Search Results for author:
Found 10 papers, 2 papers with code
Fully-Dynamic Approximate Decision Trees With Worst-Case Update Time Guarantees
We give the first algorithm that maintains an approximate decision tree over an arbitrary sequence of insertions and deletions of labeled examples, with strong guarantees on the worst-case running time per update request.
Fully-Dynamic Decision Trees
We develop the first fully dynamic algorithm that maintains a decision tree over an arbitrary sequence of insertions and deletions of labeled examples.
Active Learning of Classifiers with Label and Seed Queries
In this work we show that, by carefully combining the two types of queries, a binary classifier can be learned in time $\operatorname{poly}(n+m)$ using only $O(m^2 \log n)$ label queries and $O\big(m \log \frac{m}{\gamma}\big)$ seed queries; the result extends to $k$-class classifiers at the price of a $k! k^2$ multiplicative overhead.
On Margin-Based Cluster Recovery with Oracle Queries
We study an active cluster recovery problem where, given a set of $n$ points and an oracle answering queries like "are these two points in the same cluster?
Exact and Approximate Pattern Counting in Degenerate Graphs: New Algorithms, Hardness Results, and Complexity Dichotomies
We study the problems of counting the homomorphisms, counting the copies, and counting the induced copies of a $k$-vertex graph $H$ in a $d$-degenerate $n$-vertex graph $G$.
Computational Complexity Data Structures and Algorithms
Exact Recovery of Clusters in Finite Metric Spaces Using Oracle Queries
Previous results show that clusters in Euclidean spaces that are convex and separated with a margin can be reconstructed exactly using only $O(\log n)$ same-cluster queries, where $n$ is the number of input points.
Efficient and near-optimal algorithms for sampling small connected subgraphs
We study the following problem: given an integer $k \ge 3$ and a simple graph $G$, sample a connected induced $k$-node subgraph of $G$ uniformly at random.
Graph Mining
Data Structures and Algorithms
Discrete Mathematics
Social and Information Networks
Exact Recovery of Mangled Clusters with Same-Cluster Queries
Given a finite set of input points, and an oracle revealing whether any two points lie in the same cluster, our goal is to recover all clusters exactly using as few queries as possible.
Motivo: fast motif counting via succinct color coding and adaptive sampling
To give an idea of the improvements, in $40$ minutes Motivo counts $7$-nodes motifs on a graph with $65$M nodes and $1. 8$B edges; this is $30$ and $500$ times larger than the state of the art, respectively in terms of nodes and edges.
Correlation Clustering with Adaptive Similarity Queries
In this work we investigate correlation clustering as an active learning problem: each similarity score can be learned by making a query, and the goal is to minimise both the disagreements and the total number of queries.
