9 citations · 9 across the 4 of their papers we have counts for
4 papers
Using Sparse Semantic Embeddings Learned from Multimodal Text and Image Data to Model Human Conceptual Knowledge
Steven Derby, Paul Miller, Brian Murphy +1
Distributional models provide a convenient way to model semantics using dense embedding spaces derived from unsupervised learning algorithms. However, the dimensions of dense embed…
NIPS 2016 Workshop on Representation Learning in Artificial and Biological Neural Networks (MLINI 2016)
Leila Wehbe, Anwar Nunez-Elizalde, Marcel van Gerven +5
This workshop explores the interface between cognitive neuroscience and recent advances in AI fields that aim to reproduce human performance such as natural language processing and…
Proceedings of the 5th Workshop on Machine Learning and Interpretation in Neuroimaging (MLINI) at NIPS 2015
I. Rish, L. Wehbe, G. Langs +3
This volume is a collection of contributions from the 5th Workshop on Machine Learning and Interpretation in Neuroimaging (MLINI) at the Neural Information Processing Systems (NIPS…
Scoup-SMT: Scalable Coupled Sparse Matrix-Tensor Factorization
Evangelos E. Papalexakis, Tom M. Mitchell, Nicholas D. Sidiropoulos +3
How can we correlate neural activity in the human brain as it responds to words, with behavioral data expressed as answers to questions about these same words? In short, we want to…