Abstract— The success of classical high level synthesis has been limited by the complexity of the applications it can handle, typically not large enough to necessitate the depart...
We consider the problem of learning incoherent sparse and lowrank patterns from multiple tasks. Our approach is based on a linear multi-task learning formulation, in which the spa...
Enterprises may have multiple database systems spread across the organization for redundancy or for serving different applications. In such systems, query workloads can be distrib...
We consider the problem of selecting a subset of m most informative features where m is the number of required features. This feature selection problem is essentially a combinator...
Zenglin Xu, Rong Jin, Jieping Ye, Michael R. Lyu, ...
Recent algorithmic and theoretical advances in reinforcement learning (RL) have attracted widespread interest. RL algorithmshave appeared that approximatedynamic programming on an ...