Abstract: Symbolic regression (SR) is an important problem with many applications, such as automatic programming tasks and data mining. Genetic programming (GP) is a commonly used technique for SR. In ...

Any confusion concerning who has the top individual TV shows -- linear, streaming, or otherwise -- should be clear when Nielsen -- or others -- release show-by-show traditional average viewer ...

Today we heard from [Richard James Howe] about his new CPU. This new 16-bit CPU is implemented in VHDL for an FPGA. The really cool thing about this CPU is that it eschews the typical program counter ...

What is linear regression in machine learning ? Understanding Linear Regression in machine learning is considered as the basis or foundation in machine learning. In this video, we will learn what is ...

Figure 1 A typical regulator output programming network where the Vsense feedback node and values for R1 varies from type to type. Quantitatively, the Vsense feedback node voltage varies from type to ...

You’d be hard-pressed to find better examples of government waste than the ones in Donald Trump’s cruel and illiberal anti-immigration agenda. He cost taxpayers millions of dollars with the use of ...

Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. There is a need for design strategies that can support rapid and widespread deployment ...

Abstract: This study proposes LiP-LLM: integrating linear programming and dependency graph with large language models (LLMs) for multi-robot task planning. For multi-robots to efficiently perform ...