52 citations · 126 across the 9 of their papers we have counts for
10 papers
Poisson Subspace Clustering: Focusing on the Essentials in Count Data
Collin Leiber, Kai Puolamäki, Heikki Mannila
Count data represented as a matrix of non-negative integer values, such as contingency tables, are prevalent across diverse domains. When clustering such data sets, specific method…
Optimal Union Probability Interval Is NP-Hard
Petteri Kaski, Heikki Mannila, Chandra Kanta Mohapatra
A problem dating back to Boole [Laws of Thought, Walton & Maberly,1854] is what can be computed about the probability of a finite union of events when given as input the probabilit…
Khatri-Rao Clustering for Data Summarization
Martino Ciaperoni, Collin Leiber, Aristides Gionis +1
As datasets continue to grow in size and complexity, finding succinct yet accurate data summaries poses a key challenge. Centroid-based clustering, a widely adopted approach to add…
Sample and Expand: Discovering Low-rank Submatrices With Quality Guarantees
Martino Ciaperoni, Aristides Gionis, Heikki Mannila
The problem of approximating a matrix by a low-rank one has been extensively studied. This problem assumes, however, that the whole matrix has a low-rank structure. This assumption…
Fair PCA, One Component at a Time
Antonis Matakos, Martino Ciaperoni, Heikki Mannila
The Min-Max Fair PCA problem seeks a low-rank representation of multi-group data such that the the approximation error is as balanced as possible across groups. Existing approaches…
Tell Me Something I Don't Know: Randomization Strategies for Iterative Data Mining
Sami Hanhijärvi, Markus Ojala, Niko Vuokko +3
There is a wide variety of data mining methods available, and it is generally useful in exploratory data analysis to use many different methods for the same dataset. This, however,…