Deep Reinforcement Learning Bootcamp: Event Report


2017-09-04 14:49:39

Preferred Networks proudly sponsored an exciting two-day event, Deep Reinforcement Learning Bootcamp, which was held August 26-27th at UC Berkeley.

The instructors of this event included famous researchers in this field, such as Vlad Mnih (DeepMind, creator of DQN), Pieter Abbeel (OpenAI/UC Berkeley), Sergey Levine (Google Brain/UC Berkeley), Andrej Karpathy (Tesla, head of AI), John Schulman (OpenAI) and up-and-coming researchers such as Chelsea Finn, Rocky Duan, and Peter Chen (UC Berkeley).

[Taken from the event page]

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ICML 2017 Report

Brian Vogel

2017-08-25 10:09:00

Preferred Networks (PFN) attended the International Conference on Machine Learning (ICML) in Sydney, Australia. The first ICML was held in 1980 in Pittsburgh, last year’s conference was in New York, and the 2018 ICML will be held in Stockholm. ICML is one of the largest machine learning conferences, with approximately 2400 people attending this year. There were 434 accepted submissions spanning nearly all areas of machine learning.

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CVPR 2017: Conference Report

Tommi Kerola

2017-08-17 10:00:50

Writers: Richard Calland, Tommi Kerola

Preferred Networks (PFN) attended the CVPR 2017 conference in Honolulu, U.S., one of the flagship conferences for discussing research and applications in computer vision and pattern recognition. Computer vision is of major importance for our activities at PFN, including applications for autonomous driving, robotics, and of course products such as PaintsChainer. Modern computer vision is largely based on deep learning, which is relevant for our continued research and product development. In this blog post, we will briefly summarize trends from this conference, focusing on a few papers relevant to each topic.

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ChainerCV Release

Yusuke Niitani

2017-08-14 11:07:10

We released ChainerCV: a utility library for computer vision in deep learning. This library aims at making the process of training and applying deep learning models for computer vision easier using Chainer. It contains high quality implementations of computer vision models, and tools that are necessary to conduct research in this field.

GitHub page:

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IETF 99 Report

Hirochika Asai

2017-08-08 14:01:13

Hello! I’m Hirochika Asai, working as a researcher at Preferred Networks (PFN). I joined PFN from this April. Today, I briefly report the 99th meeting of the Internet Engineering Task Force (IETF) (IETF 99) in this post. I participated in IETF 99, held at Hilton Prague, Prague, Czech. It was the first attendance to the IETF meetings from PFN.

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Publish 2017 PFN Internship Coding Tasks

Kosuke Nakago

2017-08-01 11:23:51

* Japanese blog is also written here.

Preferred Networks (PFN) organizes two-month-long summer internship program for students in August and September every year.

The number of applications is increasing year by year. This year we have received the highest number of applications ever and the interview and selection process has been finished.

PFN 2017 Summer Internship Program


Then we have published our intern coding tasks on github.

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FCN-Based 6D Robotic Grasping for Arbitrary Placed Objects


2017-07-25 10:01:28

Hello! My name is Hitoshi Kusano. I participated in 2016 PFN summer internship program and have been a part-time engineer at PFN ever since, while also studying machine learning at Kyoto University. At PFN, my research topic was to teach an industrial robot how to pick up an object.

Based on the result of my work at PFN, I presented a paper titled ”FCN-Based 6D Robotic Grasping for Arbitrary Placed Objects” at the Learning and Control for Autonomous Manipulation Systems: The Role of Dimensionality Reduction workshop at ICRA 2017, the world’s biggest annual conference in robotics.

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Pieter Abbeel becomes Technical Advisor at Preferred Networks


2017-07-24 12:00:56

Today, Preferred Networks is pleased to announce that Professor Pieter Abbeel, UC Berkeley and OpenAI, will be appointed as a technical advisor. PFN researchers and engineers are very excited about this news and looking forward to working with him.

Prof. Pieter Abbeel


Though he does not require any introduction, let me share the story behind it in the following.

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ICLR 2017: Conference Report & Coming ICML


2017-07-21 11:20:57

I am Takeru Miyato, a researcher at Preferred Networks (PFN), and I participated in  ICLR 2017 (4/24-4/26), which is the biggest conference on deep learning research.

Let me give you a brief overview of the event. ICLR has been held since 2013 and this was the fifth ICLR. The main features of ICLR are:

  • Focus on deep learning and its application. Most of the papers focus on neural networks.
  • Adaptation of open review system. Everyone can join the review process. To be precise, everyone can see the all of the reviews and rebuttals and also can comment, ask questions, and post his or her reviews as public reviews. In addition, authors can update their paper anytime from the feedback until the end of the discussion phase.

As far as I know, there is no other conference exposing the all of the reviews and rebuttals to the public, which I think is interesting / helpful to the people who write or review research papers. Also, some people analyzed the submissions and reviews, and they posted articles with interesting results. Here are some links to a pair of interesting ones:

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IV 2017: Conference Report


2017-07-13 10:56:42

Writers: Tommi Kerola, Shintarou Okada, Shirou Maruyama

Preferred Networks (PFN) was present at the IEEE IV 2017 conference in Redondo Beach, CA, US, one of the flagship conferences for discussing research and applications for intelligent vehicles, including techniques for autonomous driving. Autonomous driving is one of the fields of main importance for PFN, which is why three of our members attended the conference in order to learn more about the latest research, and to connect with people from both academia and the industry. In this blog post, we will briefly summarize trends from this conference, focusing mainly on perception and motion planning.


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