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Found 6 papers, 0 papers with code
LiD-FL: Towards List-Decodable Federated Learning
Federated learning is often used in environments with many unverified participants.
Error-Tolerant E-Discovery Protocols
Our goal is to find a protocol that verifies that the responding party sends almost all responsive documents while minimizing the disclosure of non-responsive documents.
Explainable k-means. Don't be greedy, plant bigger trees!
Our randomized bi-criteria algorithm constructs a threshold decision tree that partitions the data set into $(1+\delta)k$ clusters (where $\delta\in (0, 1)$ is a parameter of the algorithm).
Near-optimal Algorithms for Explainable k-Medians and k-Means
This is an improvement over the previous guarantees of $O(k)$ and $O(k^2)$ by Dasgupta et al (2020).
Improved Guarantees for k-means++ and k-means++ Parallel
In this paper, we study k-means++ and k-means++ parallel, the two most popular algorithms for the classic k-means clustering problem.
Stochastic Linear Optimization with Adversarial Corruption
We extend the model of stochastic bandits with adversarial corruption (Lykouriset al., 2018) to the stochastic linear optimization problem (Dani et al., 2008).
