activity
20192021
most citedEfficient Integration of Multi-channel Information for Speaker-independent Speech Separation

3 citations · 8 across the 5 of their papers we have counts for

collaborators

5 papers

cs.LG20213 cited

Proceedings of the NeurIPS 2020 Workshop on Machine Learning for the Developing World: Improving Resilience

Tejumade Afonja, Konstantin Klemmer, Aya Salama +3

These are the proceedings of the 4th workshop on Machine Learning for the Developing World (ML4D), held as part of the Thirty-fourth Conference on Neural Information Processing Sys…

cs.LG20202 cited

Differentiable Histogram with Hard-Binning

Ibrahim Yusuf, George Igwegbe, Oluwafemi Azeez

The simplicity and expressiveness of a histogram render it a useful feature in different contexts including deep learning. Although the process of computing a histogram is non-diff…

eess.AS20203 cited

Efficient Integration of Multi-channel Information for Speaker-independent Speech Separation

Yuichiro Koyama, Oluwafemi Azeez, Bhiksha Raj

Although deep-learning-based methods have markedly improved the performance of speech separation over the past few years, it remains an open question how to integrate multi-channel…

cs.MA2019

Agent Probing Interaction Policies

Siddharth Ghiya, Oluwafemi Azeez, Brendan Miller

Reinforcement learning in a multi agent system is difficult because these systems are inherently non-stationary in nature. In such a case, identifying the type of the opposite agen…

cs.CV2019

Unsupervised Domain Adaptation by Optical Flow Augmentation in Semantic Segmentation

Oluwafemi Azeez

It is expensive to generate real-life image labels and there is a domain gap between real-life and simulated images, hence a model trained on the latter cannot adapt to the former.…