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05/14/2023
Learning Non-linguistic Skills without Sacrificing Linguistic Proficiency
The field of Math-NLP has witnessed significant growth in recent years, ...
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11/03/2022
Overcoming Barriers to Skill Injection in Language Modeling: Case Study in Arithmetic
Through their transfer learning abilities, highly-parameterized large pr...
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10/01/2022
Detecting Irregular Network Activity with Adversarial Learning and Expert Feedback
Anomaly detection is a ubiquitous and challenging task relevant across m...
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08/04/2022
Memetic algorithms for Spatial Partitioning problems
Spatial optimization problems (SOPs) are characterized by spatial relati...
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07/31/2022
Scrutinizing Shipment Records To Thwart Illegal Timber Trade
Timber and forest products made from wood, like furniture, are valuable ...
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07/25/2022
Innovations in Neural Data-to-text Generation
The neural boom that has sparked natural language processing (NLP) resea...
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07/08/2022
Lessons from Deep Learning applied to Scholarly Information Extraction: What Works, What Doesn't, and Future Directions
Understanding key insights from full-text scholarly articles is essentia...
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06/29/2022
Framing Algorithmic Recourse for Anomaly Detection
The problem of algorithmic recourse has been explored for supervised mac...
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06/08/2022
Sampling-based techniques for designing school boundaries
Recently, an increasing number of researchers, especially in the realm o...
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04/06/2022
Improving Zero-Shot Event Extraction via Sentence Simplification
The success of sites such as ACLED and Our World in Data have demonstrat...
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03/04/2022
Contrastive Graph Convolutional Networks for Hardware Trojan Detection in Third Party IP Cores
The availability of wide-ranging third-party intellectual property (3PIP...
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02/21/2022
EINNs: Epidemiologically-Informed Neural Networks
We introduce a new class of physics-informed neural networks-EINN-crafte...
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11/09/2021
Deep diffusion-based forecasting of COVID-19 by incorporating network-level mobility information
Modeling the spatiotemporal nature of the spread of infectious diseases ...
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10/11/2021
TCube: Domain-Agnostic Neural Time-series Narration
The task of generating rich and fluent narratives that aptly describe th...
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06/30/2021
Using AntiPatterns to avoid MLOps Mistakes
We describe lessons learned from developing and deploying machine learni...
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04/02/2021
Detecting Anomalies Through Contrast in Heterogeneous Data
Detecting anomalies has been a fundamental approach in detecting potenti...
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12/11/2020
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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09/27/2020
STAN: Synthetic Network Traffic Generation using Autoregressive Neural Models
Deep learning models have achieved great success in recent years. Howeve...
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09/23/2020
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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09/06/2020
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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11/26/2019
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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11/06/2019
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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07/17/2019
Mitigating Uncertainty in Document Classification
The uncertainty measurement of classifiers' predictions is especially im...
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05/22/2019
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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12/05/2018
Neural Abstractive Text Summarization with Sequence-to-Sequence Models
In the past few years, neural abstractive text summarization with sequen...
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10/15/2018
Deep Transfer Reinforcement Learning for Text Summarization
Deep neural networks are data hungry models and thus they face difficult...
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05/24/2018
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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02/22/2017
Distributed Representation of Subgraphs
Network embeddings have become very popular in learning effective featur...
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02/22/2017
SIGNet: Scalable Embeddings for Signed Networks
Recent successes in word embedding and document embedding have motivated...
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02/22/2017
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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06/01/2016
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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03/31/2016
Hierarchical Quickest Change Detection via Surrogates
Change detection (CD) in time series data is a critical problem as it re...
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03/01/2016
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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02/21/2016
Interactive Storytelling over Document Collections
Storytelling algorithms aim to 'connect the dots' between disparate docu...
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02/17/2010
Efficiently Discovering Hammock Paths from Induced Similarity Networks
Similarity networks are important abstractions in many information manag...
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06/22/2009
Recommender Systems for the Conference Paper Assignment Problem
Conference paper assignment, i.e., the task of assigning paper submissio...
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07/21/2002
Reinforcing Reachable Routes
This paper studies the evaluation of routing algorithms from the perspec...
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05/14/2002
The Traits of the Personable
Information personalization is fertile ground for application of AI tech...
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04/26/2002
Qualitative Analysis of Correspondence for Experimental Algorithmics
Correspondence identifies relationships among objects via similarities a...
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04/22/2002
Sampling Strategies for Mining in Data-Scarce Domains
Data mining has traditionally focused on the task of drawing inferences ...
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10/18/1999
