efficient algorithms
Algorithms designed to achieve desired outcomes while minimizing computational resources (time and memory), crucial for handling large-scale AI problems effectively.
- A Generalized Binary Tree Mechanism for Private Approximation of All-Pair Shortest Distances
- A Novel General Framework for Sharp Lower Bounds in Succinct Stochastic Bandits
- Distribution Learning Meets Graph Structure Sampling
- Dynamic Diameter in High-Dimensions against Adaptive Adversary and Beyond
- Fast Computation and Optimization for Opinion-Based Quantities of Friedkin-Johnsen Model
- Faster Algorithms for Structured John Ellipsoid Computation
- Information-Computation Tradeoffs for Noiseless Linear Regression with Oblivious Contamination
- Localized Data Shapley: Accelerating Valuation for Nearest Neighbor Algorithms
- Nearly-Linear Time Private Hypothesis Selection with the Optimal Approximation Factor
- Quantum Speedups for Minimax Optimization and Beyond
- The Complexity of Correlated Equilibria in Generalized Games
- The Power of Iterative Filtering for Supervised Learning with (Heavy) Contamination
- Variational Inference with Mixtures of Isotropic Gaussians