output
19982026
most citedLearning Representations for Neural Network-Based Classification Using the Information Bottleneck Principle

200 citations

Showing 2024Show all

6 papers · 1 filter

astro-ph.IM2024★ 4 cited

Machine learning based stellar classification with highly sparse photometry data

Sean Enis Cody, Sebastian Scher, Iain McDonald +3

Identifying stars belonging to different classes is vital in order to build up statistical samples of different phases and pathways of stellar evolution. In the era of surveys cove…

cs.IR2024★ 11 cited

Oh, Behave! Country Representation Dynamics Created by Feedback Loops in Music Recommender Systems

Oleg Lesota, Jonas Geiger, Max Walder +2

Recent work suggests that music recommender systems are prone to disproportionally frequent recommendations of music from countries more prominently represented in the training dat…

cs.IR2024★ 11 cited

Making Alice Appear Like Bob: A Probabilistic Preference Obfuscation Method For Implicit Feedback Recommendation Models

Gustavo Escobedo, Marta Moscati, Peter Muellner +4

Users' interaction or preference data used in recommender systems carry the risk of unintentionally revealing users' private attributes (e.g., gender or race). This risk becomes pa…

cs.LG2024★ 3 cited

Continual Learning in the Presence of Repetition

Hamed Hemati, Lorenzo Pellegrini, Xiaotian Duan +11

Continual learning (CL) provides a framework for training models in ever-evolving environments. Although re-occurrence of previously seen objects or tasks is common in real-world p…

cs.LG2024★ 6 cited

Approximating Families of Sharp Solutions to Fisher's Equation with Physics-Informed Neural Networks

Franz M. Rohrhofer, Stefan Posch, Clemens Gößnitzer +1

This paper employs physics-informed neural networks (PINNs) to solve Fisher's equation, a fundamental reaction-diffusion system with both simplicity and significance. The focus is…

cs.SI2024

Recommendation Fairness in Social Networks Over Time

Meng Cao, Hussain Hussain, Sandipan Sikdar +3

In social recommender systems, it is crucial that the recommendation models provide equitable visibility for different demographic groups, such as gender or race. Most existing res…