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Preferred Infrastructure, Inc. is a company, providing distributed-realtime search engine, called Sedue. http://preferred.jp/index_en.html

ChainerRL: A Deep Reinforcement Learning Library

In this paper, we introduce ChainerRL, an open-source Deep Reinforcement...
12/09/2019 ∙ by Yasuhiro Fujita, et al. ∙ 41 ∙ share

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Differentiable Rendering: A Survey

Deep neural networks (DNNs) have shown remarkable performance improvemen...
06/22/2020 ∙ by Hiroharu Kato, et al. ∙ 22 ∙ share

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Graph Warp Module: an Auxiliary Module for Boosting the Power of Graph Neural Networks

Recently, Graph Neural Networks (GNNs) are trending in the machine learn...
02/04/2019 ∙ by Katsuhiko Ishiguro, et al. ∙ 20 ∙ share

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Two-stage Discriminative Re-ranking for Large-scale Landmark Retrieval

We propose an efficient pipeline for large-scale landmark image retrieva...
03/25/2020 ∙ by Shuhei Yokoo, et al. ∙ 7 ∙ share

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Discovering Avoidable Planner Failures of Autonomous Vehicles using Counterfactual Analysis in Behaviorally Diverse Simulation

Automated Vehicles require exhaustive testing in simulation to detect as...
11/24/2020 ∙ by Daisuke Nishiyama, et al. ∙ 6 ∙ share

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Hierarchical Lovász Embeddings for Proposal-free Panoptic Segmentation

Panoptic segmentation brings together two separate tasks: instance and s...
06/08/2021 ∙ by Tommi Kerola, et al. ∙ 6 ∙ share

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Reconnaissance and Planning algorithm for constrained MDP

Practical reinforcement learning problems are often formulated as constr...
09/20/2019 ∙ by Shin-ichi Maeda, et al. ∙ 5 ∙ share

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Learning Latent State Spaces for Planning through Reward Prediction

Model-based reinforcement learning methods typically learn models for hi...
12/09/2019 ∙ by Aaron Havens, et al. ∙ 5 ∙ share

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Fast Soft Color Segmentation

We address the problem of soft color segmentation, defined as decomposin...
04/17/2020 ∙ by Naofumi Akimoto, et al. ∙ 4 ∙ share

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Superpixel clustering with deep features for unsupervised road segmentation

Vision-based autonomous driving requires classifying each pixel as corre...
11/16/2017 ∙ by Shunta Saito, et al. ∙ 1 ∙ share

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Periodic Intra-Ensemble Knowledge Distillation for Reinforcement Learning

Off-policy ensemble reinforcement learning (RL) methods have demonstrate...
02/01/2020 ∙ by Zhang-Wei Hong, et al. ∙ 1 ∙ share

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ChainerMN: Scalable Distributed Deep Learning Framework

One of the keys for deep learning to have made a breakthrough in various...
10/31/2017 ∙ by Takuya Akiba, et al. ∙ 0 ∙ share

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Semi-supervised learning of hierarchical representations of molecules using neural message passing

With the rapid increase of compound databases available in medicinal and...
11/28/2017 ∙ by Hai Nguyen, et al. ∙ 0 ∙ share

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Map-based Multi-Policy Reinforcement Learning: Enhancing Adaptability of Robots by Deep Reinforcement Learning

In order for robots to perform mission-critical tasks, it is essential t...
10/17/2017 ∙ by Ayaka Kume, et al. ∙ 0 ∙ share

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Parameter Reference Loss for Unsupervised Domain Adaptation

The success of deep learning in computer vision is mainly attributed to ...
11/20/2017 ∙ by Jiren Jin, et al. ∙ 0 ∙ share

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Extremely Large Minibatch SGD: Training ResNet-50 on ImageNet in 15 Minutes

We demonstrate that training ResNet-50 on ImageNet for 90 epochs can be ...
11/12/2017 ∙ by Takuya Akiba, et al. ∙ 0 ∙ share

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ChainerCV: a Library for Deep Learning in Computer Vision

Despite significant progress of deep learning in the field of computer v...
08/28/2017 ∙ by Yusuke Niitani, et al. ∙ 0 ∙ share

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Spectral Norm Regularization for Improving the Generalizability of Deep Learning

We investigate the generalizability of deep learning based on the sensit...
05/31/2017 ∙ by Yuichi Yoshida, et al. ∙ 0 ∙ share

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Reparameterization trick for discrete variables

Low-variance gradient estimation is crucial for learning directed graphi...
11/04/2016 ∙ by Seiya Tokui, et al. ∙ 0 ∙ share

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Temporal Generative Adversarial Nets with Singular Value Clipping

In this paper, we propose a generative model, Temporal Generative Advers...
11/21/2016 ∙ by Masaki Saito, et al. ∙ 0 ∙ share

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Interactively Picking Real-World Objects with Unconstrained Spoken Language Instructions

Comprehension of spoken natural language is an essential component for r...
10/17/2017 ∙ by Jun Hatori, et al. ∙ 0 ∙ share

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A Neural Language Model for Dynamically Representing the Meanings of Unknown Words and Entities in a Discourse

This study addresses the problem of identifying the meaning of unknown w...
09/06/2017 ∙ by Sosuke Kobayashi, et al. ∙ 0 ∙ share

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cGANs with Projection Discriminator

We propose a novel, projection based way to incorporate the conditional ...
02/15/2018 ∙ by Takeru Miyato, et al. ∙ 0 ∙ share

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Variance-based Gradient Compression for Efficient Distributed Deep Learning

Due to the substantial computational cost, training state-of-the-art dee...
02/16/2018 ∙ by Yusuke Tsuzuku, et al. ∙ 0 ∙ share

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Spectral Normalization for Generative Adversarial Networks

One of the challenges in the study of generative adversarial networks is...
02/16/2018 ∙ by Takeru Miyato, et al. ∙ 0 ∙ share

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Deep Visuo-Tactile Learning: Estimation of Material Properties from Images

Estimation of materials properties, such as softness or roughness from v...
03/09/2018 ∙ by Kuniyuki Takahashi, et al. ∙ 0 ∙ share

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Interpretable Adversarial Perturbation in Input Embedding Space for Text

Following great success in the image processing field, the idea of adver...
05/08/2018 ∙ by Motoki Sato, et al. ∙ 0 ∙ share

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Unsupervised Learning of Style-sensitive Word Vectors

This paper presents the first study aimed at capturing stylistic similar...
05/15/2018 ∙ by Reina Akama, et al. ∙ 0 ∙ share

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Contextual Augmentation: Data Augmentation by Words with Paradigmatic Relations

We propose a novel data augmentation for labeled sentences called contex...
05/16/2018 ∙ by Sosuke Kobayashi, et al. ∙ 0 ∙ share

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BayesGrad: Explaining Predictions of Graph Convolutional Networks

Recent advances in graph convolutional networks have significantly impro...
07/04/2018 ∙ by Hirotaka Akita, et al. ∙ 0 ∙ share

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Addressee and Response Selection for Multilingual Conversation

Developing conversational systems that can converse in many languages is...
08/12/2018 ∙ by Motoki Sato, et al. ∙ 0 ∙ share

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Pointwise HSIC: A Linear-Time Kernelized Co-occurrence Norm for Sparse Linguistic Expressions

In this paper, we propose a new kernel-based co-occurrence measure that ...
09/04/2018 ∙ by Sho Yokoi, et al. ∙ 0 ∙ share

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PFDet: 2nd Place Solution to Open Images Challenge 2018 Object Detection Track

We present a large-scale object detection system by team PFDet. Our syst...
09/04/2018 ∙ by Takuya Akiba, et al. ∙ 0 ∙ share

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Deterministic Implementations for Reproducibility in Deep Reinforcement Learning

While deep reinforcement learning (DRL) has led to numerous successes in...
09/15/2018 ∙ by prabhatn, et al. ∙ 0 ∙ share

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DQN-TAMER: Human-in-the-Loop Reinforcement Learning with Intractable Feedback

Exploration has been one of the greatest challenges in reinforcement lea...
10/28/2018 ∙ by Riku Arakawa, et al. ∙ 0 ∙ share

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Automated Theorem Proving in Intuitionistic Propositional Logic by Deep Reinforcement Learning

The problem-solving in automated theorem proving (ATP) can be interprete...
11/02/2018 ∙ by Mitsuru Kusumoto, et al. ∙ 0 ∙ share

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TGANv2: Efficient Training of Large Models for Video Generation with Multiple Subsampling Layers

In this paper, we propose a novel method to efficiently train a Generati...
11/22/2018 ∙ by Masaki Saito, et al. ∙ 0 ∙ share

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Sampling Techniques for Large-Scale Object Detection from Sparsely Annotated Objects

Efficient and reliable methods for training of object detectors are in h...
11/27/2018 ∙ by Yusuke Niitani, et al. ∙ 0 ∙ share

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Dynamic Manipulation of Flexible Objects with Torque Sequence Using a Deep Neural Network

For dynamic manipulation of flexible objects, we propose an acquisition ...
01/29/2019 ∙ by Kento Kawaharazuka, et al. ∙ 0 ∙ share

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Low-latency job scheduling with preemption for the development of deep learning

One significant challenge in the job scheduling of computing clusters fo...
02/05/2019 ∙ by Hidehito Yabuuchi, et al. ∙ 0 ∙ share

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A Graph Theoretic Framework of Recomputation Algorithms for Memory-Efficient Backpropagation

Recomputation algorithms collectively refer to a family of methods that ...
05/28/2019 ∙ by Mitsuru Kusumoto, et al. ∙ 0 ∙ share

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Robustness to Adversarial Perturbations in Learning from Incomplete Data

What is the role of unlabeled data in an inference problem, when the pre...
05/24/2019 ∙ by Amir Najafi, et al. ∙ 0 ∙ share

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Chainer: A Deep Learning Framework for Accelerating the Research Cycle

Software frameworks for neural networks play a key role in the developme...
08/01/2019 ∙ by Seiya Tokui, et al. ∙ 0 ∙ share

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FDA: Feature Disruptive Attack

Though Deep Neural Networks (DNN) show excellent performance across vari...
09/10/2019 ∙ by Aditya Ganeshan, et al. ∙ 0 ∙ share

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GA-GAN: CT reconstruction from Biplanar DRRs using GAN with Guided Attention

This work investigates the use of guided attention in the reconstruction...
09/27/2019 ∙ by Ashish Sinha, et al. ∙ 0 ∙ share

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Graph Residual Flow for Molecular Graph Generation

Statistical generative models for molecular graphs attract attention fro...
09/30/2019 ∙ by Shion Honda, et al. ∙ 0 ∙ share

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Motion Generation Considering Situation with Conditional Generative Adversarial Networks for Throwing Robots

When robots work in a cluttered environment, the constraints for motions...
10/08/2019 ∙ by Kyo Kutsuzawa, et al. ∙ 0 ∙ share

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Emergent Communication with World Models

We introduce Language World Models, a class of language-conditional gene...
02/22/2020 ∙ by Alexander I. Cowen-Rivers, et al. ∙ 0 ∙ share

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Machine Translation System Selection from Bandit Feedback

Adapting machine translation systems in the real world is a difficult pr...
02/22/2020 ∙ by Jason Naradowsky, et al. ∙ 0 ∙ share

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Visual Task Progress Estimation with Appearance Invariant Embeddings for Robot Control and Planning

To fulfill the vision of full autonomy, robots must be capable of reason...
03/16/2020 ∙ by Guilherme Maeda, et al. ∙ 0 ∙ share

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