activity
20172021
most citedEfficient Autotuning of Hyperparameters in Approximate Nearest Neighbor Search

7 citations · 8 across the 2 of their papers we have counts for

collaborators

5 papers

cs.CV2021

Transfer Learning with Ensembles of Deep Neural Networks for Skin Cancer Detection in Imbalanced Data Sets

Aqsa Saeed Qureshi, Teemu Roos

Several machine learning techniques for accurate detection of skin cancer from medical images have been reported. Many of these techniques are based on pre-trained convolutional ne…

stat.ME2019

Minimum Description Length Revisited

Peter Grünwald, Teemu Roos

This is an up-to-date introduction to and overview of the Minimum Description Length (MDL) Principle, a theory of inductive inference that can be applied to general problems in sta…

cs.DS20187 cited

Efficient Autotuning of Hyperparameters in Approximate Nearest Neighbor Search

Elias Jääsaari, Ville Hyvönen, Teemu Roos

Approximate nearest neighbor algorithms are used to speed up nearest neighbor search in a wide array of applications. However, current indexing methods feature several hyperparamet…

cs.IT2018

An Application of Storage-Optimal MatDot Codes for Coded Matrix Multiplication: Fast k-Nearest Neighbors Estimation

Utsav Sheth, Sanghamitra Dutta, Malhar Chaudhari +5

We propose a novel application of coded computing to the problem of the nearest neighbor estimation using MatDot Codes [Fahim. et.al. 2017], that are known to be optimal for matrix…

cs.LG20171 cited

Learning non-parametric Markov networks with mutual information

Janne Leppä-aho, Santeri Räisänen, Xiao Yang +1

We propose a method for learning Markov network structures for continuous data without invoking any assumptions about the distribution of the variables. The method makes use of pre…