Abstract: Data-driven inverse reinforcement learning (RL) control aims to infer the unknown cost function of a learner system from expert demonstrations. The convergence of existing methods ...

Abstract: This paper presents BAM-Net, a hardware-efficient binarization algorithm designed for associative memory (AM) implementation. BAM-Net aims to reduce memory overhead, power consumption, and ...

The breakneck expansion of cloud computing and AI is straining global data centers. All this data has to be stored and processed, which consumes enormous amounts of electricity per year, driving ...