randomized algorithm

A One-Size-Fits-All Approach to Improving Randomness in Paper Assignment NeurIPS 2023 BanditPAM++: Faster k-medoids Clustering NeurIPS 2023 Dimensionality Reduction for General KDE Mode Finding ICML 2023 Explainable and Efficient Randomized Voting Rules NeurIPS 2023 Improved Learning-Augmented Algorithms for the Multi-Option Ski Rental Problem via Best-Possible Competitive Analysis ICML 2023 Matrix Compression via Randomized Low Rank and Low Precision Factorization NeurIPS 2023 Mean Payoff Optimization for Systems of Periodic Service and Maintenance IJCAI 2023 Randomized Gaussian Process Upper Confidence Bound with Tighter Bayesian Regret Bounds ICML 2023 RSC: Accelerate Graph Neural Networks Training via Randomized Sparse Computations ICML 2023 Simple, Scalable and Effective Clustering via One-Dimensional Projections NeurIPS 2023 Tensor-Based Sketching Method for the Low-Rank Approximation of Data Streams. ICLR 2023 Toward Better PAC-Bayes Bounds for Uniformly Stable Algorithms NeurIPS 2023 Tricking the Hashing Trick: A Tight Lower Bound on the Robustness of CountSketch to Adaptive Inputs AAAI 2023 A competitive analysis of online failure-aware assignment UAI 2022 Inconsistent Planning: When in Doubt, Toss a Coin! AAAI 2022 Insight into Voting Problem Complexity Using Randomized Classes IJCAI 2022 Learning Augmented Binary Search Trees ICML 2022 On a Connection Between Fast and Sparse Oblivious Subspace Embeddings AISTATS 2022 On the Robustness of CountSketch to Adaptive Inputs ICML 2022 Scaling Structured Inference with Randomization ICML 2022 Sublinear time algorithms for greedy selection in high dimensions UAI 2022 Trustworthy Monte Carlo NeurIPS 2022 Asymptotically Exact and Fast Gaussian Copula Models for Imputation of Mixed Data Types ACML 2021 Communication-Efficient Distributed Covariance Sketch, with Application to Distributed PCA JMLR 2021 Competitive Analysis for Two-Level Ski-Rental Problem AAAI 2021