32 citations · 63 across the 5 of their papers we have counts for
5 papers
From Trees to Continuous Embeddings and Back: Hyperbolic Hierarchical Clustering
Ines Chami, Albert Gu, Vaggos Chatziafratis +1
Similarity-based Hierarchical Clustering (HC) is a classical unsupervised machine learning algorithm that has traditionally been solved with heuristic algorithms like Average-Linka…
Bisect and Conquer: Hierarchical Clustering via Max-Uncut Bisection
Sara Ahmadian, Vaggos Chatziafratis, Alessandro Epasto +4
Hierarchical Clustering is an unsupervised data analysis method which has been widely used for decades. Despite its popularity, it had an underdeveloped analytical foundation and t…
Depth-Width Trade-offs for ReLU Networks via Sharkovsky's Theorem
Vaggos Chatziafratis, Sai Ganesh Nagarajan, Ioannis Panageas +1
Understanding the representational power of Deep Neural Networks (DNNs) and how their structural properties (e.g., depth, width, type of activation unit) affect the functions they…
Hierarchical Clustering for Euclidean Data
Moses Charikar, Vaggos Chatziafratis, Rad Niazadeh +1
Recent works on Hierarchical Clustering (HC), a well-studied problem in exploratory data analysis, have focused on optimizing various objective functions for this problem under arb…
Approximate Hierarchical Clustering via Sparsest Cut and Spreading Metrics
Moses Charikar, Vaggos Chatziafratis
Dasgupta recently introduced a cost function for the hierarchical clustering of a set of points given pairwise similarities between them. He showed that this function is NP-hard to…