2 papers
cs.LG2025
Depth-Width tradeoffs in Algorithmic Reasoning of Graph Tasks with Transformers
Gilad Yehudai, Clayton Sanford, Maya Bechler-Speicher +3
Transformers have revolutionized the field of machine learning. In particular, they can be used to solve complex algorithmic problems, including graph-based tasks. In such algorith…
cs.LG2023
Optimal Sample Complexity of Contrastive Learning
Noga Alon, Dmitrii Avdiukhin, Dor Elboim +2
Contrastive learning is a highly successful technique for learning representations of data from labeled tuples, specifying the distance relations within the tuple. We study the sam…