
Vertex Ordering Problems in Directed Graph Streams
We consider directed graph algorithms in a streaming setting, focusing o...
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Maximum Coverage in the Data Stream Model: Parameterized and Generalized
We present algorithms for the MaxCover and MaxUniqueCover problems in...
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Intervention Efficient Algorithms for Approximate Learning of Causal Graphs
We study the problem of learning the causal relationships between a set ...
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Diverse Data Selection under Fairness Constraints
Diversity is an important principle in data selection and summarization,...
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Efficient Intervention Design for Causal Discovery with Latents
We consider recovering a causal graph in presence of latent variables, w...
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Compact Representation of Uncertainty in Hierarchical Clustering
Hierarchical clustering is a fundamental task often used to discover mea...
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Algebraic and Analytic Approaches for Parameter Learning in Mixture Models
We present two different approaches for parameter learning in several mi...
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Sample Complexity of Learning Mixtures of Sparse Linear Regressions
In the problem of learning mixtures of linear regressions, the goal is t...
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Trace Reconstruction: Generalized and Parameterized
In the beautifully simpletostate problem of trace reconstruction, the ...
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Mesh: Compacting Memory Management for C/C++ Applications
Programs written in C/C++ can suffer from serious memory fragmentation, ...
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Correlation Clustering in Data Streams
Clustering is a fundamental tool for analyzing large data sets. A rich b...
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Approximate Principal Direction Trees
We introduce a new spatial data structure for high dimensional data call...
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Andrew McGregor
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