b'Lise Getoor'

HyperFair: A Soft Approach to Integrating Fairness Criteria

Recommender systems are being employed across an increasingly diverse se...
09/05/2020 ∙ by Charles Dickens, et al. ∙ 0 ∙ share

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Causal Relational Learning

Causal inference is at the heart of empirical research in natural and so...
04/07/2020 ∙ by Babak Salimi, et al. ∙ 20 ∙ share

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Estimating Aggregate Properties In Relational Networks With Unobserved Data

Aggregate network properties such as cluster cohesion and the number of ...
01/16/2020 ∙ by Varun Embar, et al. ∙ 24 ∙ share

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User Profiling Using Hinge-loss Markov Random Fields

A variety of approaches have been proposed to automatically infer the pr...
01/05/2020 ∙ by Golnoosh Farnadi, et al. ∙ 6 ∙ share

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Estimating Causal Effects of Tone in Online Debates

Statistical methods applied to social media posts shed light on the dyna...
06/10/2019 ∙ by Dhanya Sridhar, et al. ∙ 0 ∙ share

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SysML: The New Frontier of Machine Learning Systems

Machine learning (ML) techniques are enjoying rapidly increasing adoptio...
03/29/2019 ∙ by Alexander Ratner, et al. ∙ 0 ∙ share

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A Fairness-aware Hybrid Recommender System

Recommender systems are used in variety of domains affecting people's li...
09/13/2018 ∙ by Golnoosh Farnadi, et al. ∙ 0 ∙ share

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Scalable Structure Learning for Probabilistic Soft Logic

Statistical relational frameworks such as Markov logic networks and prob...
07/03/2018 ∙ by Varun Embar, et al. ∙ 4 ∙ share

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Using Noisy Extractions to Discover Causal Knowledge

Knowledge bases (KB) constructed through information extraction from tex...
11/16/2017 ∙ by Dhanya Sridhar, et al. ∙ 0 ∙ share

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Generic Statistical Relational Entity Resolution in Knowledge Graphs

Entity resolution, the problem of identifying the underlying entity of r...
07/04/2016 ∙ by Jay Pujara, et al. ∙ 0 ∙ share

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Adaptive Neighborhood Graph Construction for Inference in Multi-Relational Networks

A neighborhood graph, which represents the instances as vertices and the...
07/02/2016 ∙ by Shobeir Fakhraei, et al. ∙ 0 ∙ share

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Hinge-Loss Markov Random Fields and Probabilistic Soft Logic

A fundamental challenge in developing high-impact machine learning techn...
05/17/2015 ∙ by Stephen H. Bach, et al. ∙ 0 ∙ share

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Value of Information Lattice: Exploiting Probabilistic Independence for Effective Feature Subset Acquisition

We address the cost-sensitive feature acquisition problem, where misclas...
01/16/2014 ∙ by Mustafa Bilgic, et al. ∙ 0 ∙ share

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Hinge-loss Markov Random Fields: Convex Inference for Structured Prediction

Graphical models for structured domains are powerful tools, but the comp...
09/26/2013 ∙ by Stephen Bach, et al. ∙ 0 ∙ share

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A Hypergraph-Partitioned Vertex Programming Approach for Large-scale Consensus Optimization

In modern data science problems, techniques for extracting value from bi...
08/30/2013 ∙ by Hui Miao, et al. ∙ 0 ∙ share

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Scalable Text and Link Analysis with Mixed-Topic Link Models

Many data sets contain rich information about objects, as well as pairwi...
03/28/2013 ∙ by Yaojia Zhu, et al. ∙ 0 ∙ share

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Utility Elicitation as a Classification Problem

We investigate the application of classification techniques to utility e...
01/30/2013 ∙ by Urszula Chajewska, et al. ∙ 0 ∙ share

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Bisimulation-based Approximate Lifted Inference

There has been a great deal of recent interest in methods for performing...
05/09/2012 ∙ by Prithviraj Sen, et al. ∙ 0 ∙ share

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Probabilistic Similarity Logic

Many machine learning applications require the ability to learn from and...
03/15/2012 ∙ by Matthias Brocheler, et al. ∙ 0 ∙ share

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Lifted Graphical Models: A Survey

This article presents a survey of work on lifted graphical models. We re...
07/25/2011 ∙ by Lilyana Mihalkova, et al. ∙ 0 ∙ share

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A Probabilistic Approach for Learning Folksonomies from Structured Data

Learning structured representations has emerged as an important problem ...
11/16/2010 ∙ by Anon Plangprasopchok, et al. ∙ 0 ∙ share

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Growing a Tree in the Forest: Constructing Folksonomies by Integrating Structured Metadata

Many social Web sites allow users to annotate the content with descripti...
05/27/2010 ∙ by Anon Plangprasopchok, et al. ∙ 0 ∙ share

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Integrating Structured Metadata with Relational Affinity Propagation

Structured and semi-structured data describing entities, taxonomies and ...
05/26/2010 ∙ by Anon Plangprasopchok, et al. ∙ 0 ∙ share

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Lise Getoor

Featured Co-authors

Michael I. Jordan

Dawn Song

Ce Zhang

Christopher Ré

Martin Jaggi

Joseph E. Gonzalez

Jing Li

Andrew Gordon Wilson

Ion Stoica

Song Han

Eric Xing

HyperFair: A Soft Approach to Integrating Fairness Criteria

Causal Relational Learning

Estimating Aggregate Properties In Relational Networks With Unobserved Data

User Profiling Using Hinge-loss Markov Random Fields

Estimating Causal Effects of Tone in Online Debates

SysML: The New Frontier of Machine Learning Systems

A Fairness-aware Hybrid Recommender System

Scalable Structure Learning for Probabilistic Soft Logic

Using Noisy Extractions to Discover Causal Knowledge

Generic Statistical Relational Entity Resolution in Knowledge Graphs

Adaptive Neighborhood Graph Construction for Inference in Multi-Relational Networks

Hinge-Loss Markov Random Fields and Probabilistic Soft Logic

Value of Information Lattice: Exploiting Probabilistic Independence for Effective Feature Subset Acquisition

Hinge-loss Markov Random Fields: Convex Inference for Structured Prediction

A Hypergraph-Partitioned Vertex Programming Approach for Large-scale Consensus Optimization

Scalable Text and Link Analysis with Mixed-Topic Link Models

Utility Elicitation as a Classification Problem

Bisimulation-based Approximate Lifted Inference

Probabilistic Similarity Logic

Lifted Graphical Models: A Survey

A Probabilistic Approach for Learning Folksonomies from Structured Data

Growing a Tree in the Forest: Constructing Folksonomies by Integrating Structured Metadata

Integrating Structured Metadata with Relational Affinity Propagation