Rutgers University

∙ New Brunswick , United States ∙ 0 followers

Rutgers, The State University of New Jersey, commonly referred to as Rutgers University, Rutgers, or RU, is a public research university in New Jersey.

Anomaly Detection with Density Estimation

We leverage recent breakthroughs in neural density estimation to propose...
01/14/2020 ∙ by Benjamin Nachman, et al. ∙ 94 ∙ share

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Embedding Compression with Isotropic Iterative Quantization

Continuous representation of words is a standard component in deep learn...
01/11/2020 ∙ by Siyu Liao, et al. ∙ 36 ∙ share

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CookGAN: Meal Image Synthesis from Ingredients

In this work we propose a new computational framework, based on generati...
02/25/2020 ∙ by Fangda Han, et al. ∙ 35 ∙ share

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Deep Cooking: Predicting Relative Food Ingredient Amounts from Images

In this paper, we study the novel problem of not only predicting ingredi...
09/26/2019 ∙ by Jiatong Li, et al. ∙ 34 ∙ share

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Point Cloud Processing via Recurrent Set Encoding

We present a new permutation-invariant network for 3D point cloud proces...
11/25/2019 ∙ by Pengxiang Wu, et al. ∙ 34 ∙ share

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Learning a Self-inverse Network for Unpaired Bidirectional Image-to-image Translation

Recently image-to-image translation has attracted significant interests ...
09/09/2019 ∙ by Zengming Shen, et al. ∙ 33 ∙ share

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Deep Sparse Representation-based Classification

We present a transductive deep learning-based formulation for the sparse...
04/24/2019 ∙ by Mahdi Abavisani, et al. ∙ 22 ∙ share

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Object-Guided Instance Segmentation for Biological Images

Instance segmentation of biological images is essential for studying obj...
11/20/2019 ∙ by Jingru Yi, et al. ∙ 21 ∙ share

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Learning Feature-to-Feature Translator by Alternating Back-Propagation for Zero-Shot Learning

We investigate learning feature-to-feature translator networks by altern...
04/22/2019 ∙ by Yizhe Zhu, et al. ∙ 18 ∙ share

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Towards Learning a Self-inverse Network for Bidirectional Image-to-image Translation

The one-to-one mapping is necessary for many bidirectional image-to-imag...
09/09/2019 ∙ by Zengming Shen, et al. ∙ 18 ∙ share

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Accelerating the Computation of UCB and Related Indices for Reinforcement Learning

In this paper we derive an efficient method for computing the indices as...
09/28/2019 ∙ by Wesley Cowan, et al. ∙ 17 ∙ share

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Scaling-up Distributed Processing of Data Streams for Machine Learning

Emerging applications of machine learning in numerous areas involve cont...
05/18/2020 ∙ by Matthew Nokleby, et al. ∙ 16 ∙ share

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Learning to Segment Brain Anatomy from 2D Ultrasound with Less Data

Automatic segmentation of anatomical landmarks from ultrasound (US) play...
12/18/2019 ∙ by Jeya Maria Jose V., et al. ∙ 15 ∙ share

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ViewSynth: Learning Local Features from Depth using View Synthesis

We address the problem of jointly detecting keypoints and learning descr...
11/22/2019 ∙ by Jisan Mahmud, et al. ∙ 14 ∙ share

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MotionNet: Joint Perception and Motion Prediction for Autonomous Driving Based on Bird's Eye View Maps

The ability to reliably perceive the environmental states, particularly ...
03/15/2020 ∙ by Pengxiang Wu, et al. ∙ 13 ∙ share

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ASSD: Attentive Single Shot Multibox Detector

This paper proposes a new deep neural network for object detection. The ...
09/27/2019 ∙ by Jingru Yi, et al. ∙ 12 ∙ share

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CAG: A Real-time Low-cost Enhanced-robustness High-transferability Content-aware Adversarial Attack Generator

Deep neural networks (DNNs) are vulnerable to adversarial attack despite...
12/16/2019 ∙ by Huy Phan, et al. ∙ 11 ∙ share

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Machine Learning for Motor Learning: EEG-based Continuous Assessment of Cognitive Engagement for Adaptive Rehabilitation Robots

Although cognitive engagement (CE) is crucial for motor learning, it rem...
02/18/2020 ∙ by Neelesh Kumar, et al. ∙ 11 ∙ share

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Are Emojis Emotional? A Study to Understand the Association between Emojis and Emotions

Given the growing ubiquity of emojis in language, there is a need for me...
05/02/2020 ∙ by Abu Shoeb, et al. ∙ 11 ∙ share

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Simulation Assisted Likelihood-free Anomaly Detection

Given the lack of evidence for new particle discoveries at the Large Had...
01/14/2020 ∙ by Anders Andreassen, et al. ∙ 10 ∙ share

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Synthesis of High-Quality Visible Faces from Polarimetric Thermal Faces using Generative Adversarial Networks

The large domain discrepancy between faces captured in polarimetric (or ...
12/12/2018 ∙ by He Zhang, et al. ∙ 8 ∙ share

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Visibility Constrained Generative Model for Depth-based 3D Facial Pose Tracking

In this paper, we propose a generative framework that unifies depth-base...
05/06/2019 ∙ by Lu Sheng, et al. ∙ 7 ∙ share

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Imbalance-XGBoost: Leveraging Weighted and Focal Losses for Binary Label-Imbalanced Classification with XGBoost

The paper presents Imbalance-XGBoost, a Python package that combines the...
08/05/2019 ∙ by Chen Wang, et al. ∙ 7 ∙ share

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Rethinking Kernel Methods for Node Representation Learning on Graphs

Graph kernels are kernel methods measuring graph similarity and serve as...
10/06/2019 ∙ by Yu Tian, et al. ∙ 7 ∙ share

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Neural Multisensory Scene Inference

For embodied agents to infer representations of the underlying 3D physic...
10/06/2019 ∙ by Jae Hyun Lim, et al. ∙ 7 ∙ share

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Scene-level Pose Estimation for Multiple Instances of Densely Packed Objects

This paper introduces key machine learning operations that allow the rea...
10/11/2019 ∙ by Chaitanya Mitash, et al. ∙ 7 ∙ share

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Stable Matrix Completion using Properly Configured Kronecker Product Decomposition

Matrix completion problems are the problems of recovering missing entrie...
11/26/2019 ∙ by Chencheng Cai, et al. ∙ 7 ∙ share

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Disconnected Manifold Learning for Generative Adversarial Networks

Real images often lie on a union of disjoint manifolds rather than one g...
06/03/2018 ∙ by Mahyar Khayatkhoei, et al. ∙ 6 ∙ share

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Polarimetric Thermal to Visible Face Verification via Attribute Preserved Synthesis

Thermal to visible face verification is a challenging problem due to the...
01/03/2019 ∙ by Xing Di, et al. ∙ 6 ∙ share

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Learning where to look: Semantic-Guided Multi-Attention Localization for Zero-Shot Learning

Zero-shot learning extends the conventional object classification to the...
03/01/2019 ∙ by Yizhe Zhu, et al. ∙ 6 ∙ share

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Deep Transfer Learning for Multiple Class Novelty Detection

We propose a transfer learning-based solution for the problem of multipl...
03/06/2019 ∙ by Pramuditha Perera, et al. ∙ 6 ∙ share

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Semantic Graph Convolutional Networks for 3D Human Pose Regression

In this paper, we study the problem of learning Graph Convolutional Netw...
04/06/2019 ∙ by Long Zhao, et al. ∙ 6 ∙ share

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Generating Animations from Screenplays

Automatically generating animation from natural language text finds appl...
04/10/2019 ∙ by Yeyao Zhang, et al. ∙ 6 ∙ share

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Unsupervised Visual Domain Adaptation: A Deep Max-Margin Gaussian Process Approach

In unsupervised domain adaptation, it is widely known that the target do...
02/23/2019 ∙ by Minyoung Kim, et al. ∙ 5 ∙ share

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Efficient Deep Gaussian Process Models for Variable-Sized Input

Deep Gaussian processes (DGP) have appealing Bayesian properties, can ha...
05/16/2019 ∙ by Issam H. Laradji, et al. ∙ 5 ∙ share

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BRIDGE: Byzantine-resilient Decentralized Gradient Descent

Decentralized optimization techniques are increasingly being used to lea...
08/21/2019 ∙ by Zhixiong Yang, et al. ∙ 5 ∙ share

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Fractional Underdamped Langevin Dynamics: Retargeting SGD with Momentum under Heavy-Tailed Gradient Noise

Stochastic gradient descent with momentum (SGDm) is one of the most popu...
02/13/2020 ∙ by Umut Şimşekli, et al. ∙ 5 ∙ share

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Approximation Algorithms for Multi-Robot Patrol-Scheduling with Min-Max Latency

We consider the problem of finding patrol schedules for k robots to visi...
05/05/2020 ∙ by Peyman Afshani, et al. ∙ 5 ∙ share

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Learning to Forecast and Refine Residual Motion for Image-to-Video Generation

We consider the problem of image-to-video translation, where an input im...
07/26/2018 ∙ by Long Zhao, et al. ∙ 4 ∙ share

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Learning Mixtures of Separable Dictionaries for Tensor Data: Analysis and Algorithms

This work addresses the problem of learning sparse representations of te...
03/22/2019 ∙ by Mohsen Ghassemi, et al. ∙ 4 ∙ share

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Learning-Aided Physical Layer Attacks Against Multicarrier Communications in IoT

Internet-of-Things (IoT) devices that are limited in power and processin...
08/01/2019 ∙ by Alireza Nooraiepour, et al. ∙ 4 ∙ share

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Learning End-to-End Codes for the BPSK-constrained Gaussian Wiretap Channel

Finite-length codes are learned for the Gaussian wiretap channel in an e...
03/23/2020 ∙ by Alireza Nooraiepour, et al. ∙ 4 ∙ share

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Learning to Learn Single Domain Generalization

We are concerned with a worst-case scenario in model generalization, in ...
03/30/2020 ∙ by Fengchun Qiao, et al. ∙ 4 ∙ share

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Jointly Optimize Data Augmentation and Network Training: Adversarial Data Augmentation in Human Pose Estimation

Random data augmentation is a critical technique to avoid overfitting in...
05/24/2018 ∙ by Xi Peng, et al. ∙ 2 ∙ share

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Effective 3D Humerus and Scapula Extraction using Low-contrast and High-shape-variability MR Data

For the initial shoulder preoperative diagnosis, it is essential to obta...
02/22/2019 ∙ by Xiaoxiao He, et al. ∙ 2 ∙ share

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Unsupervised Domain Adaptation with Copula Models

We study the task of unsupervised domain adaptation, where no labeled da...
09/29/2017 ∙ by Cuong D. Tran, et al. ∙ 1 ∙ share

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Sketch-based Face Editing in Video Using Identity Deformation Transfer

We address the problem of using hand-drawn sketch to edit facial identit...
03/25/2017 ∙ by Long Zhao, et al. ∙ 1 ∙ share

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Intrinsic Non-stationary Covariance Function for Climate Modeling

Designing a covariance function that represents the underlying correlati...
07/09/2015 ∙ by Chintan A. Dalal, et al. ∙ 1 ∙ share

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D-MFVI: Distributed Mean Field Variational Inference using Bregman ADMM

Bayesian models provide a framework for probabilistic modelling of compl...
07/03/2015 ∙ by Behnam Babagholami-Mohamadabadi, et al. ∙ 1 ∙ share

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Gaussian Process for Noisy Inputs with Ordering Constraints

We study the Gaussian Process regression model in the context of trainin...
06/30/2015 ∙ by Cuong Tran, et al. ∙ 1 ∙ share

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