196 citations · 214 across the 5 of their papers we have counts for
4 papers · 1 filter
TabTransformer: Tabular Data Modeling Using Contextual Embeddings
Xin Huang, Ashish Khetan, Milan Cvitkovic +1
We propose TabTransformer, a novel deep tabular data modeling architecture for supervised and semi-supervised learning. The TabTransformer is built upon self-attention based Transf…
PruneNet: Channel Pruning via Global Importance
Ashish Khetan, Zohar Karnin
Channel pruning is one of the predominant approaches for accelerating deep neural networks. Most existing pruning methods either train from scratch with a sparsity inducing term su…
DARC: Differentiable ARchitecture Compression
Shashank Singh, Ashish Khetan, Zohar Karnin
In many learning situations, resources at inference time are significantly more constrained than resources at training time. This paper studies a general paradigm, called Different…
Number of Connected Components in a Graph: Estimation via Counting Patterns
Ashish Khetan, Harshay Shah, Sewoong Oh
Due to the limited resources and the scale of the graphs in modern datasets, we often get to observe a sampled subgraph of a larger original graph of interest, whether it is the wo…