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Found 6 papers, 0 papers with code
Online Adaptive Mahalanobis Distance Estimation
Mahalanobis metrics are widely used in machine learning in conjunction with methods like $k$-nearest neighbors, $k$-means clustering, and $k$-medians clustering.
Adaptive and Dynamic Multi-Resolution Hashing for Pairwise Summations
In this paper, we propose Adam-Hash: an adaptive and dynamic multi-resolution hashing data-structure for fast pairwise summation estimation.
Dynamic Tensor Product Regression
In this work, we initiate the study of \emph{Dynamic Tensor Product Regression}.
Online MAP Inference and Learning for Nonsymmetric Determinantal Point Processes
In this paper, we introduce the online and streaming MAP inference and learning problems for Non-symmetric Determinantal Point Processes (NDPPs) where data points arrive in an arbitrary order and the algorithms are constrained to use a single-pass over the data as well as sub-linear memory.
Beyond Perturbation Stability: LP Recovery Guarantees for MAP Inference on Noisy Stable Instances
Several works have shown that perturbation stable instances of the MAP inference problem in Potts models can be solved exactly using a natural linear programming (LP) relaxation.
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.
