MLSP 2020

IEEE International Workshop on
MACHINE LEARNING FOR SIGNAL PROCESSING

September 21–24, 2020 Aalto University, Espoo, Finland (virtual conference)

Paper Review

Login here to review papers. If you already have an existing Microsoft Conference Management Toolkit (CMT) account, you can use your existing account. Otherwise if you are new to CMT, please click on register.

When you login the first time as a reviewer for MLSP 2020, please select 1 primary subject area and up to 5 secondary subject areas. In order to help us ensure sufficient reviewers for submitted papers, please choose a broad selection of secondary subjects (up to 5) for which you are willing to review papers.

Paper Evaluation Process and Review Criteria

The Evaluation Process in Short

Reviewer’s Familiarity with the Paper’s Subject

The familiarity is scored as:

Evaluation Criteria

A quality paper is defined as a paper with high scores along the following criteria. The criteria reflect independent aspects of the paper’s quality and are hence also scored independently. Each criterion has an acceptance threshold and extended description of the issues to be evaluated. All marks indicated by green color are above the threshold.The interpretation of the scores is:

Criterion 1: Relevance to Conference Call and to which Degree the Paper is a Timely Contribution

Score:
Excellent, very good, good, fair, poor

Interpretation:
Is the paper within the scope of the workshop. Are the results important and timely?

Criterion 2: Scientific/Technical Originality and Potential Impact

Score:
Excellent, very good, good, fair, poor

Interpretation:
Are the problems or approaches new? Where possible, reviewers should identify submissions that are very similar (or identical) to versions that have been previously published. Is this a novel combination of familiar techniques? Is it clear how this work differs from previous contributions? Are other people (practitioners, researchers or commercial sector) likely to use these ideas or build on them? Are the results likely to have an impact on the research community or commercial sector?

Criterion 3: Scientific/Technical Content and Advances Beyond the State-of-the-Art

Score:
Excellent, very good, good, fair, poor

Interpretation:
Is the paper technically sound? Is related work adequately referenced? Are claims well-supported by theoretical analysis or experimental results? Is this a complete piece of work, or merely a position paper? Are the authors careful and honest about evaluating both the strengths and weaknesses of the work. Does the paper address a difficult problem in a better way than previous research? Does it advance the state of the art in a demonstrable way? Does it provide unique data, unique conclusions on existing data, or a unique theoretical or pragmatic approach?

Criterion 4: Quality and Clarity of the Presentation

Score:
Excellent, very good, good, fair, poor

Interpretation:
Is the paper clearly written? Is it well-organized? Does it adequately inform the reader? A superbly written paper provides enough information for the expert reader to reproduce its results may be assisted by cited supplementary material such as detailed explanations, derivations, code, and data.

Criterion 5: Comments for the Authors

Interpretation:
Provides an overall summary and detailed comments related to every evaluation criterion. If appropriate, suggestions to improve the work is included. It should be made sure that high marks are reflected by positive comments and low marks by negative comments. Offending comments and anything which could reveal reviewers identity should be avoided.