Researchers have demonstrated that the maximum of n real numbers can be precisely represented by a ReLU network with two hidden layers for any n up to 10. This is achieved by translating the problem into exact rational linear algebra, solving for necessary cancellations computationally. The study also shows that for n > 10, the maximum can be represented with fewer hidden layers than previously thought, improving upon prior bounds. AI
IMPACT This research advances the theoretical understanding of ReLU networks, potentially influencing the design and efficiency of future neural network architectures.
RANK_REASON The cluster contains a research paper published on arXiv detailing theoretical advancements in neural network representations.
Read on arXiv cs.NE (Neural & Evolutionary) →
- arXiv cs.NE
- Brunck
- Hertrich
- IEEE Trans. Inf. Theory
- ReLU
- STOC'26
- Wang
- Yehudayoff
- ACM Symposium on Theory of Computing
- arXiv
- IEEE Transactions on Information Theory
- Sun
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