Search Results for author: Cynthia C. S. Liem

Found 6 papers, 4 papers with code

Run, Forest, Run? On Randomization and Reproducibility in Predictive Software Engineering

no code implementations15 Dec 2020 Cynthia C. S. Liem, Annibale Panichella

To understand whether and how researchers in SE address these threats, we surveyed 45 recent papers related to three predictive tasks: defect prediction (DP), predictive mutation testing (PMT), and code smell detection (CSD).

Software Engineering

Are Nearby Neighbors Relatives?: Testing Deep Music Embeddings

no code implementations15 Apr 2019 Jaehun Kim, Julián Urbano, Cynthia C. S. Liem, Alan Hanjalic

The underlying assumption is that in case a deep representation is to be trusted, distance consistency between known related points should be maintained both in the input audio space and corresponding latent deep space.

Transfer Learning of Artist Group Factors to Musical Genre Classification

1 code implementation5 May 2018 Jaehun Kim, Minz Won, Xavier Serra, Cynthia C. S. Liem

The automated recognition of music genres from audio information is a challenging problem, as genre labels are subjective and noisy.

Classification General Classification +2

One Deep Music Representation to Rule Them All? : A comparative analysis of different representation learning strategies

1 code implementation12 Feb 2018 Jaehun Kim, Julián Urbano, Cynthia C. S. Liem, Alan Hanjalic

In this paper, we present the results of our investigation of what are the most important factors to generate deep representations for the data and learning tasks in the music domain.

Information Retrieval Music Information Retrieval +2

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