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Detecting Anomalies Through Contrast in Heterogeneous Data
Detecting anomalies has been a fundamental approach in detecting potenti...
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Better call Surrogates: A hybrid Evolutionary Algorithm for Hyperparameter optimization
In this paper, we propose a surrogate-assisted evolutionary algorithm (E...
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STAN: Synthetic Network Traffic Generation using Autoregressive Neural Models
Deep learning models have achieved great success in recent years. Howeve...
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Steering a Historical Disease Forecasting Model Under a Pandemic: Case of Flu and COVID-19
Forecasting influenza in a timely manner aids health organizations and p...
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Once Upon A Time In Visualization: Understanding the Use of Textual Narratives for Causality
Causality visualization can help people understand temporal chains of ev...
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Low Rank Factorization for Compact Multi-Head Self-Attention
Effective representation learning from text has been an active area of r...
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Physics-guided Design and Learning of Neural Networks for Predicting Drag Force on Particle Suspensions in Moving Fluids
Physics-based simulations are often used to model and understand complex...
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Mitigating Uncertainty in Document Classification
The uncertainty measurement of classifiers' predictions is especially im...
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Patent Citation Dynamics Modeling via Multi-Attention Recurrent Networks
Modeling and forecasting forward citations to a patent is a central task...
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Neural Abstractive Text Summarization with Sequence-to-Sequence Models
In the past few years, neural abstractive text summarization with sequen...
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Deep Transfer Reinforcement Learning for Text Summarization
Deep neural networks are data hungry models and thus they face difficult...
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Deep Reinforcement Learning For Sequence to Sequence Models
In recent years, sequence-to-sequence (seq2seq) models are used in a var...
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Distributed Representation of Subgraphs
Network embeddings have become very popular in learning effective featur...
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SIGNet: Scalable Embeddings for Signed Networks
Recent successes in word embedding and document embedding have motivated...
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Guided Deep List: Automating the Generation of Epidemiological Line Lists from Open Sources
Real-time monitoring and responses to emerging public health threats rel...
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Temporal Topic Modeling to Assess Associations between News Trends and Infectious Disease Outbreaks
In retrospective assessments, internet news reports have been shown to c...
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Hierarchical Quickest Change Detection via Surrogates
Change detection (CD) in time series data is a critical problem as it re...
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Characterizing Diseases from Unstructured Text: A Vocabulary Driven Word2vec Approach
Traditional disease surveillance can be augmented with a wide variety of...
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Interactive Storytelling over Document Collections
Storytelling algorithms aim to 'connect the dots' between disparate docu...
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Efficiently Discovering Hammock Paths from Induced Similarity Networks
Similarity networks are important abstractions in many information manag...
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Recommender Systems for the Conference Paper Assignment Problem
Conference paper assignment, i.e., the task of assigning paper submissio...
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Reinforcing Reachable Routes
This paper studies the evaluation of routing algorithms from the perspec...
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The Traits of the Personable
Information personalization is fertile ground for application of AI tech...
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Qualitative Analysis of Correspondence for Experimental Algorithmics
Correspondence identifies relationships among objects via similarities a...
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Sampling Strategies for Mining in Data-Scarce Domains
Data mining has traditionally focused on the task of drawing inferences ...
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PIPE: Personalizing Recommendations via Partial Evaluation
It is shown that personalization of web content can be advantageously vi...
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