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12/08/2022
GenSyn: A Multi-stage Framework for Generating Synthetic Microdata using Macro Data Sources
Individual-level data (microdata) that characterizes a population, is es...
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08/16/2022
Ex-Ante Assessment of Discrimination in Dataset
Data owners face increasing liability for how the use of their data coul...
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04/26/2022
SoFaiR: Single Shot Fair Representation Learning
To avoid discriminatory uses of their data, organizations can learn to m...
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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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02/24/2022
Trade-offs between Group Fairness Metrics in Societal Resource Allocation
We consider social resource allocations that deliver an array of scarce ...
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12/10/2021
Causal Knowledge Guided Societal Event Forecasting
Data-driven societal event forecasting methods exploit relevant historic...
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09/01/2021
Asynchronous Federated Learning for Sensor Data with Concept Drift
Federated learning (FL) involves multiple distributed devices jointly tr...
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08/31/2021
Cross-Lingual Text Classification of Transliterated Hindi and Malayalam
Transliteration is very common on social media, but transliterated text ...
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05/28/2021
Fair Representations by Compression
Organizations that collect and sell data face increasing scrutiny for th...
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03/13/2021
Multilingual Code-Switching for Zero-Shot Cross-Lingual Intent Prediction and Slot Filling
Predicting user intent and detecting the corresponding slots from text a...
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11/13/2020
Metric-Free Individual Fairness with Cooperative Contextual Bandits
Data mining algorithms are increasingly used in automated decision makin...
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10/12/2020
FedAT: A Communication-Efficient Federated Learning Method with Asynchronous Tiers under Non-IID Data
Federated learning (FL) involves training a model over massive distribut...
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06/15/2020
Learning Smooth and Fair Representations
Organizations that own data face increasing legal liability for its disc...
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03/26/2020
Common-Knowledge Concept Recognition for SEVA
We build a common-knowledge concept recognition system for a Systems Eng...
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03/04/2020
FineHand: Learning Hand Shapes for American Sign Language Recognition
American Sign Language recognition is a difficult gesture recognition pr...
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03/04/2020
Unsupervised and Interpretable Domain Adaptation to Rapidly Filter Social Web Data for Emergency Services
During the onset of a disaster event, filtering relevant information fro...
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02/25/2020
Diversity-Based Generalization for Neural Unsupervised Text Classification under Domain Shift
Domain adaptation approaches seek to learn from a source domain and gene...
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12/26/2019
Academic Performance Estimation with Attention-based Graph Convolutional Networks
Student's academic performance prediction empowers educational technolog...
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12/21/2019
Graph Message Passing with Cross-location Attentions for Long-term ILI Prediction
Forecasting influenza-like illness (ILI) is of prime importance to epide...
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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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11/05/2019
Asynchronous Online Federated Learning for Edge Devices
Federated learning (FL) is a machine learning paradigm where a shared ce...
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09/24/2019
Sign Language Recognition Analysis using Multimodal Data
Voice-controlled personal and home assistants (such as the Amazon Echo a...
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05/13/2019
Federated Multi-task Hierarchical Attention Model for Sensor Analytics
Sensors are an integral part of modern Internet of Things (IoT) applicat...
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03/18/2019
Multi-Differential Fairness Auditor for Black Box Classifiers
Machine learning algorithms are increasingly involved in sensitive decis...
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02/26/2019
Reliable Deep Grade Prediction with Uncertainty Estimation
Currently, college-going students are taking longer to graduate than the...
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01/17/2018
ALE: Additive Latent Effect Models for Grade Prediction
The past decade has seen a growth in the development and deployment of e...
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06/06/2017
Classifying Documents within Multiple Hierarchical Datasets using Multi-Task Learning
Multi-task learning (MTL) is a supervised learning paradigm in which the...
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06/06/2017
Embedding Feature Selection for Large-scale Hierarchical Classification
Large-scale Hierarchical Classification (HC) involves datasets consistin...
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06/05/2017
Inconsistent Node Flattening for Improving Top-down Hierarchical Classification
Large-scale classification of data where classes are structurally organi...
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03/02/2016
