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Priya Kasimbeg

2 accepted papers

2025

Accelerating neural network training: An analysis of the AlgoPerf competition

ICLR 2025poster

The goal of the AlgoPerf: Training Algorithms competition is to evaluate practical speed-ups in neural network training achieved solely by improving the underlying training algorithms. In the external tuning ruleset, submissions must provide workload-agnostic hyperparameter search spaces, while in t…

Cited by 0SourcePDFScholar
2020

Interactive Gibson Benchmark: A Benchmark for Interactive Navigation in Cluttered Environments

RA-L 2020

We present Interactive Gibson Benchmark, the first comprehensive benchmark for training and evaluating Interactive Navigation solutions. Interactive Navigation tasks are robot navigation problems where physical interaction with objects (e.g., pushing) is allowed and even encouraged to reach the goal

Cited by 211SourceScholar