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cs.CL2024
More Discriminative Sentence Embeddings via Semantic Graph Smoothing
Chakib Fettal, Lazhar Labiod, Mohamed Nadif
This paper explores an empirical approach to learn more discriminantive sentence representations in an unsupervised fashion. Leveraging semantic graph smoothing, we enhance sentenc…
cs.LG2024
Scalable Multi-view Clustering via Explicit Kernel Features Maps
Chakib Fettal, Lazhar Labiod, Mohamed Nadif
The proliferation of high-dimensional data from sources such as social media, sensor networks, and online platforms has created new challenges for clustering algorithms. Multi-view…
cs.LG2024
Graph Cuts with Arbitrary Size Constraints Through Optimal Transport
Chakib Fettal, Lazhar Labiod, Mohamed Nadif
A common way of partitioning graphs is through minimum cuts. One drawback of classical minimum cut methods is that they tend to produce small groups, which is why more balanced var…