GREED: A Neural Framework for Learning Graph Distance Functions
- Rishabh Ranjan
- Siddharth Grover
- et al.
- 2022
- NeurIPS 2022
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58 results for Yogish Sabharwal
Efficient Scaling of Dynamic Graph Neural Networks
- Venkatesan T. Chakaravarthy
- Shivmaran S. Pandian
- et al.
- 2021
- SC 2021
Effective Elastic Scaling of Deep Learning Workloads
- Vaibhav Saxena
- Jayaram Kr Kallapalayam Radhakrishnan
- et al.
- 2020
- MASCOTS 2020
PoWER-BERT: Accelerating BERT inference via progressive word-vector elimination
- Saurabh Goyal
- Anamitra R. Choudhury
- et al.
- 2020
- ICML 2020
Variable batch size across layers for efficient prediction on CNNs
- Anamitra R. Choudhury
- Saurabh Goyal
- et al.
- 2020
- CLOUD 2020
Looking under the hood of the IBM blue gene/Q network
- Dong Chen
- Noel Eisley
- et al.
- 2012
- SC 2012
A divide and conquer strategy for scaling weather simulations with multiple regions of interest
- Preeti Malakar
- Thomas George
- et al.
- 2012
- SC 2012
Breaking the speed and scalability barriers for graph exploration on distributed-memory machines
- Fabio Checconi
- Fabrizio Petrini
- et al.
- 2012
- SC 2012
Rightsizing Clusters for Time-Limited Tasks
- Venkatesan T. Chakaravarthy
- Padmanabha V. Seshadri
- et al.
- 2021
- CLOUD 2021
Linear-time approximation schemes for clustering problems in any dimensions
- Amit Kumar
- Yogish Sabharwal
- et al.
- 2010
- Journal of the ACM