Deep Belief Networks (DBN's) are generative models that contain many layers of hidden variables. Efficient greedy algorithms for learning and approximate inference have allow...
When given a small sample, we show that classification with SVM can be considerably enhanced by using a kernel function learned from the training data prior to discrimination. Thi...
Many NLP tasks rely on accurately estimating word dependency probabilities P(w1|w2), where the words w1 and w2 have a particular relationship (such as verb-object). Because of the...
Kristina Toutanova, Christopher D. Manning, Andrew...
In the task of adaptive information filtering, a system receives a stream of documents but delivers only those that match a person's information need. As the system filters i...
A single signal processing algorithm can be represented by many mathematically equivalent formulas. However, when these formulas are implemented in code and run on real machines, ...