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Found 5 papers, 2 papers with code
Explaining Classifiers by Constructing Familiar Concepts
Our proposed `CLAssifier-DECoder' architecture (ClaDec) facilitates the understanding of the output of an arbitrary layer of neurons or subsets thereof.
Personalization of Deep Learning
We discuss training techniques, objectives and metrics toward personalization of deep learning models.
Scalable and interpretable product recommendations via overlapping co-clustering
We consider the problem of generating interpretable recommendations by identifying overlapping co-clusters of clients and products, based only on positive or implicit feedback.
Compressive Mining: Fast and Optimal Data Mining in the Compressed Domain
However, distance estimation when the data are represented using different sets of coefficients is still a largely unexplored area.
Approximate Matrix Multiplication with Application to Linear Embeddings
In this paper, we study the problem of approximately computing the product of two real matrices.
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