
PartiallyShared Variational Autoencoders for Unsupervised Domain Adaptation with Target Shift
This paper proposes a novel approach for unsupervised domain adaptation ...
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When Person Reidentification Meets Changing Clothes
Person reidentification (Reid) is now an active research topic for AIb...
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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...
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Automatically Neutralizing Subjective Bias in Text
Texts like news, encyclopedias, and some social media strive for objecti...
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GraphLIME: Local Interpretable Model Explanations for Graph Neural Networks
Graph structured data has wide applicability in various domains such as ...
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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...
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Learning subtree pattern importance for WeisfeilerLehmanbased graph kernels
Graph is an usual representation of relational data, which are ubiquitou...
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Topological Bayesian Optimization with Persistence Diagrams
Finding an optimal parameter of a blackbox function is important for se...
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Unsupervised Speech Enhancement Based on Multichannel NMFInformed Beamforming for NoiseRobust Automatic Speech Recognition
This paper describes multichannel speech enhancement for improving autom...
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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...
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Universal consistency of the kNN rule in metric spaces and Nagata dimension
The k nearest neighbour learning rule (under the uniform distance tie br...
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Shape from Water Reflection
This paper introduces singleimage 3D scene reconstruction from water re...
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Stochastic Neighbor Embedding of Multimodal Relational Data for ImageText Simultaneous Visualization
Multimodal relational data analysis has become of increasing importance ...
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Semisupervised learning of hierarchical representations of molecules using neural message passing
With the rapid increase of compound databases available in medicinal and...
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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...
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Deep Learning Assisted Heuristic Tree Search for the Container Premarshalling Problem
One of the key challenges for operations researchers solving realworld ...
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LargeScale Optimal Transport and Mapping Estimation
This paper presents a novel twostep approach for the fundamental proble...
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Efficient Diverse Ensemble for Discriminative CoTracking
Ensemble discriminative tracking utilizes a committee of classifiers, to...
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Using Posters to Recommend Anime and Mangas in a ColdStart Scenario
Item coldstart is a classical issue in recommender systems that affects...
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Happy Travelers Take Big Pictures: A Psychological Study with Machine Learning and Big Data
In psychology, theorydriven researches are usually conducted with exten...
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Rhythm Transcription of Polyphonic Piano Music Based on MergedOutput HMM for Multiple Voices
In a recent conference paper, we have reported a rhythm transcription me...
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A Bayesian encourages dropout
Dropout is one of the key techniques to prevent the learning from overfi...
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Convex Coupled Matrix and Tensor Completion
We propose a set of convex low rank inducing norms for a coupled matrice...
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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...
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Efficient VersionSpace Reduction for Visual Tracking
Discrminative trackers, employ a classification approach to separate the...
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Efficient Asymmetric CoTracking using Uncertainty Sampling
Adaptive trackingbydetection approaches are popular for tracking arbit...
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GPflow: A Gaussian process library using TensorFlow
GPflow is a Gaussian process library that uses TensorFlow for its core c...
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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...
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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...
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Localized Lasso for HighDimensional Regression
We introduce the localized Lasso, which is suited for learning models th...
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Collaborative Representation for Classification, Sparse or Nonsparse?
Sparse representation based classification (SRC) has been proved to be a...
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Design of a GISbased Assistant Software Agent for the Incident Commander to Coordinate Emergency Response Operations
Problem: This paper addresses the design of an intelligent software syst...
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Stochastic gradient method with accelerated stochastic dynamics
In this paper, we propose a novel technique to implement stochastic grad...
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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 ...
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Bayesian Masking: Sparse Bayesian Estimation with Weaker Shrinkage Bias
A common strategy for sparse linear regression is to introduce regulariz...
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Wasserstein Training of Boltzmann Machines
The Boltzmann machine provides a useful framework to learn highly comple...
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Distributional Smoothing with Virtual Adversarial Training
We propose local distributional smoothness (LDS), a new notion of smooth...
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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...
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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 ...
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Deep learning of fMRI big data: a novel approach to subjecttransfer decoding
As a technology to read brain states from measurable brain activities, b...
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Principal Sensitivity Analysis
We present a novel algorithm (Principal Sensitivity Analysis; PSA) to an...
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How Does the LowRank Matrix Decomposition Help Internal and External Learnings for SuperResolution
Wisely utilizing the internal and external learning methods is a new cha...
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Detection of cheating by decimation algorithm
We expand the item response theory to study the case of "cheating studen...
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Sparse Learning over Infinite Subgraph Features
We present a supervisedlearning algorithm from graph data (a set of gra...
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Sinkhorn Distances: Lightspeed Computation of Optimal Transportation Distances
Optimal transportation distances are a fundamental family of parameteriz...
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Positivity and Transportation
We prove in this paper that the weighted volume of the set of integral t...
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Ground Metric Learning
Transportation distances have been used for more than a decade now in ma...
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VC dimension of ellipsoids
We will establish that the VC dimension of the class of ddimensional el...
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Learning Valuation Functions
In this paper we study the approximate learnability of valuations common...
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Autoregressive Kernels For Time Series
We propose in this work a new family of kernels for variablelength time...
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Kyoto University
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.