In this paper we present a simple to implement truly online large margin version of the Perceptron ranking (PRank) algorithm, called the OAP-BPM (Online Aggregate Prank-Bayes Poin...
Most existing techniques for analyzing face images assume that the faces are at near-frontal poses. Generalizing to non-frontal faces is often difficult, due to a dearth of groun...
One aim of Meta-learning techniques is to minimize the time needed for problem solving, and the effort of parameter hand-tuning, by automating algorithm selection. The predictive m...
The Viterbi algorithm is an efficient and optimal method for decoding linear-chain Markov Models. However, the entire input sequence must be observed before the labels for any tim...
Inference is a key component in learning probabilistic models from partially observable data. When learning temporal models, each of the many inference phases requires a complete ...