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Found 7 papers, 4 papers with code
DriftSurf: A Risk-competitive Learning Algorithm under Concept Drift
The advantage of our approach is that we can use aggressive drift detection in the stable state to achieve a high detection rate, but mitigate the false positive rate of standalone drift detection via a reactive state that reacts quickly to true drifts while eliminating most false positives.
Random Sampling for Group-By Queries
We consider random sampling for answering the ubiquitous class of group-by queries, which first group data according to one or more attributes, and then aggregate within each group after filtering through a predicate.
Databases Data Structures and Algorithms
FLEET: Butterfly Estimation from a Bipartite Graph Stream
We consider space-efficient single-pass estimation of the number of butterflies, a fundamental bipartite graph motif, from a massive bipartite graph stream where each edge represents a connection between entities in two different partitions.
Data Structures and Algorithms
Variance-Reduced Stochastic Gradient Descent on Streaming Data
We present an algorithm STRSAGA for efficiently maintaining a machine learning model over data points that arrive over time, quickly updating the model as new training data is observed.
Enumerating Top-k Quasi-Cliques
Quasi-cliques are dense incomplete subgraphs of a graph that generalize the notion of cliques.
Data Structures and Algorithms
Butterfly Counting in Bipartite Networks
We consider the problem of counting motifs in bipartite affiliation networks, such as author-paper, user-product, and actor-movie relations.
Discrete Mathematics
Learning Graphical Models from a Distributed Stream
We study Bayesian networks, the workhorse of graphical models, and present a communication-efficient method for continuously learning and maintaining a Bayesian network model over data that is arriving as a distributed stream partitioned across multiple processors.
