Temporally-asymmetric Hebbian learning is a class of algorithms motivated by data from recent neurophysiology experiments. While traditional Hebbian learning rules use mean firin...
Data quality is critical for many information-intensive applications. One of the best opportunities to improve data quality is during entry. USHER provides a theoretical, data-dri...
Kuang Chen, Joseph M. Hellerstein, Tapan S. Parikh
Ranking algorithms, whose goal is to appropriately order a set of objects/documents, are an important component of information retrieval systems. Previous work on ranking algorith...
: Precise sensorimotor mappings between various motor, ensor, and abstract physical spaces are the basis for many robotics tasks. Their cheap construction is a challenge for adapti...
Background: Generally speaking, different classifiers tend to work well for certain types of data and conversely, it is usually not known a priori which algorithm will be optimal ...