
Online Page Migration with ML Advice
We consider online algorithms for the page migration problem that use pr...
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Estimating Entropy of Distributions in Constant Space
We consider the task of estimating the entropy of kary distributions fr...
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LearningBased LowRank Approximations
We introduce a "learningbased" algorithm for the lowrank decomposition...
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Scalable Nearest Neighbor Search for Optimal Transport
The Optimal Transport (a.k.a. Wasserstein) distance is an increasingly p...
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(Learned) Frequency Estimation Algorithms under Zipfian Distribution
The frequencies of the elements in a data stream are an important statis...
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Composable Coresets for Determinant Maximization: A Simple NearOptimal Algorithm
"Composable coresets" are an efficient framework for solving optimizati...
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SampleOptimal LowRank Approximation of Distance Matrices
A distance matrix A ∈ R^n × m represents all pairwise distances, A_ij=d(...
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Set Cover in Sublinear Time
We study the classic set cover problem from the perspective of sublinea...
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Scalable Fair Clustering
We study the fair variant of the classic kmedian problem introduced by ...
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Learning SublinearTime Indexing for Nearest Neighbor Search
Most of the efficient sublineartime indexing algorithms for the highdi...
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Learning Space Partitions for Nearest Neighbor Search
Space partitions of R^d underlie a vast and important class of fast near...
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Composable Coresets for Determinant Maximization Problems via Spectral Spanners
We study a spectral generalization of classical combinatorial graph span...
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Approximate Nearest Neighbors in Limited Space
We consider the (1+ϵ)approximate nearest neighbor search problem: given...
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Approximate Nearest Neighbor Search in High Dimensions
The nearest neighbor problem is defined as follows: Given a set P of n p...
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Practical DataDependent Metric Compression with Provable Guarantees
We introduce a new distancepreserving compact representation of multid...
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On the FineGrained Complexity of Empirical Risk Minimization: Kernel Methods and Neural Networks
Empirical risk minimization (ERM) is ubiquitous in machine learning and ...
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