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09/18/2023
LLM4Jobs: Unsupervised occupation extraction and standardization leveraging Large Language Models
Automated occupation extraction and standardization from free-text job p...
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08/18/2023
ReCon: Reducing Congestion in Job Recommendation using Optimal Transport
Recommender systems may suffer from congestion, meaning that there is an...
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04/17/2023
SkillGPT: a RESTful API service for skill extraction and standardization using a Large Language Model
We present SkillGPT, a tool for skill extraction and standardization (SE...
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04/12/2023
Maximal Fairness
Fairness in AI has garnered quite some attention in research, and increa...
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12/13/2022
Inherent Limitations of AI Fairness
As the real-world impact of Artificial Intelligence (AI) systems has bee...
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09/16/2022
A Systematic Evaluation of Node Embedding Robustness
Node embedding methods map network nodes to low dimensional vectors that...
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09/12/2022
A challenge-based survey of e-recruitment recommendation systems
E-recruitment recommendation systems recommend jobs to job seekers and j...
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03/14/2022
Graph-Survival: A Survival Analysis Framework for Machine Learning on Temporal Networks
Continuous time temporal networks are attracting increasing attention du...
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02/22/2022
Evaluating Feature Attribution Methods in the Image Domain
Feature attribution maps are a popular approach to highlight the most im...
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02/08/2022
Optimal Transport of Binary Classifiers to Fairness
Much of the past work on fairness in machine learning has focused on for...
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12/14/2021
An Earth Mover's Distance Based Graph Distance Metric For Financial Statements
Quantifying the similarity between a group of companies has proven to be...
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10/18/2021
Topologically Regularized Data Embeddings
Unsupervised feature learning often finds low-dimensional embeddings tha...
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09/22/2021
The Curse Revisited: a Newly Quantified Concept of Meaningful Distances for Learning from High-Dimensional Noisy Data
Distances between data points are widely used in point cloud representat...
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07/05/2021
Adversarial Robustness of Probabilistic Network Embedding for Link Prediction
In today's networked society, many real-world problems can be formalized...
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05/12/2021
Automating Data Science: Prospects and Challenges
Given the complexity of typical data science projects and the associated...
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03/02/2021
The KL-Divergence between a Graph Model and its Fair I-Projection as a Fairness Regularizer
Learning and reasoning over graphs is increasingly done by means of prob...
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05/19/2020
CSNE: Conditional Signed Network Embedding
Signed networks are mathematical structures that encode positive and neg...
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02/26/2020
DeBayes: a Bayesian method for debiasing network embeddings
As machine learning algorithms are increasingly deployed for high-impact...
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02/25/2020
Network Representation Learning for Link Prediction: Are we improving upon simple heuristics?
Network representation learning has become an active research area in re...
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02/24/2020
FONDUE: A Framework for Node Disambiguation Using Network Embeddings
Real-world data often presents itself in the form of a network. Examples...
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02/14/2020
Scalable Dyadic Independence Models with Local and Global Constraints
An important challenge in the field of exponential random graphs (ERGs) ...
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02/04/2020
ALPINE: Active Link Prediction using Network Embedding
Many real-world problems can be formalized as predicting links in a part...
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09/20/2019
FACE: Feasible and Actionable Counterfactual Explanations
Work in Counterfactual Explanations tends to focus on the principle of "...
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09/03/2019
Discovering Interesting Cycles in Directed Graphs
Cycles in graphs often signify interesting processes. For example, cycli...
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05/24/2019
Conditional t-SNE: Complementary t-SNE embeddings through factoring out prior information
Dimensionality reduction and manifold learning methods such as t-Distrib...
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04/22/2019
ExplaiNE: An Approach for Explaining Network Embedding-based Link Predictions
Networks are powerful data structures, but are challenging to work with ...
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05/19/2018
Conditional Network Embeddings
Network embeddings map the nodes of a given network into d-dimensional E...
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10/23/2017
Interactive Visual Data Exploration with Subjective Feedback: An Information-Theoretic Approach
Visual exploration of high-dimensional real-valued datasets is a fundame...
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10/12/2017
Subjectively Interesting Subgroup Discovery on Real-valued Targets
Deriving insights from high-dimensional data is one of the core problems...
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07/25/2011
An end-to-end machine learning system for harmonic analysis of music
We present a new system for simultaneous estimation of keys, chords, and...
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06/29/2009
