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cs.LG2026
Algorithmic Separation between Constant-Depth and Logarithmic-Depth Neural Networks
Yunwei Ren, Zihao Wang, Jason D. Lee
Despite the empirical advantages of deep networks over shallow ones, theoretical depth separations largely concern approximation power, while algorithmic results are mostly limited…
cs.LG2026
Provable Learning of Random Hierarchy Models and Hierarchical Shallow-to-Deep Chaining
Yunwei Ren, Yatin Dandi, Florent Krzakala +1
The empirical success of deep learning is often attributed to deep networks' ability to exploit hierarchical structure in data, constructing increasingly complex features across la…