UMass Lowell

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UMass Lowell is a national research university that helps students get ready for work, for life and for all the world offers.

CLVSA: A Convolutional LSTM Based Variational Sequence-to-Sequence Model with Attention for Predicting Trends of Financial Markets

Financial markets are a complex dynamical system. The complexity comes f...
04/08/2021 ∙ by Jia Wang, et al. ∙ 18 ∙ share

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What's in a Name? Reducing Bias in Bios without Access to Protected Attributes

There is a growing body of work that proposes methods for mitigating bia...
04/10/2019 ∙ by Alexey Romanov, et al. ∙ 12 ∙ share

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Retinopathy of Prematurity Stage Diagnosis Using Object Segmentation and Convolutional Neural Networks

Retinopathy of Prematurity (ROP) is an eye disorder primarily affecting ...
04/03/2020 ∙ by Alexander Ding, et al. ∙ 12 ∙ share

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HYPE: A High Performing NLP System for Automatically Detecting Hypoglycemia Events from Electronic Health Record Notes

Hypoglycemia is common and potentially dangerous among those treated for...
11/29/2018 ∙ by Yonghao Jin, et al. ∙ 10 ∙ share

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Pseudo-Labeling for Small Lesion Detection on Diabetic Retinopathy Images

Diabetic retinopathy (DR) is a primary cause of blindness in working-age...
03/26/2020 ∙ by Qilei Chen, et al. ∙ 5 ∙ share

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Benchmarking Off-The-Shelf Solutions to Robotic Assembly Tasks

In recent years, many learning based approaches have been studied to rea...
03/08/2021 ∙ by Wenzhao Lian, et al. ∙ 5 ∙ share

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Return of Frustratingly Easy Domain Adaptation

Unlike human learning, machine learning often fails to handle changes be...
11/17/2015 ∙ by Baochen Sun, et al. ∙ 0 ∙ share

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Ask, Attend and Answer: Exploring Question-Guided Spatial Attention for Visual Question Answering

We address the problem of Visual Question Answering (VQA), which require...
11/17/2015 ∙ by Huijuan Xu, 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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One-Shot Adaptation of Supervised Deep Convolutional Models

Dataset bias remains a significant barrier towards solving real world co...
12/21/2013 ∙ by Judy Hoffman, et al. ∙ 0 ∙ share

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Natural Language Object Retrieval

In this paper, we address the task of natural language object retrieval,...
11/13/2015 ∙ by Ronghang Hu, et al. ∙ 0 ∙ share

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Simultaneous Deep Transfer Across Domains and Tasks

Recent reports suggest that a generic supervised deep CNN model trained ...
10/08/2015 ∙ by Eric Tzeng, et al. ∙ 0 ∙ share

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What Do Deep CNNs Learn About Objects?

Deep convolutional neural networks learn extremely powerful image repres...
04/09/2015 ∙ by Xingchao Peng, et al. ∙ 0 ∙ share

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Translating Videos to Natural Language Using Deep Recurrent Neural Networks

Solving the visual symbol grounding problem has long been a goal of arti...
12/15/2014 ∙ by Subhashini Venugopalan, et al. ∙ 0 ∙ share

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Deep Domain Confusion: Maximizing for Domain Invariance

Recent reports suggest that a generic supervised deep CNN model trained ...
12/10/2014 ∙ by Eric Tzeng, et al. ∙ 0 ∙ share

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Detector Discovery in the Wild: Joint Multiple Instance and Representation Learning

We develop methods for detector learning which exploit joint training ov...
12/02/2014 ∙ by Judy Hoffman, et al. ∙ 0 ∙ share

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LSDA: Large Scale Detection Through Adaptation

A major challenge in scaling object detection is the difficulty of obtai...
07/18/2014 ∙ by Judy Hoffman, et al. ∙ 0 ∙ share

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Modeling Radiometric Uncertainty for Vision with Tone-mapped Color Images

To produce images that are suitable for display, tone-mapping is widely ...
11/27/2013 ∙ by Ayan Chakrabarti, et al. ∙ 0 ∙ share

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Fast Verification of Convexity of Piecewise-linear Surfaces

We show that a realization of a closed connected PL-manifold of dimensio...
09/23/2003 ∙ by Konstantin Rybnikov, et al. ∙ 0 ∙ share

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DTATG: An Automatic Title Generator based on Dependency Trees

We study automatic title generation for a given block of text and presen...
10/01/2017 ∙ by Liqun Shao, et al. ∙ 0 ∙ share

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Efficient and Effective Single-Document Summarizations and A Word-Embedding Measurement of Quality

Our task is to generate an effective summary for a given document with s...
10/01/2017 ∙ by Liqun Shao, et al. ∙ 0 ∙ share

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Temporal Information Extraction for Question Answering Using Syntactic Dependencies in an LSTM-based Architecture

In this paper, we propose to use a set of simple, uniform in architectur...
03/17/2017 ∙ by Yuanliang Meng, et al. ∙ 0 ∙ share

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Here's My Point: Joint Pointer Architecture for Argument Mining

One of the major goals in automated argumentation mining is to uncover t...
12/28/2016 ∙ by Peter Potash, et al. ∙ 0 ∙ share

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#HashtagWars: Learning a Sense of Humor

In this work, we present a new dataset for computational humor, specific...
12/09/2016 ∙ by Peter Potash, et al. ∙ 0 ∙ share

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Evaluating Creative Language Generation: The Case of Rap Lyric Ghostwriting

Language generation tasks that seek to mimic human ability to use langua...
12/09/2016 ∙ by Peter Potash, et al. ∙ 0 ∙ share

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A Game-theoretic Framework for Revenue Sharing in Edge-Cloud Computing System

We introduce a game-theoretic framework to ex- plore revenue sharing in ...
11/28/2017 ∙ by Zhi Cao, et al. ∙ 0 ∙ share

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Design Decisions for Weave: A Real-Time Web-based Collaborative Visualization Framework

There are many web-based visualization systems available to date, each h...
08/28/2017 ∙ by Andrew Dufilie, et al. ∙ 0 ∙ share

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CliNER 2.0: Accessible and Accurate Clinical Concept Extraction

Clinical notes often describe important aspects of a patient's stay and ...
03/06/2018 ∙ by Willie Boag, et al. ∙ 0 ∙ share

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Challenges Towards Deploying Data Intensive Scientific Applications on Extreme Heterogeneity Supercomputers

Shrinking transistors, which powered the advancement of computing in the...
04/25/2018 ∙ by Hang Liu, et al. ∙ 0 ∙ share

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IoT Security: An End-to-End View and Case Study

In this paper, we present an end-to-end view of IoT security and privacy...
05/15/2018 ∙ by Zhen Ling, et al. ∙ 0 ∙ share

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Deep learning in business analytics and operations research: Models, applications and managerial implications

Business analytics refers to methods and practices that create value thr...
06/28/2018 ∙ by Mathias Kraus, et al. ∙ 0 ∙ share

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Lessons from Natural Language Inference in the Clinical Domain

State of the art models using deep neural networks have become very good...
08/21/2018 ∙ by Alexey Romanov, et al. ∙ 0 ∙ share

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Adversarial Decomposition of Text Representation

In this paper, we present a method for adversarial decomposition of text...
08/27/2018 ∙ by Alexey Romanov, et al. ∙ 0 ∙ share

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Semantic WordRank: Generating Finer Single-Document Summarizations

We present Semantic WordRank (SWR), an unsupervised method for generatin...
09/12/2018 ∙ by Hao Zhang, et al. ∙ 0 ∙ share

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Triad-based Neural Network for Coreference Resolution

We propose a triad-based neural network system that generates affinity s...
09/18/2018 ∙ by Yuanliang Meng, et al. ∙ 0 ∙ share

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Adversarial Text Generation Without Reinforcement Learning

Generative Adversarial Networks (GANs) have experienced a recent surge i...
10/11/2018 ∙ by David Donahue, et al. ∙ 0 ∙ share

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Evolutionary Cell Aided Design for Neural Network Architectures

Mathematical theory shows us that multilayer feedforward Artificial Neur...
03/06/2019 ∙ by Philip Colangelo, et al. ∙ 0 ∙ share

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Skill Acquisition via Automated Multi-Coordinate Cost Balancing

We propose a learning framework, named Multi-Coordinate Cost Balancing (...
03/27/2019 ∙ by Harish Ravichandar, et al. ∙ 0 ∙ share

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Revealing the Dark Secrets of BERT

BERT-based architectures currently give state-of-the-art performance on ...
08/21/2019 ∙ by Olga Kovaleva, et al. ∙ 0 ∙ share

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A Deep Reinforcement Learning Approach to Multi-component Job Scheduling in Edge Computing

We are interested in the optimal scheduling of a collection of multi-com...
08/26/2019 ∙ by Zhi Cao, et al. ∙ 0 ∙ share

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Solving Math Word Problems with Double-Decoder Transformer

This paper proposes a Transformer-based model to generate equations for ...
08/28/2019 ∙ by Yuanliang Meng, et al. ∙ 0 ∙ share

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3D Anchor-Free Lesion Detector on Computed Tomography Scans

Lesions are injuries and abnormal tissues in the human body. Detecting l...
08/29/2019 ∙ by Ning Zhang, et al. ∙ 0 ∙ share

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NarrativeTime: Dense High-Speed Temporal Annotation on a Timeline

We present NarrativeTime, a new timeline-based annotation scheme for tem...
08/29/2019 ∙ by Anna Rogers, et al. ∙ 0 ∙ share

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AFP-Net: Realtime Anchor-Free Polyp Detection in Colonoscopy

Colorectal cancer (CRC) is a common and lethal disease. Globally, CRC is...
09/05/2019 ∙ by Dechun Wang, et al. ∙ 0 ∙ share

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Mini Lesions Detection on Diabetic Retinopathy Images via Large Scale CNN Features

Diabetic retinopathy (DR) is a diabetes complication that affects eyes. ...
11/19/2019 ∙ by Qilei Chen, et al. ∙ 0 ∙ share

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ICD Coding from Clinical Text Using Multi-Filter Residual Convolutional Neural Network

Automated ICD coding, which assigns the International Classification of ...
11/25/2019 ∙ by Fei Li, et al. ∙ 0 ∙ share

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MetaMT,a MetaLearning Method Leveraging Multiple Domain Data for Low Resource Machine Translation

Manipulating training data leads to robust neural models for MT....
12/11/2019 ∙ by Rumeng Li, et al. ∙ 0 ∙ share

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A Primer in BERTology: What we know about how BERT works

Transformer-based models are now widely used in NLP, but we still do not...
02/27/2020 ∙ by Anna Rogers, et al. ∙ 0 ∙ share

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Towards Mobile Multi-Task Manipulation in a Confined and Integrated Environment with Irregular Objects

The FetchIt! Mobile Manipulation Challenge, held at the IEEE Internation...
03/03/2020 ∙ by Zhao Han, et al. ∙ 0 ∙ share

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LAXARY: A Trustworthy Explainable Twitter Analysis Model for Post-Traumatic Stress Disorder Assessment

Veteran mental health is a significant national problem as large number ...
03/16/2020 ∙ by Mohammad Arif Ul Alam, et al. ∙ 0 ∙ share

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