E-graphs, originally developed for use in automated theorem provers, are data structures that compactly represent a large number of expressions and the equalities between them. Recently, a technique ...

Combinatorial optimization is a broadly attractive area for potential quantum advantage, but no quantum algorithm has yet made the leap. Noise in quantum hardware remains a challenge, and more ...

Lets geek out. The HackerNoon library is now ranked by reading time created. Start learning by what others read most. A full stack developer is an engineer who can handle all the work of databases, ...

Coachella invented the modern music festival, drafting the blueprint for genre-hopping lineups that place equal emphasis on fads and classics. Ever since the inaugural two-day celebration in 1999, ...

Uncertainties are widespread in the optimization of process systems, such as uncertainties in process technologies, prices, and customer demands. In this paper, we review the basic concepts and recent ...

A deep Q network (DQN) (Mnih et al., 2013) is an extension of Q learning, which is a typical deep reinforcement learning method. In DQN, a Q function expresses all action values under all states, and ...

Robots working in human environments often encounter a wide range of articulated objects, such as tools, cabinets, and other jointed objects. Such articulated objects can take an infinite number of ...

Optimization problems arise naturally in statistical machine learning and other fields concerned with data analysis. The rapid growth in the scale and complexity of modern datasets has led to a focus ...