
InformationGeometric Set Embeddings (IGSE): From Sets to Probability Distributions
This letter introduces an abstract learning problem called the “set embe...
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HighResolution Representations for Labeling Pixels and Regions
Highresolution representation learning plays an essential role in many ...
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On The Chain Rule Optimal Transport Distance
We define a novel class of distances between statistical multivariate di...
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Lightlike Neuromanifolds, Occam's Razor and Deep Learning
Why do deep neural networks generalize with a very high dimensional para...
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qNeurons: Neuron Activations based on Stochastic Jackson's Derivative Operators
We propose a new generic type of stochastic neurons, called qneurons, t...
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Human Pose Estimation using Global and Local Normalization
In this paper, we address the problem of estimating the positions of hum...
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Clustering in Hilbert simplex geometry
Clustering categorical distributions in the probability simplex is a fun...
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Guaranteed bounds on the KullbackLeibler divergence of univariate mixtures using piecewise logsumexp inequalities
Informationtheoretic measures such as the entropy, crossentropy and th...
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On Hölder projective divergences
We describe a framework to build distances by measuring the tightness of...
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Deep Feature Consistent Variational Autoencoder
We present a novel method for constructing Variational Autoencoder (VAE)...
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Automatic Visual Theme Discovery from Joint Image and Text Corpora
A popular approach to semantic image understanding is to manually tag im...
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Object Specific Deep Learning Feature and Its Application to Face Detection
We present a method for discovering and exploiting object specific deep ...
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TwoStage Metric Learning
In this paper, we present a novel twostage metric learning algorithm. W...
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Robust Stereo Visual Inertial Odometry for Fast Autonomous Flight
In recent years, visionaided inertial odometry for state estimation has...
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Fast, Autonomous Flight in GPSDenied and Cluttered Environments
One of the most challenging tasks for a flying robot is to autonomously ...
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L_pNorm Constrained Coding With FrankWolfe Network
We investigate the problem of L_pnorm constrained coding, i.e. converti...
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Dense 3D Mapping with Spatial Correlation via Gaussian Filtering
Constructing an occupancy representation of the environment is a fundame...
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IGCV3: Interleaved LowRank Group Convolutions for Efficient Deep Neural Networks
In this paper, we are interested in building lightweight and efficient c...
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Guaranteed Deterministic Bounds on the Total Variation Distance between Univariate Mixtures
The total variation distance is a core statistical distance between prob...
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Chinese Lexical Analysis with Deep BiGRUCRF Network
Lexical analysis is believed to be a crucial step towards natural langua...
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Experiments in Fast, Autonomous, GPSDenied Quadrotor Flight
High speed navigation through unknown environments is a challenging prob...
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Stealth Attacks on the Smart Grid
Random attacks that jointly minimize the amount of information acquired ...
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The Open Vision Computer: An Integrated Sensing and Compute System for Mobile Robots
In this paper we describe the Open Vision Computer (OVC) which was desig...
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Intrinsic Universal Measurements of Nonlinear Embeddings
A basic problem in machine learning is to find a mapping f from a low di...
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Stochastic 2D Motion Planning with a POMDP Framework
Motion planning is challenging when it comes to the case of imperfect st...
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Relative GeometryAware Siamese Neural Network for 6DOF Camera Relocalization
6DOF camera relocalization is an important component of autonomous drivi...
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Deep HighResolution Representation Learning for Human Pose Estimation
This is an official pytorch implementation of Deep HighResolution Repre...
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Virtual Adversarial Training on Graph Convolutional Networks in Node Classification
The effectiveness of Graph Convolutional Networks (GCNs) has been demons...
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MultiStage SelfSupervised Learning for Graph Convolutional Networks
Graph Convolutional Networks(GCNs) play a crucial role in graph learning...
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Enhancing the Robustness of Deep Neural Networks by Boundary Conditional GAN
Deep neural networks have been widely deployed in various machine learni...
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Towards Understanding Adversarial Examples Systematically: Exploring Data Size, Task and Model Factors
Most previous works usually explained adversarial examples from several ...
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FisherBures Adversary Graph Convolutional Networks
In a graph convolutional network, we assume that the graph G is generate...
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Learning requirements for stealth attacks
The learning data requirements are analyzed for the construction of stea...
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Experimental Quantumenhanced Cryptographic Remote Control
The Internet of Things (IoT), as a cuttingedge integrated crosstechnol...
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Learning Deep Image Priors for Blind Image Denoising
Image denoising is the process of removing noise from noisy images, whic...
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Improving Variational Autoencoder with Deep Feature Consistent and Generative Adversarial Training
We present a new method for improving the performances of variational au...
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AdaGCN: Adaboosting Graph Convolutional Networks into Deep Models
The design of deep graph models still remains to be investigated and the...
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Deep HighResolution Representation Learning for Visual Recognition
Highresolution representations are essential for positionsensitive vis...
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A Note on Our Submission to Track 4 of iDASH 2019
iDASH is a competition soliciting implementations of cryptographic schem...
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Patchlevel Neighborhood Interpolation: A General and Effective Graphbased Regularization Strategy
Regularization plays a crucial role in machine learning models, especial...
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Seq2seq Translation Model for Sequential Recommendation
The context information such as product category plays a critical role i...
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Ke Sun
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patent scientist at Duane Morris LLP since 2017, Postdoc fellow at Caltech from 20132017, PhD Nanoelectronics and nanomaterials at University of California San Diego 20092013.