Maria-Florina F Balcan

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

Achievements

+9 more ↓

🏃 Academic Marathon (10) 🧭 Keyword Pioneer 🐣 Hot Topic Early Bird 🌉 Interdisciplinary Bridge 🐝 Cross-Pollinator (7)

🧭 Keyword Pioneer 🏃 Academic Marathon (10) 🏠 Conference Loyalist (25) 🏆 Keyword Champion (2) 🔬 Deep Specialist (14) 🗃️ Keyword Collector (128) 💎 Century Club (25) 📈 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