Kyoto University

∙ Kyōto-shi , Japan ∙ 0 followers

Kyoto University Hospital, by analyzing the cancer genetic analysis of cancer patients, examining the best anticancer drugs for patients with cancer, is called “OncoPrime” ” will start in April.

Partially-Shared Variational Auto-encoders for Unsupervised Domain Adaptation with Target Shift

This paper proposes a novel approach for unsupervised domain adaptation ...
01/22/2020 ∙ by Ryuhei Takahashi, et al. ∙ 83 ∙ share

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When Person Re-identification Meets Changing Clothes

Person re-identification (Reid) is now an active research topic for AI-b...
03/09/2020 ∙ by Fangbin Wan, et al. ∙ 33 ∙ share

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Transformer Dissection: An Unified Understanding for Transformer's Attention via the Lens of Kernel

Transformer is a powerful architecture that achieves superior performanc...
08/30/2019 ∙ by Yao-Hung Hubert Tsai, et al. ∙ 32 ∙ share

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Automatically Neutralizing Subjective Bias in Text

Texts like news, encyclopedias, and some social media strive for objecti...
11/21/2019 ∙ by Reid Pryzant, et al. ∙ 26 ∙ share

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GraphLIME: Local Interpretable Model Explanations for Graph Neural Networks

Graph structured data has wide applicability in various domains such as ...
01/17/2020 ∙ by Qiang Huang, et al. ∙ 22 ∙ share

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An Entropic Optimal Transport Loss for Learning Deep Neural Networks under Label Noise in Remote Sensing Images

Deep neural networks have established as a powerful tool for large scale...
10/02/2018 ∙ by Bharath Bhushan Damodaran, et al. ∙ 12 ∙ share

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Learning subtree pattern importance for Weisfeiler-Lehmanbased graph kernels

Graph is an usual representation of relational data, which are ubiquitou...
06/08/2021 ∙ by Dai Hai Nguyen, et al. ∙ 12 ∙ share

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Topological Bayesian Optimization with Persistence Diagrams

Finding an optimal parameter of a black-box function is important for se...
02/26/2019 ∙ by Tatsuya Shiraishi, et al. ∙ 10 ∙ share

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Unsupervised Speech Enhancement Based on Multichannel NMF-Informed Beamforming for Noise-Robust Automatic Speech Recognition

This paper describes multichannel speech enhancement for improving autom...
03/22/2019 ∙ by Kazuki Shimada, et al. ∙ 10 ∙ share

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Learning to Find Hard Instances of Graph Problems

Finding hard instances, which need a long time to solve, of graph proble...
02/26/2019 ∙ by Ryoma Sato, et al. ∙ 8 ∙ share

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Universal consistency of the k-NN rule in metric spaces and Nagata dimension

The k nearest neighbour learning rule (under the uniform distance tie br...
02/28/2020 ∙ by Benoît Collins, et al. ∙ 4 ∙ share

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Shape from Water Reflection

This paper introduces single-image 3D scene reconstruction from water re...
06/25/2019 ∙ by Ryo Kawahara, et al. ∙ 3 ∙ share

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Stochastic Neighbor Embedding of Multimodal Relational Data for Image-Text Simultaneous Visualization

Multimodal relational data analysis has become of increasing importance ...
05/02/2020 ∙ by Morihiro Mizutani, et al. ∙ 2 ∙ 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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Deformation estimation of an elastic object by partial observation using a neural network

Deformation estimation of elastic object assuming an internal organ is i...
11/28/2017 ∙ by Utako Yamamoto, et al. ∙ 0 ∙ share

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Deep Learning Assisted Heuristic Tree Search for the Container Pre-marshalling Problem

One of the key challenges for operations researchers solving real-world ...
09/28/2017 ∙ by André Hottung, et al. ∙ 0 ∙ share

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Large-Scale Optimal Transport and Mapping Estimation

This paper presents a novel two-step approach for the fundamental proble...
11/07/2017 ∙ by Vivien Seguy, et al. ∙ 0 ∙ share

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Efficient Diverse Ensemble for Discriminative Co-Tracking

Ensemble discriminative tracking utilizes a committee of classifiers, to...
11/16/2017 ∙ by Kourosh Meshgi, et al. ∙ 0 ∙ share

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Using Posters to Recommend Anime and Mangas in a Cold-Start Scenario

Item cold-start is a classical issue in recommender systems that affects...
09/03/2017 ∙ by Jill-Jênn Vie, et al. ∙ 0 ∙ share

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Happy Travelers Take Big Pictures: A Psychological Study with Machine Learning and Big Data

In psychology, theory-driven researches are usually conducted with exten...
09/22/2017 ∙ by Xuefeng Liang, et al. ∙ 0 ∙ share

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Rhythm Transcription of Polyphonic Piano Music Based on Merged-Output HMM for Multiple Voices

In a recent conference paper, we have reported a rhythm transcription me...
01/29/2017 ∙ by Eita Nakamura, et al. ∙ 0 ∙ share

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A Bayesian encourages dropout

Dropout is one of the key techniques to prevent the learning from overfi...
12/22/2014 ∙ by Shin-ichi Maeda, et al. ∙ 0 ∙ share

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Convex Coupled Matrix and Tensor Completion

We propose a set of convex low rank inducing norms for a coupled matrice...
05/15/2017 ∙ by Kishan Wimalawarne, et al. ∙ 0 ∙ share

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Paraiso : An Automated Tuning Framework for Explicit Solvers of Partial Differential Equations

We propose Paraiso, a domain specific language embedded in functional pr...
04/21/2012 ∙ by Takayuki Muranushi, et al. ∙ 0 ∙ share

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Efficient Version-Space Reduction for Visual Tracking

Discrminative trackers, employ a classification approach to separate the...
04/02/2017 ∙ by Kourosh Meshgi, et al. ∙ 0 ∙ share

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Efficient Asymmetric Co-Tracking using Uncertainty Sampling

Adaptive tracking-by-detection approaches are popular for tracking arbit...
03/31/2017 ∙ by Kourosh Meshgi, et al. ∙ 0 ∙ share

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GPflow: A Gaussian process library using TensorFlow

GPflow is a Gaussian process library that uses TensorFlow for its core c...
10/27/2016 ∙ by Alexander G. de G. Matthews, et al. ∙ 0 ∙ share

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A Linear Extrinsic Calibration of Kaleidoscopic Imaging System from Single 3D Point

This paper proposes a new extrinsic calibration of kaleidoscopic imaging...
03/08/2017 ∙ by Kosuke Takahashi, et al. ∙ 0 ∙ share

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Panoptic Studio: A Massively Multiview System for Social Interaction Capture

We present an approach to capture the 3D motion of a group of people eng...
12/09/2016 ∙ by Hanbyul Joo, et al. ∙ 0 ∙ share

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Localized Lasso for High-Dimensional Regression

We introduce the localized Lasso, which is suited for learning models th...
03/22/2016 ∙ by Makoto Yamada, et al. ∙ 0 ∙ share

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Collaborative Representation for Classification, Sparse or Non-sparse?

Sparse representation based classification (SRC) has been proved to be a...
03/06/2014 ∙ by Yang Wu, et al. ∙ 0 ∙ share

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Design of a GIS-based Assistant Software Agent for the Incident Commander to Coordinate Emergency Response Operations

Problem: This paper addresses the design of an intelligent software syst...
01/01/2014 ∙ by Reza Nourjou, et al. ∙ 0 ∙ share

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Stochastic gradient method with accelerated stochastic dynamics

In this paper, we propose a novel technique to implement stochastic grad...
11/19/2015 ∙ by Masayuki Ohzeki, et al. ∙ 0 ∙ share

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On Wasserstein Two Sample Testing and Related Families of Nonparametric Tests

Nonparametric two sample or homogeneity testing is a decision theoretic ...
09/08/2015 ∙ by Aaditya Ramdas, et al. ∙ 0 ∙ share

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Bayesian Masking: Sparse Bayesian Estimation with Weaker Shrinkage Bias

A common strategy for sparse linear regression is to introduce regulariz...
09/03/2015 ∙ by Yohei Kondo, et al. ∙ 0 ∙ share

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Wasserstein Training of Boltzmann Machines

The Boltzmann machine provides a useful framework to learn highly comple...
07/07/2015 ∙ by Grégoire Montavon, et al. ∙ 0 ∙ share

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Distributional Smoothing with Virtual Adversarial Training

We propose local distributional smoothness (LDS), a new notion of smooth...
07/02/2015 ∙ by Takeru Miyato, et al. ∙ 0 ∙ share

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Principal Geodesic Analysis for Probability Measures under the Optimal Transport Metric

Given a family of probability measures in P(X), the space of probability...
06/26/2015 ∙ by Vivien Seguy, et al. ∙ 0 ∙ share

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Mathematical understanding of detailed balance condition violation and its application to Langevin dynamics

We develop an efficient sampling method by simulating Langevin dynamics ...
03/09/2015 ∙ by M. Ohzeki, et al. ∙ 0 ∙ share

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Deep learning of fMRI big data: a novel approach to subject-transfer decoding

As a technology to read brain states from measurable brain activities, b...
01/31/2015 ∙ by Sotetsu Koyamada, et al. ∙ 0 ∙ share

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Principal Sensitivity Analysis

We present a novel algorithm (Principal Sensitivity Analysis; PSA) to an...
12/21/2014 ∙ by Sotetsu Koyamada, et al. ∙ 0 ∙ share

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How Does the Low-Rank Matrix Decomposition Help Internal and External Learnings for Super-Resolution

Wisely utilizing the internal and external learning methods is a new cha...
04/06/2016 ∙ by Shuang Wang, et al. ∙ 0 ∙ share

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Detection of cheating by decimation algorithm

We expand the item response theory to study the case of "cheating studen...
10/14/2014 ∙ by Shogo Yamanaka, et al. ∙ 0 ∙ share

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Sparse Learning over Infinite Subgraph Features

We present a supervised-learning algorithm from graph data (a set of gra...
03/20/2014 ∙ by Ichigaku Takigawa, et al. ∙ 0 ∙ share

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Sinkhorn Distances: Lightspeed Computation of Optimal Transportation Distances

Optimal transportation distances are a fundamental family of parameteriz...
06/04/2013 ∙ by Marco Cuturi, et al. ∙ 0 ∙ share

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Positivity and Transportation

We prove in this paper that the weighted volume of the set of integral t...
09/12/2012 ∙ by Marco Cuturi, et al. ∙ 0 ∙ share

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Ground Metric Learning

Transportation distances have been used for more than a decade now in ma...
10/11/2011 ∙ by Marco Cuturi, et al. ∙ 0 ∙ share

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VC dimension of ellipsoids

We will establish that the VC dimension of the class of d-dimensional el...
09/20/2011 ∙ by Yohji Akama, et al. ∙ 0 ∙ share

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Learning Valuation Functions

In this paper we study the approximate learnability of valuations common...
08/29/2011 ∙ by Maria-Florina Balcan, et al. ∙ 0 ∙ share

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Autoregressive Kernels For Time Series

We propose in this work a new family of kernels for variable-length time...
01/04/2011 ∙ by Marco Cuturi, et al. ∙ 0 ∙ share

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