.
CoRR, 2017

Lifelong Learning in Costly Feature Spaces.
CoRR, 2017

General and Robust Communication-Efficient Algorithms for Distributed Clustering.
CoRR, 2017

Sample and Computationally Efficient Learning Algorithms under S-Concave Distributions.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Risk Bounds for Transferring Representations With and Without Fine-Tuning.
Proceedings of the 34th International Conference on Machine Learning, 2017

Differentially Private Clustering in High-Dimensional Euclidean Spaces.
Proceedings of the 34th International Conference on Machine Learning, 2017

Performance guarantees for transferring representations.
Proceedings of the 5th International Conference on Learning Representations, 2017

Learning-Theoretic Foundations of Algorithm Configuration for Combinatorial Partitioning Problems.
Proceedings of the 30th Conference on Learning Theory, 2017

Lifelong Learning in Costly Feature Spaces.
Proceedings of the International Conference on Algorithmic Learning Theory, 2017

Data Driven Resource Allocation for Distributed Learning.
Proceedings of the 20th International Conference on Artificial Intelligence and Statistics, 2017

Data Driven Resource Allocation for Distributed Learning.
Proceedings of the Workshops of the The Thirty-First AAAI Conference on Artificial Intelligence, 2017

Label Efficient Learning by Exploiting Multi-Class Output Codes.
Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence, 2017

2016
Active Learning - Modern Learning Theory.
Encyclopedia of Algorithms, 2016

Clustering under Perturbation Resilience.
SIAM J. Comput., 2016

Foundations of Unsupervised Learning (Dagstuhl Seminar 16382).
Dagstuhl Reports, 2016

Scalable Influence Maximization for Multiple Products in Continuous-Time Diffusion Networks.
CoRR, 2016

Active Learning Algorithms for Graphical Model Selection.
CoRR, 2016

Noise-Tolerant Life-Long Matrix Completion via Adaptive Sampling.
CoRR, 2016

Learning Combinatorial Functions from Pairwise Comparisons.
CoRR, 2016

Sample Complexity of Automated Mechanism Design.
CoRR, 2016

Learning the best algorithm for max-cut, clustering, and other partitioning problems.
CoRR, 2016

An Improved Gap-Dependency Analysis of the Noisy Power Method.
CoRR, 2016

Noise-Tolerant Life-Long Matrix Completion via Adaptive Sampling.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Sample Complexity of Automated Mechanism Design.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Communication Efficient Distributed Kernel Principal Component Analysis.
Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2016

k-Center Clustering Under Perturbation Resilience.
Proceedings of the 43rd International Colloquium on Automata, Languages, and Programming, 2016

Learning Combinatorial Functions from Pairwise Comparisons.
Proceedings of the 29th Conference on Learning Theory, 2016

An Improved Gap-Dependency Analysis of the Noisy Power Method.
Proceedings of the 29th Conference on Learning Theory, 2016

Learning and 1-bit Compressed Sensing under Asymmetric Noise.
Proceedings of the 29th Conference on Learning Theory, 2016

Active Learning Algorithms for Graphical Model Selection.
Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, 2016

Communication Efficient Distributed Agnostic Boosting.
Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, 2016

2015
Data Driven Resource Allocation for Distributed Learning.
CoRR, 2015

Communication Efficient Distributed Agnostic Boosting.
CoRR, 2015

Learning Cooperative Games.
CoRR, 2015

Distributed Kernel Principal Component Analysis.
CoRR, 2015

Symmetric and Asymmetric $k$-center Clustering under Stability.
CoRR, 2015

On the geometry of output-code multi-class learning.
CoRR, 2015

Efficient Learning of Linear Separators under Bounded Noise.
CoRR, 2015

Statistical Active Learning Algorithms for Noise Tolerance and Differential Privacy.
Algorithmica, 2015

Commitment Without Regrets: Online Learning in Stackelberg Security Games.
Proceedings of the Sixteenth ACM Conference on Economics and Computation, 2015

A Distributed Frank-Wolfe Algorithm for Communication-Efficient Sparse Learning.
Proceedings of the 2015 SIAM International Conference on Data Mining, Vancouver, BC, Canada, April 30, 2015

Learning Cooperative Games.
Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence, 2015

Efficient Representations for Lifelong Learning and Autoencoding.
Proceedings of The 28th Conference on Learning Theory, 2015

Efficient Learning of Linear Separators under Bounded Noise.
Proceedings of The 28th Conference on Learning Theory, 2015

Learning Submodular Functions with Applications to Multi-Agent Systems.
Proceedings of the 2015 International Conference on Autonomous Agents and Multiagent Systems, 2015

2014
Near-Optimality in Covering Games by Exposing Global Information.
ACM Trans. Economics and Comput., 2014

Robust hierarchical clustering.
J. Mach. Learn. Res., 2014

Analysis of Algorithms Beyond the Worst Case (Dagstuhl Seminar 14372).
Dagstuhl Reports, 2014

Efficient Clustering with Limited Distance Information.
CoRR, 2014

Scalable Kernel Methods via Doubly Stochastic Gradients.
CoRR, 2014

Distributed Frank-Wolfe Algorithm: A Unified Framework for Communication-Efficient Sparse Learning.
CoRR, 2014

Robust Hierarchical Clustering.
CoRR, 2014

Improved Distributed Principal Component Analysis.
CoRR, 2014

Learning Economic Parameters from Revealed Preferences.
CoRR, 2014

Efficient Representations for Life-Long Learning and Autoencoding.
CoRR, 2014

Active Learning and Best-Response Dynamics.
CoRR, 2014

Learning Economic Parameters from Revealed Preferences.
Proceedings of the Web and Internet Economics - 10th International Conference, 2014

The power of localization for efficiently learning linear separators with noise.
Proceedings of the Symposium on Theory of Computing, 2014

Improved Distributed Principal Component Analysis.
Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

Learning Time-Varying Coverage Functions.
Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

Scalable Kernel Methods via Doubly Stochastic Gradients.
Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

Active Learning and Best-Response Dynamics.
Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

Influence Function Learning in Information Diffusion Networks.
Proceedings of the 31th International Conference on Machine Learning, 2014

Local algorithms for interactive clustering.
Proceedings of the 31th International Conference on Machine Learning, 2014

A New Perspective on Learning Linear Separators with Large \(L_qL_p\) Margins.
Proceedings of the Seventeenth International Conference on Artificial Intelligence and Statistics, 2014

2013
The Price of Uncertainty.
ACM Trans. Economics and Comput., 2013

Special Section on the Fiftieth Annual IEEE Symposium on Foundations of Computer Science (FOCS 2009).
SIAM J. Comput., 2013

Circumventing the Price of Anarchy: Leading Dynamics to Good Behavior.
SIAM J. Comput., 2013

Clustering under approximation stability.
J. ACM, 2013

Continuous-Time Influence Maximization for Multiple Items.
CoRR, 2013

Statistical Active Learning Algorithms.
CoRR, 2013

Distributed Clustering on Graphs.
CoRR, 2013

Local algorithms for interactive clustering.
CoRR, 2013

The Power of Localization for Efficiently Learning Linear Separators with Malicious Noise.
CoRR, 2013

Finding Endogenously Formed Communities.
Proceedings of the Twenty-Fourth Annual ACM-SIAM Symposium on Discrete Algorithms, 2013

Modeling and Detecting Community Hierarchies.
Proceedings of the Similarity-Based Pattern Recognition - Second International Workshop, 2013

Statistical Active Learning Algorithms.
Proceedings of the Advances in Neural Information Processing Systems 26: 27th Annual Conference on Neural Information Processing Systems 2013. Proceedings of a meeting held December 5-8, 2013

Distributed k-means and k-median clustering on general communication topologies.
Proceedings of the Advances in Neural Information Processing Systems 26: 27th Annual Conference on Neural Information Processing Systems 2013. Proceedings of a meeting held December 5-8, 2013

Exploiting Ontology Structures and Unlabeled Data for Learning.
Proceedings of the 30th International Conference on Machine Learning, 2013

Efficient Semi-supervised and Active Learning of Disjunctions.
Proceedings of the 30th International Conference on Machine Learning, 2013

Active and passive learning of linear separators under log-concave distributions.
Proceedings of the COLT 2013, 2013

2012
Active Clustering of Biological Sequences.
J. Mach. Learn. Res., 2012

Robust Interactive Learning.
Proceedings of the COLT 2012, 2012

Learning Valuation Functions.
Proceedings of the COLT 2012, 2012

Distributed Learning, Communication Complexity and Privacy.
Proceedings of the COLT 2012, 2012

Active and passive learning of linear separators under log-concave distributions
CoRR, 2012

Distributed Learning, Communication Complexity and Privacy
CoRR, 2012

I Like Her more than You: Self-determined Communities
CoRR, 2012

Clustering under Perturbation Resilience.
Proceedings of the Automata, Languages, and Programming - 39th International Colloquium, 2012

Active Property Testing.
Proceedings of the 53rd Annual IEEE Symposium on Foundations of Computer Science, 2012

Minimally invasive mechanism design: Distributed covering with carefully chosen advice.
Proceedings of the 51th IEEE Conference on Decision and Control, 2012

2011
Leading dynamics to good behavior.
SIGecom Exchanges, 2011

Clustering under Perturbation Resilience
CoRR, 2011

Robust Interactive Learning
CoRR, 2011

Active Testing
CoRR, 2011

Near Optimality in Covering and Packing Games by Exposing Global Information
CoRR, 2011

Learning Valuation Functions
CoRR, 2011

Clustering Protein Sequences Given the Approximation Stability of the Min-Sum Objective Function
CoRR, 2011

The Snowball Effect of Uncertainty in Potential Games.
Proceedings of the Internet and Network Economics - 7th International Workshop, 2011

Learning submodular functions.
Proceedings of the 43rd ACM Symposium on Theory of Computing, 2011

Min-sum Clustering of Protein Sequences with Limited Distance Information.
Proceedings of the Similarity-Based Pattern Recognition - First International Workshop, 2011

Game couplings: Learning dynamics and applications.
Proceedings of the 50th IEEE Conference on Decision and Control and European Control Conference, 2011

Combining Self Training and Active Learning for Video Segmentation.
Proceedings of the British Machine Vision Conference, 2011

2010
The true sample complexity of active learning.
Machine Learning, 2010

A discriminative model for semi-supervised learning.
J. ACM, 2010

Sequential item pricing for unlimited supply
CoRR, 2010

Learning Submodular Functions
CoRR, 2010

Approximate Nash Equilibria under Stability Conditions
CoRR, 2010

Sequential Item Pricing for Unlimited Supply.
Proceedings of the Internet and Network Economics - 6th International Workshop, 2010

Efficient Clustering with Limited Distance Information.
Proceedings of the UAI 2010, 2010

On the Equilibria of Alternating Move Games.
Proceedings of the Twenty-First Annual ACM-SIAM Symposium on Discrete Algorithms, 2010

On Nash-Equilibria of Approximation-Stable Games.
Proceedings of the Algorithmic Game Theory - Third International Symposium, 2010

Circumventing the Price of Anarchy: Leading Dynamics to Good Behavior.
Proceedings of the Innovations in Computer Science, 2010

Robust Hierarchical Clustering.
Proceedings of the COLT 2010, 2010

2009
Agnostic active learning.
J. Comput. Syst. Sci., 2009

Improved equilibria via public service advertising.
Proceedings of the Twentieth Annual ACM-SIAM Symposium on Discrete Algorithms, 2009

Approximate clustering without the approximation.
Proceedings of the Twentieth Annual ACM-SIAM Symposium on Discrete Algorithms, 2009

The price of uncertainty.
Proceedings of the Proceedings 10th ACM Conference on Electronic Commerce (EC-2009), 2009

Finding Low Error Clusterings.
Proceedings of the COLT 2009, 2009

Better Guarantees for Sparsest Cut Clustering.
Proceedings of the COLT 2009, 2009

Agnostic Clustering.
Proceedings of the Algorithmic Learning Theory, 20th International Conference, 2009

2008
Item pricing for revenue maximization.
SIGecom Exchanges, 2008

A theory of learning with similarity functions.
Machine Learning, 2008

Robust reductions from ranking to classification.
Machine Learning, 2008

Reducing mechanism design to algorithm design via machine learning.
J. Comput. Syst. Sci., 2008

A discriminative framework for clustering via similarity functions.
Proceedings of the 40th Annual ACM Symposium on Theory of Computing, 2008

Item pricing for revenue maximization.
Proceedings of the Proceedings 9th ACM Conference on Electronic Commerce (EC-2008), 2008

The True Sample Complexity of Active Learning.
Proceedings of the 21st Annual Conference on Learning Theory, 2008

Improved Guarantees for Learning via Similarity Functions.
Proceedings of the 21st Annual Conference on Learning Theory, 2008

Clustering with Interactive Feedback.
Proceedings of the Algorithmic Learning Theory, 19th International Conference, 2008

2007
Approximation Algorithms and Online Mechanisms for Item Pricing.
Theory of Computing, 2007

Mechanism design, machine learning, and pricing problems.
SIGecom Exchanges, 2007

A Theory of Loss-Leaders: Making Money by Pricing Below Cost.
Proceedings of the Internet and Network Economics, Third International Workshop, 2007

Item Pricing for Revenue Maximization in Combinatorial Auctions.
Proceedings of the Computational Social Systems and the Internet, 1.7. - 6.7.2007, 2007

Open Problems in Efficient Semi-supervised PAC Learning.
Proceedings of the Learning Theory, 20th Annual Conference on Learning Theory, 2007

Margin Based Active Learning.
Proceedings of the Learning Theory, 20th Annual Conference on Learning Theory, 2007

Robust Reductions from Ranking to Classification.
Proceedings of the Learning Theory, 20th Annual Conference on Learning Theory, 2007

2006
Kernels as features: On kernels, margins, and low-dimensional mappings.
Machine Learning, 2006

Approximation algorithms and online mechanisms for item pricing.
Proceedings of the Proceedings 7th ACM Conference on Electronic Commerce (EC-2006), 2006

Agnostic active learning.
Proceedings of the Machine Learning, 2006

On a theory of learning with similarity functions.
Proceedings of the Machine Learning, 2006

An Augmented PAC Model for Semi-Supervised Learning.
Proceedings of the Semi-Supervised Learning, 2006

2005
Mechanism Design via Machine Learning.
Proceedings of the 46th Annual IEEE Symposium on Foundations of Computer Science (FOCS 2005), 2005

A PAC-Style Model for Learning from Labeled and Unlabeled Data.
Proceedings of the Learning Theory, 18th Annual Conference on Learning Theory, 2005

2004
Co-Training and Expansion: Towards Bridging Theory and Practice.
Proceedings of the Advances in Neural Information Processing Systems 17 [Neural Information Processing Systems, 2004

On Kernels, Margins, and Low-Dimensional Mappings.
Proceedings of the Algorithmic Learning Theory, 15th International Conference, 2004

2001
Handwritten text localization in skewed documents.
Proceedings of the 2001 International Conference on Image Processing, 2001


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