UIS-RNN solves the problem of segmenting and clustering sequential data by learning from examples. It was originally proposed in the paper Fully Supervised Speaker Diarization for identifying who spoke when in audio recordings. The algorithm performs supervised clustering using speaker embeddings (d-vector) to group audio segments by speaker identity.