A fundamental problem in data management is to draw and maintain a sample of a large data set, for approximate query answering, selectivity estimation, and query planning. With la...
Graham Cormode, S. Muthukrishnan, Ke Yi, Qin Zhang
Existing techniques for approximate storage of visited states in a model checker are too special-purpose and too DRAM-intensive. Bitstate hashing, based on Bloom filters, is good ...
In this paper, we propose the concept of Manifold of Facial Expression based on the observation that images of a subject’s facial expressions define a smooth manifold in the hig...
Both the logic and the stochastic analysis of discrete-state systems are hindered by the combinatorial growth of the state space underlying a high-level model. In this work, we con...
Reinforcement learning is an effective machine learning paradigm in domains represented by compact and discrete state-action spaces. In high-dimensional and continuous domains, ti...