Temporal difference methods are theoretically grounded and empirically effective methods for addressing reinforcement learning problems. In most real-world reinforcement learning ...
We initiate the study of the computational complexity of the covering radius problem for point lattices, and approximation versions of the problem for both lattices and linear cod...
In this paper, we examine a method for feature subset selection based on Information Theory. Initially, a framework for de ning the theoretically optimal, but computationally intr...
We investigate the diameter problem in the streaming and slidingwindow models. We show that, for a stream of n points or a sliding window of size n, any exact algorithm for diamet...
This paper presents the first theoretical study, on using local-recoding generalization (LRG) to compute a kanonymous table with quality guarantee. First, we prove that it is NP-h...
Yang Du, Tian Xia, Yufei Tao, Donghui Zhang, Feng ...