The linear model with sparsity-favouring prior on the coefficients has important applications in many different domains. In machine learning, most methods to date search for maxim...
Similarity search methods are widely used as kernels in various data mining and machine learning applications including those in computational biology, web search/clustering. Near...
Recent scaling up of POMDP solvers towards realistic applications is largely due to point-based methods such as PBVI, Perseus, and HSVI, which quickly converge to an approximate so...
Partially observable Markov decision processes (POMDPs) provide a principled, general framework for robot motion planning in uncertain and dynamic environments. They have been app...
Sylvie C. W. Ong, Shao Wei Png, David Hsu, Wee Sun...
In this work we focus on the problem of frequent itemset mining on large, out-of-core data sets. After presenting a characterization of existing out-of-core frequent itemset minin...