1.2k citations · 2.2k across the 38 of their papers we have counts for
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HiTR: Hierarchical Topic Model Re-estimation for Measuring Topical Diversity of Documents
Hosein Azarbonyad, Mostafa Dehghani, Tom Kenter +3
A high degree of topical diversity is often considered to be an important characteristic of interesting text documents. A recent proposal for measuring topical diversity identifies…
Universal Transformers
Mostafa Dehghani, Stephan Gouws, Oriol Vinyals +2
Recurrent neural networks (RNNs) sequentially process data by updating their state with each new data point, and have long been the de facto choice for sequence modeling tasks. How…
Learning to Rank from Samples of Variable Quality
Mostafa Dehghani, Jaap Kamps
Training deep neural networks requires many training samples, but in practice, training labels are expensive to obtain and may be of varying quality, as some may be from trusted ex…
Neural Networks for Information Retrieval
Tom Kenter, Alexey Borisov, Christophe Van Gysel +3
Machine learning plays a role in many aspects of modern IR systems, and deep learning is applied in all of them. The fast pace of modern-day research has given rise to many approac…