A new parameter estimation method is presented, applicable to many computer vision problems. It operates under the assumption that the data (typically image point locations) are a...
Wojciech Chojnacki, Michael J. Brooks, Anton van d...
Achieving design closure is one of the biggest headaches for modern VLSI designers. This problem is exacerbated by high-level design automation tools that ignore increasingly impo...
Zhenyu (Peter) Gu, Jia Wang, Robert P. Dick, Hai Z...
In this paper, we present a low-power architectural synthesis system (LOPASS) for field-programmable gate-array (FPGA) designs with interconnect power estimation and optimization. ...
Reinforcement learning problems are commonly tackled with temporal difference methods, which use dynamic programming and statistical sampling to estimate the long-term value of ta...
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...