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Featured Co-authors

Liang Wang
119 publications
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∙ 03/22/2021

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

Early diagnosis plays a key role in prevention and treatment of skin can...

0 Aqsa Saeed Qureshi, et al. ∙

∙ 04/06/2020

Gradient-Based Training and Pruning of Radial Basis Function Networks with an Application in Materials Physics

Many applications, especially in physics and other sciences, call for ea...

10 Jussi Määttä, et al. ∙

∙ 10/18/2019

Supervised Learning Approach to Approximate Nearest Neighbor Search

Approximate nearest neighbor search is a classic algorithmic problem whe...

0 Ville Hyvönen, et al. ∙

∙ 08/21/2019

Minimum Description Length Revisited

This is an up-to-date introduction to and overview of the Minimum Descri...

0 Peter Grünwald, et al. ∙

∙ 12/18/2018

Efficient Autotuning of Hyperparameters in Approximate Nearest Neighbor Search

Approximate nearest neighbor algorithms are used to speed up nearest nei...

0 Elias Jääsaari, et al. ∙

∙ 11/28/2018

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

We propose a novel application of coded computing to the problem of the ...

0 Utsav Sheth, et al. ∙

∙ 08/08/2017

Learning non-parametric Markov networks with mutual information

We propose a method for learning Markov network structures for continuou...

0 Janne Leppä-aho, et al. ∙

∙ 02/25/2016

Learning Gaussian Graphical Models With Fractional Marginal Pseudo-likelihood

We propose a Bayesian approximate inference method for learning the depe...

0 Janne Leppä-aho, et al. ∙

∙ 09/23/2015

Fast k-NN search

Efficient index structures for fast approximate nearest neighbor queries...

0 Ville Hyvönen, et al. ∙

∙ 01/28/2014

Bayesian Properties of Normalized Maximum Likelihood and its Fast Computation

The normalized maximized likelihood (NML) provides the minimax regret so...

0 Andrew Barron, et al. ∙

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