1 citations · 1 across the 4 of their papers we have counts for
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Contrastive Neural Algorithmic Reasoning for Graph Coloring
Thien Le, Tianyu Zhao, Melanie Weber
Graph coloring seeks to assigns colors to a graph's nodes so that adjacent nodes receive different colors, using as few colors as possible. Here, we study approximate -coloring,…
Towards Distillation Guarantees under Algorithmic Alignment for Combinatorial Optimization
Thien Le, Melanie Weber
Distillation transfers knowledge from a large model trained on broad data to a smaller, more efficient model suitable for deployment. In structured prediction settings, prior knowl…
On the hardness of learning under symmetries
Bobak T. Kiani, Thien Le, Hannah Lawrence +2
We study the problem of learning equivariant neural networks via gradient descent. The incorporation of known symmetries ("equivariance") into neural nets has empirically improved…
A Poincaré Inequality and Consistency Results for Signal Sampling on Large Graphs
Thien Le, Luana Ruiz, Stefanie Jegelka
Large-scale graph machine learning is challenging as the complexity of learning models scales with the graph size. Subsampling the graph is a viable alternative, but sampling on gr…