We present a set of techniques for placement-coupled, timingdriven logic replication. Two components are at the core of the approach. First is an algorithm for optimal timingdrive...
We present a novel framework for learning a joint shape and appearance model from a large set of un-labelled training examples in arbitrary positions and orientations. The shape an...
In multi-task learning our goal is to design regression or classification models for each of the tasks and appropriately share information between tasks. A Dirichlet process (DP) ...
We investigate the problem of learning to predict moves in the board game of Go from game records of expert players. In particular, we obtain a probability distribution over legal...
Clustering is one of the most widely used statistical tools for data analysis. Among all existing clustering techniques, k-means is a very popular method because of its ease of pr...