171 citations · 173 across the 2 of their papers we have counts for
6 papers
Direct Federated Neural Architecture Search
Anubhav Garg, Amit Kumar Saha, Debo Dutta
Neural Architecture Search (NAS) is a collection of methods to craft the way neural networks are built. We apply this idea to Federated Learning (FL), wherein predefined neural net…
Revisiting Neural Architecture Search
Anubhav Garg, Amit Kumar Saha, Debo Dutta
Neural Architecture Search (NAS) is a collection of methods to craft the way neural networks are built. Current NAS methods are far from ab initio and automatic, as they use manual…
NASIB: Neural Architecture Search withIn Budget
Abhishek Singh, Anubhav Garg, Jinan Zhou +2
Neural Architecture Search (NAS) represents a class of methods to generate the optimal neural network architecture and typically iterate over candidate architectures till convergen…
MLPerf Training Benchmark
Peter Mattson, Christine Cheng, Cody Coleman +34
Machine learning (ML) needs industry-standard performance benchmarks to support design and competitive evaluation of the many emerging software and hardware solutions for ML. But M…
Tiered Object Storage using Persistent Memory
Johnu George, Ramdoot Pydipaty, Xinyuan Huang +4
Most data intensive applications often access only a few fields of the objects they are operating on. Since NVM provides fast, byte-addressable access to durable memory, it is poss…
Fast Neural Architecture Construction using EnvelopeNets
Purushotham Kamath, Abhishek Singh, Debo Dutta
Fast Neural Architecture Construction (NAC) is a method to construct deep network architectures by pruning and expansion of a base network. In recent years, several automated searc…