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Discovery and Separation of Features for Invariant Representation Learning
Supervised machine learning models often associate irrelevant nuisance f...
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Invariant Representations through Adversarial Forgetting
We propose a novel approach to achieving invariance for deep neural netw...
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KGTK: A Toolkit for Large Knowledge Graph Manipulation and Analysis
Knowledge graphs (KGs) have become the preferred technology for represen...
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Sequential Unsupervised Domain Adaptation through Prototypical Distributions
We develop an algorithm for unsupervised domain adaptation (UDA) of a cl...
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Tensor Embedding: A Supervised Framework for Human Behavioral Data Mining and Prediction
Today's densely instrumented world offers tremendous opportunities for c...
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Identifying and Analyzing Cryptocurrency Manipulations in Social Media
Interest surrounding cryptocurrencies, digital or virtual currencies tha...
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Learning Behavioral Representations from Wearable Sensors
The ubiquity of mobile devices and wearable sensors offers unprecedented...
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Multi-Modal Fingerprint Presentation Attack Detection: Evaluation On A New Dataset
Fingerprint presentation attack detection is becoming an increasingly ch...
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Multispectral Biometrics System Framework: Application to Presentation Attack Detection
In this work, we present a general framework for building a biometrics s...
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DARKMENTION: A Deployed System to Predict Enterprise-Targeted External Cyberattacks
Recent incidents of data breaches call for organizations to proactively ...
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Discovering patterns of online popularity from time series
How is popularity gained online? Is being successful strictly related to...
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Towards Learning Representations of Binary Executable Files for Security Tasks
Tackling binary analysis problems has traditionally implied manually def...
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Event Cartography: Latent Point Process Embeddings
Many important phenomena arise naturally as temporal point processes wit...
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SemEval-2013 Task 4: Free Paraphrases of Noun Compounds
In this paper, we describe SemEval-2013 Task 4: the definition, the data...
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Overview of Scanner Invariant Representations
Pooled imaging data from multiple sources is subject to bias from each s...
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Challenges in Forecasting Malicious Events from Incomplete Data
The ability to accurately predict cyber-attacks would enable organizatio...
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Recurrent Event Network for Reasoning over Temporal Knowledge Graphs
Recently, there has been a surge of interest in learning representation ...
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Identifying Cultural Differences through Multi-Lingual Wikipedia
Understanding cross-cultural differences is an important application of ...
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R^3: Reverse, Retrieve, and Rank for Sarcasm Generation with Commonsense Knowledge
We propose an unsupervised approach for sarcasm generation based on a no...
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Discovering Hidden Structure in High Dimensional Human Behavioral Data via Tensor Factorization
In recent years, the rapid growth in technology has increased the opport...
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An End-to-End Neural Network for Image Cropping by Learning Composition from Aesthetic Photos
As one of the fundamental techniques for image editing, image cropping d...
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Learn How to Cook a New Recipe in a New House: Using Map Familiarization, Curriculum Learning, and Common Sense to Learn Families of Text-Based Adventure Games
We consider the task of learning to play families of text-based computer...
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Connecting the Dots: A Knowledgeable Path Generator for Commonsense Question Answering
Commonsense question answering (QA) requires the modeling of general bac...
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Unsupervised Adversarial Invariance
Data representations that contain all the information about target varia...
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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...
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Efficient Covariance Estimation from Temporal Data
Estimating the covariance structure of multivariate time series is a fun...
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Neural Machine Translation with Imbalanced Classes
We cast neural machine translation (NMT) as a classification task in an ...
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FlagIt: A System for Minimally Supervised Human Trafficking Indicator Mining
In this paper, we describe and study the indicator mining problem in the...
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Always Lurking: Understanding and Mitigating Bias in Online Human Trafficking Detection
Web-based human trafficking activity has increased in recent years but i...
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Bidirectional Conditional Generative Adversarial Networks
Conditional variants of Generative Adversarial Networks (GANs), known as...
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Efficient Representation for Natural Language Processing via Kernelized Hashcodes
Kernel similarity functions have been successfully applied in classifica...
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WMRB: Learning to Rank in a Scalable Batch Training Approach
We propose a new learning to rank algorithm, named Weighted Margin-Rank ...
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Multimedia Semantic Integrity Assessment Using Joint Embedding Of Images And Text
Real world multimedia data is often composed of multiple modalities such...
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Modeling Missing Data in Clinical Time Series with RNNs
We demonstrate a simple strategy to cope with missing data in sequential...
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FacePoseNet: Making a Case for Landmark-Free Face Alignment
We show how a simple convolutional neural network (CNN) can be trained t...
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Using Contexts and Constraints for Improved Geotagging of Human Trafficking Webpages
Extracting geographical tags from webpages is a well-motivated applicati...
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Unsupervised Learning via Total Correlation Explanation
Learning by children and animals occurs effortlessly and largely without...
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Label Propagation on K-partite Graphs with Heterophily
In this paper, for the first time, we study label propagation in heterog...
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Deep Matching and Validation Network -- An End-to-End Solution to Constrained Image Splicing Localization and Detection
Image splicing is a very common image manipulation technique that is som...
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Towards the Modeling of Behavioral Trajectories of Users in Online Social Media
In this paper, we introduce a methodology that allows to model behaviora...
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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. ...
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Learning the Semantics of Structured Data Sources
Information sources such as relational databases, spreadsheets, XML, JSO...
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Hardware-Driven Nonlinear Activation for Stochastic Computing Based Deep Convolutional Neural Networks
Recently, Deep Convolutional Neural Networks (DCNNs) have made unprecede...
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Extracting Biomolecular Interactions Using Semantic Parsing of Biomedical Text
We advance the state of the art in biomolecular interaction extraction w...
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Temporal Learning and Sequence Modeling for a Job Recommender System
We present our solution to the job recommendation task for RecSys Challe...
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Using Syntax-Based Machine Translation to Parse English into Abstract Meaning Representation
We present a parser for Abstract Meaning Representation (AMR). We treat ...
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Toward Interpretable Topic Discovery via Anchored Correlation Explanation
Many predictive tasks, such as diagnosing a patient based on their medic...
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Variational Information Maximization for Feature Selection
Feature selection is one of the most fundamental problems in machine lea...
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Sifting Common Information from Many Variables
Measuring the relationship between any pair of variables is a rich and a...
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Discovering Structure in High-Dimensional Data Through Correlation Explanation
We introduce a method to learn a hierarchy of successively more abstract...
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