← Authors

Maria-Florina F Balcan

25 papers · 2013–2023 · 1 conference · across top CS/AI conferences

Achievements

🐝 Cross-Pollinator (7) πŸ—ΊοΈ Taxonomy Completionist (56) 🌈 Renaissance Researcher (7) 🐣 Hot Topic Early Bird πŸŒ‰ Interdisciplinary Bridge 🧭 Keyword Pioneer πŸƒ Academic Marathon (10) 🏠 Conference Loyalist (25) πŸ† Keyword Champion (2) πŸ”¬ Deep Specialist (14) πŸ—ƒοΈ Keyword Collector (128) πŸ’Ž Century Club (25) πŸ“ˆ Trend Setter ⚑ Prolific Year (5)

Conferences

NIPS (25)

Top co-authors

Dravyansh Sharma (5) Tuomas Sandholm (5) Ameet Talwalkar (4) Siddharth Prasad (4) Yingyu Liang (4) Mikhail Khodak (3) Le Song (3) Misha Khodak (3) Ellen Vitercik (3) Hongyang Zhang (2)

Research topics

Differential Privacy (1) Probability (1)

Keywords

sample complexity (6) online learning (6) learning theory (5) regret bound (5) active learning (3) k-means clustering (3) federated learning (2) generalization guarantee (2) noise-tolerant learning (2) hyperparameter tuning (2) mechanism design (2) hyperparameter optimization (2) integer programming (2) cutting plane (2) revenue optimization (2) game theory (2) statistical learning (2) transfer learning (1) non-convex optimization (1) algorithmic fairness (1)

Papers

Meta-Learning Adversarial Bandit Algorithms NIPS 2023
New Bounds for Hyperparameter Tuning of Regression Problems Across Instances NIPS 2023
Learning with Explanation Constraints NIPS 2023
Reliable learning in challenging environments NIPS 2023
Bicriteria Multidimensional Mechanism Design with Side Information NIPS 2023
Learning Predictions for Algorithms with Predictions NIPS 2022
Structural Analysis of Branch-and-Cut and the Learnability of Gomory Mixed Integer Cuts NIPS 2022
Provably tuning the ElasticNet across instances NIPS 2022
Maximizing Revenue under Market Shrinkage and Market Uncertainty NIPS 2022
Sample Complexity of Tree Search Configuration: Cutting Planes and Beyond NIPS 2021
Data driven semi-supervised learning NIPS 2021
Learning-to-learn non-convex piecewise-Lipschitz functions NIPS 2021
Federated Hyperparameter Tuning: Challenges, Baselines, and Connections to Weight-Sharing NIPS 2021
Adaptive Gradient-Based Meta-Learning Methods NIPS 2019
Envy-Free Classification NIPS 2019
Data-Driven Clustering via Parameterized Lloyd's Families NIPS 2018
Sample and Computationally Efficient Learning Algorithms under S-Concave Distributions NIPS 2017
Sample Complexity of Automated Mechanism Design NIPS 2016
Noise-Tolerant Life-Long Matrix Completion via Adaptive Sampling NIPS 2016
Learning Time-Varying Coverage Functions NIPS 2014
Scalable Kernel Methods via Doubly Stochastic Gradients NIPS 2014
Active Learning and Best-Response Dynamics NIPS 2014
Improved Distributed Principal Component Analysis NIPS 2014
Statistical Active Learning Algorithms NIPS 2013
Distributed $k$-means and $k$-median Clustering on General Topologies NIPS 2013