Those that solve artificially simplified problems where quantum advantage is meaningless. Those that provide no genuine quantum advantage when all costs are properly accounted for. This critique is ...
Abstract: Adversarial imitation learning (AIL), a prominent approach in imitation learning, has achieved significant practical success powered by neural network approximation. However, existing ...
There’s a familiar TV discourse taking shape online right now, the kind that I suspect will look awfully familiar to you if you remember the way Game of Thrones crashed and burned in its eighth and ...
I (94) esp_image: segment 0: paddr=00010020 vaddr=3f400020 size=1e314h (123668) map I (133) esp_image: segment 1: paddr=0002e33c vaddr=3ff80000 size=0001ch ( 28) load I (133) esp_image: segment 2: ...
Abstract: In applied and numerical algebraic geometry, many problems are reduced to computing an approximation to a real algebraic curve. In order to elevate the results of such a computation to the ...
One of the biggest barriers to using AI successfully is bias, which is one of the terms we defined last time, as follows: Bias, in a general context, refers to a predisposition or inclination towards ...
Abstract: Noncommutative constraint satisfaction problems (CSPs) are higher-dimensional operator extensions of classical CSPs. Their approximability remains largely unexplored. A notable example of a ...
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