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Deep learning has brought incredible progress in areas where traditional algorithms struggle. It can be because they need rules that are sometimes hard to conceptualize, it can also be that the number and manner of combining these rules are too complex to ...
This manuscript is the lecture notes of B. Barak’s course in the Les Houches ‘Statistical Physics and Machine Learning’ summer school in 2022. It surveys various proxies for computational hardness in random planted problems, from the low-degree likelihood ...
Recent advancements in deep learning have found compelling applications in the image-based inspection of infrastructure systems. However, the efficacy of these models hinges significantly on the quality and diversity of the input data used for training. In ...
