Search Results for author:
Found 7 papers, 2 papers with code
Implicit Regularization for Multi-label Feature Selection
In this paper, we address the problem of feature selection in the context of multi-label learning, by using a new estimator based on implicit regularization and label embedding.
Multi-View Majority Vote Learning Algorithms: Direct Minimization of PAC-Bayesian Bounds
The PAC-Bayesian framework has significantly advanced our understanding of statistical learning, particularly in majority voting methods.
iText2KG: Incremental Knowledge Graphs Construction Using Large Language Models
Our method demonstrates superior performance compared to baseline methods across three scenarios: converting scientific papers to graphs, websites to graphs, and CVs to graphs.
PAC-Bayesian Domain Adaptation Bounds for Multi-view learning
This paper presents a series of new results for domain adaptation in the multi-view learning setting.
Autoencoder-based Attribute Noise Handling Method for Medical Data
Medical datasets are particularly subject to attribute noise, that is, missing and erroneous values.
Deep Multi-View Learning for Tire Recommendation
We are constantly using recommender systems, often without even noticing.
Debiasing Pretrained Text Encoders by Paying Attention to Paying Attention
Recent studies in fair Representation Learning have observed a strong inclination for natural language processing (NLP) models to exhibit discriminatory stereotypes across gender, religion, race and many such social constructs.
