Rensselaer Polytechnic Institute

∙ Troy , United States ∙ 0 followers

The institute was established in 1824 by Stephen van Rensselaer and Amos Eaton for the "application of science to the common purposes of life" and is described as the oldest technological university in the English-speaking world.

Towards Visually Explaining Variational Autoencoders

Recent advances in Convolutional Neural Network (CNN) model interpretabi...
11/18/2019 ∙ by Wenqian Liu, et al. ∙ 84 ∙ share

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Chart Auto-Encoders for Manifold Structured Data

Auto-encoding and generative models have made tremendous successes in im...
12/20/2019 ∙ by Stefan Schonsheck, et al. ∙ 31 ∙ share

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Multi-organ Segmentation over Partially Labeled Datasets with Multi-scale Feature Abstraction

This paper presents a unified training strategy that enables a novel mul...
01/01/2020 ∙ by Xi Fang, et al. ∙ 30 ∙ share

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Deep Encoder-decoder Adversarial Reconstruction (DEAR) Network for 3D CT from Few-view Data

X-ray computed tomography (CT) is widely used in clinical practice. The ...
11/13/2019 ∙ by Huidong Xie, et al. ∙ 27 ∙ share

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Deep Efficient End-to-end Reconstruction (DEER) Network for Low-dose Few-view Breast CT from Projection Data

Breast CT provides image volumes with isotropic resolution in high contr...
12/09/2019 ∙ by Huidong Xie, et al. ∙ 22 ∙ share

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Duality of Width and Depth of Neural Networks

Here, we report that the depth and the width of a neural network are dua...
02/06/2020 ∙ by Fenglei-Lei Fan, et al. ∙ 20 ∙ share

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Truth Discovery via Proxy Voting

Truth discovery is a general name for a broad range of statistical metho...
05/02/2019 ∙ by Reshef Meir, et al. ∙ 12 ∙ share

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Can Deep Learning Outperform Modern Commercial CT Image Reconstruction Methods?

Commercial iterative reconstruction techniques on modern CT scanners tar...
11/08/2018 ∙ by Hongming Shan, et al. ∙ 8 ∙ share

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Boundary-weighted Domain Adaptive Neural Network for Prostate MR Image Segmentation

Accurate segmentation of the prostate from magnetic resonance (MR) image...
02/21/2019 ∙ by Qikui Zhu, et al. ∙ 8 ∙ share

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An image-driven machine learning approach to kinetic modeling of a discontinuous precipitation reaction

Micrograph quantification is an essential component of several materials...
06/13/2019 ∙ by Elizabeth Kautz, et al. ∙ 6 ∙ share

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Multi-person Spatial Interaction in a Large Immersive Display Using Smartphones as Touchpads

In this paper, we present a multi-user interaction interface for a large...
11/26/2019 ∙ by Gyanendra Sharma, et al. ∙ 6 ∙ share

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Universal Approximation with Quadratic Deep Networks

Recently, deep learning has been playing a central role in machine learn...
07/31/2018 ∙ by Fenglei Fan, et al. ∙ 4 ∙ share

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Rational Neural Networks for Approximating Jump Discontinuities of Graph Convolution Operator

For node level graph encoding, a recent important state-of-art method is...
08/30/2018 ∙ by Zhiqian Chen, et al. ∙ 4 ∙ share

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Nonisometric Surface Registration via Conformal Laplace-Beltrami Basis Pursuit

Surface registration is one of the most fundamental problems in geometry...
09/19/2018 ∙ by Stefan C. Schonsheck, et al. ∙ 4 ∙ share

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Knowledge-based Analysis for Mortality Prediction from CT Images

Recent studies have highlighted the high correlation between cardiovascu...
02/20/2019 ∙ by Hengtao Guo, et al. ∙ 4 ∙ share

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A Grounded Unsupervised Universal Part-of-Speech Tagger for Low-Resource Languages

Unsupervised part of speech (POS) tagging is often framed as a clusterin...
04/10/2019 ∙ by Ronald Cardenas, et al. ∙ 4 ∙ share

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Dual Network Architecture for Few-view CT --Trained on ImageNet Data and Transferred for Medical Imaging

X-ray computed tomography (CT) reconstructs cross-sectional images from ...
07/02/2019 ∙ by Huidong Xie, et al. ∙ 1 ∙ share

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Communication-Efficient Distributed Learning via Lazily Aggregated Quantized Gradients

The present paper develops a novel aggregated gradient approach for dist...
09/17/2019 ∙ by Jun Sun, et al. ∙ 1 ∙ share

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A Dependency-Based Neural Network for Relation Classification

Previous research on relation classification has verified the effectiven...
07/16/2015 ∙ by Yang Liu, et al. ∙ 0 ∙ share

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Influence of Personal Preferences on Link Dynamics in Social Networks

We study a unique network dataset including periodic surveys and electro...
09/21/2017 ∙ by Ashwin Bahulkar, et al. ∙ 0 ∙ share

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Application of a Shallow Neural Network to Short-Term Stock Trading

Machine learning is increasingly prevalent in stock market trading. Thou...
03/30/2017 ∙ by Abhinav Madahar, et al. ∙ 0 ∙ share

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Towards Cognitive-and-Immersive Systems: Experiments in a Shared (or common) Blockworld Framework

As computational power has continued to increase, and sensors have becom...
09/14/2017 ∙ by Matthew Peveler, et al. ∙ 0 ∙ share

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A Generative Restricted Boltzmann Machine Based Method for High-Dimensional Motion Data Modeling

Many computer vision applications involve modeling complex spatio-tempor...
10/21/2017 ∙ by Siqi Nie, et al. ∙ 0 ∙ share

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From Data to City Indicators: A Knowledge Graph for Supporting Automatic Generation of Dashboards

In the context of Smart Cities, indicator definitions have been used to ...
04/06/2017 ∙ by Henrique Santos, et al. ∙ 0 ∙ share

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Deep Learning for Passive Synthetic Aperture Radar

We introduce a deep learning (DL) framework for inverse problems in imag...
08/12/2017 ∙ by Bariscan Yonel, et al. ∙ 0 ∙ share

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Scalable Kernel K-Means Clustering with Nystrom Approximation: Relative-Error Bounds

Kernel k-means clustering can correctly identify and extract a far more ...
06/09/2017 ∙ by Shusen Wang, et al. ∙ 0 ∙ share

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Low Dose CT Image Denoising Using a Generative Adversarial Network with Wasserstein Distance and Perceptual Loss

In this paper, we introduce a new CT image denoising method based on the...
08/03/2017 ∙ by Qingsong Yang, et al. ∙ 0 ∙ share

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KATE: K-Competitive Autoencoder for Text

Autoencoders have been successful in learning meaningful representations...
05/04/2017 ∙ by Yu Chen, et al. ∙ 0 ∙ share

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Truthful Mechanisms for Matching and Clustering in an Ordinal World

We study truthful mechanisms for matching and related problems in a part...
10/13/2016 ∙ by Elliot Anshelevich, et al. ∙ 0 ∙ share

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Census Signal Temporal Logic Inference for Multi-Agent Group Behavior Analysis

In this paper, we define a novel census signal temporal logic (CensusSTL...
10/05/2016 ∙ by Zhe Xu, et al. ∙ 0 ∙ share

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Rank Persistence: Assessing the Temporal Performance of Real-World Person Re-Identification

Designing useful person re-identification systems for real-world applica...
06/02/2017 ∙ by Srikrishna Karanam, et al. ∙ 0 ∙ share

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Accelerated Primal-Dual Proximal Block Coordinate Updating Methods for Constrained Convex Optimization

Block Coordinate Update (BCU) methods enjoy low per-update computational...
02/17/2017 ∙ by Yangyang Xu, et al. ∙ 0 ∙ share

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Sketched Ridge Regression: Optimization Perspective, Statistical Perspective, and Model Averaging

We address the statistical and optimization impacts of using classical s...
02/16/2017 ∙ by Shusen Wang, et al. ∙ 0 ∙ share

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CrossNets : A New Approach to Complex Learning

We propose a novel neural network structure called CrossNets, which cons...
05/21/2017 ∙ by Chirag Agarwal, et al. ∙ 0 ∙ share

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Building a Fine-Grained Entity Typing System Overnight for a New X (X = Language, Domain, Genre)

Recent research has shown great progress on fine-grained entity typing. ...
03/10/2016 ∙ by Lifu Huang, et al. ∙ 0 ∙ share

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Randomized Social Choice Functions Under Metric Preferences

We determine the quality of randomized social choice mechanisms in a set...
12/23/2015 ∙ by Elliot Anshelevich, et al. ∙ 0 ∙ share

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Hybrid Jacobian and Gauss-Seidel proximal block coordinate update methods for linearly constrained convex programming

Recent years have witnessed the rapid development of block coordinate up...
08/13/2016 ∙ by Yangyang Xu, et al. ∙ 0 ∙ share

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Manifold Based Low-rank Regularization for Image Restoration and Semi-supervised Learning

Low-rank structures play important role in recent advances of many probl...
02/09/2017 ∙ by Rongjie Lai, et al. ∙ 0 ∙ share

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Allocating Indivisible Items in Categorized Domains

We formulate a general class of allocation problems called categorized d...
04/22/2015 ∙ by Erika Mackin, et al. ∙ 0 ∙ share

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Optimal Sparse Linear Auto-Encoders and Sparse PCA

Principal components analysis (PCA) is the optimal linear auto-encoder o...
02/23/2015 ∙ by Malik Magdon-Ismail, et al. ∙ 0 ∙ share

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Possible and Necessary Allocations via Sequential Mechanisms

A simple mechanism for allocating indivisible resources is sequential al...
12/06/2014 ∙ by Haris Aziz, et al. ∙ 0 ∙ share

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A Statistical Decision-Theoretic Framework for Social Choice

In this paper, we take a statistical decision-theoretic viewpoint on soc...
10/29/2014 ∙ by Hossein Azari Soufiani, et al. ∙ 0 ∙ share

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Advances in Learning Bayesian Networks of Bounded Treewidth

This work presents novel algorithms for learning Bayesian network struct...
06/05/2014 ∙ by Siqi Nie, et al. ∙ 0 ∙ share

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A Randomized Rounding Algorithm for Sparse PCA

We present and analyze a simple, two-step algorithm to approximate the o...
08/13/2015 ∙ by Kimon Fountoulakis, et al. ∙ 0 ∙ share

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Feature Selection for Ridge Regression with Provable Guarantees

We introduce single-set spectral sparsification as a deterministic sampl...
06/17/2015 ∙ by Saurabh Paul, et al. ∙ 0 ∙ share

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Sketching for Sequential Change-Point Detection

We study sequential change-point detection using sketches (linear projec...
05/25/2015 ∙ by Yang Cao, et al. ∙ 0 ∙ share

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A Systematic Evaluation and Benchmark for Person Re-Identification: Features, Metrics, and Datasets

Person re-identification (re-id) is a critical problem in video analytic...
05/31/2016 ∙ by Srikrishna Karanam, et al. ∙ 0 ∙ share

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Approximating Sparse PCA from Incomplete Data

We study how well one can recover sparse principal components of a data ...
03/12/2015 ∙ by Abhisek Kundu, et al. ∙ 0 ∙ share

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Recovering PCA from Hybrid-(ℓ_1,ℓ_2) Sparse Sampling of Data Elements

This paper addresses how well we can recover a data matrix when only giv...
03/02/2015 ∙ by Abhisek Kundu, et al. ∙ 0 ∙ share

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NP-Hardness and Inapproximability of Sparse PCA

We give a reduction from clique to establish that sparse PCA is NP-hard...
02/19/2015 ∙ by Malik Magdon-Ismail, et al. ∙ 0 ∙ share

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