Off-policy reinforcement learning is aimed at efficiently reusing data samples gathered in the past, which is an essential problem for physically grounded AI as experiments are us...
Achieving high performance on today’s architectures requires careful orchestration of many optimization parameters. In particular, the presence of shared-caches on multicore arch...
This paper presents a new approach to timing optimization for FPGA designs, namely incremental physical resynthesis, to answer the challenge of effectively integrating logic and p...
Peter Suaris, Lung-Tien Liu, Yuzheng Ding, Nan-Chi...
We consider the problem of clustering in its most basic form where only a local metric on the data space is given. No parametric statistical model is assumed, and the number of cl...
Cell tower triangulation is a popular technique for determining the location of a mobile device. However, cell tower triangulation methods require the knowledge of the actual loca...
Jie Yang, Alexander Varshavsky, Hongbo Liu, Yingyi...