I’m a Computer Science PhD student in the
ASPIRE,
BAIR,
BDD labs,
where I’m part of
Kurt Keutzer’s
group.
My current work is on stochastic optimization methods for deep learning,
including parallel/distributed learning and new algorithms.
I’m also interested in all things related to Monte Carlo tree search
and GPUs.

I received my AB in Physics from Princeton University in 2012.

#### Preprints

##### Regret Minimization for Partially Observable Deep Reinforcement Learning

Peter H. Jin, Sergey Levine, and Kurt Keutzer

[arxiv]

##### SqueezeDet: Unified, Small, Low Power Fully Convolutional Neural Networks for Real-Time Object Detection for Autonomous Driving

Bichen Wu, Forrest Iandola, Peter H. Jin, and Kurt Keutzer

CVPR Embedded Vision Workshop 2017

[arxiv]

##### How to scale distributed deep learning? [a.k.a. the gossiping SGD paper]

Peter H. Jin, Qiaochu Yuan, Forrest Iandola, and Kurt Keutzer

NIPS ML Systems Workshop 2016

[arxiv]

##### Convolutional Monte Carlo Rollouts in Go

Peter H. Jin and Kurt Keutzer

CG 2016 Neural Networks Workshop

[arxiv]