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cs.LG2022
MinUn: Accurate ML Inference on Microcontrollers
Shikhar Jaiswal, Rahul Kiran Kranti Goli, Aayan Kumar +2
Running machine learning inference on tiny devices, known as TinyML, is an emerging research area. This task requires generating inference code that uses memory frugally, a task th…
cs.LG2021
Variational Rejection Particle Filtering
Rahul Sharma, Soumya Banerjee, Dootika Vats +1
We present a variational inference (VI) framework that unifies and leverages sequential Monte-Carlo (particle filtering) with \emph{approximate} rejection sampling to construct a f…
cs.LG2019
Refined -Divergence Variational Inference via Rejection Sampling
Rahul Sharma, Abhishek Kumar, Piyush Rai
We present an approximate inference method, based on a synergistic combination of Rényi -divergence variational inference (RDVI) and rejection sampling (RS). RDVI is based on mi…