10 citations · 11 across the 5 of their papers we have counts for
5 papers
Deep Learning based Forecasting: a case study from the online fashion industry
Manuel Kunz, Stefan Birr, Mones Raslan +13
Demand forecasting in the online fashion industry is particularly amendable to global, data-driven forecasting models because of the industry's set of particular challenges. These…
Probabilistic Time Series Forecasting with Implicit Quantile Networks
Adèle Gouttes, Kashif Rasul, Mateusz Koren +2
Here, we propose a general method for probabilistic time series forecasting. We combine an autoregressive recurrent neural network to model temporal dynamics with Implicit Quantile…
Automatic Pronunciation Generation by Utilizing a Semi-supervised Deep Neural Networks
Naoya Takahashi, Tofigh Naghibi, Beat Pfister
Phonemic or phonetic sub-word units are the most commonly used atomic elements to represent speech signals in modern ASRs. However they are not the optimal choice due to several re…
A Semidefinite Programming Based Search Strategy for Feature Selection with Mutual Information Measure
Tofigh Naghibi, Sarah Hoffmann, Beat Pfister
Feature subset selection, as a special case of the general subset selection problem, has been the topic of a considerable number of studies due to the growing importance of data-mi…
A Boosting Framework on Grounds of Online Learning
Tofigh Naghibi, Beat Pfister
By exploiting the duality between boosting and online learning, we present a boosting framework which proves to be extremely powerful thanks to employing the vast knowledge availab…