Foundations and Trends in Machine Learning Template
Get your Foundations and Trends in Machine Learning paper right the first time: a ready-made structure with the right abstract and citations, so editors see your science, not formatting slips.
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How to Use the Foundations and Trends in Machine Learning Template | A Step-by-Step Guide
Authored by Sumalatha Gangadhar | Published on 11 August, 2026
Submitting to Foundations and Trends in Machine Learning goes smoothly when your draft already matches the journal's own rules. Editors screen new manuscripts against the Foundations and Trends in Machine Learning guide for authors before peer review, so formatting, structure, and required statements should be right on the first draft rather than repaired during upload. This template sets that structure up for you.
What is the Foundations and Trends in Machine Learning Template?
It is a manuscript shell aligned to Foundations and Trends in Machine Learning. It covers front matter, the abstract the journal expects, a body organized to the journal's article types, and a reference list in the journal's required style. Confirm current scope and article types on the Foundations and Trends in Machine Learning journal page before you draft.
What's actually in a Foundations Trends Machine Learning submission:
Prepare the title, authors, affiliations, and ORCID iDs. Write the abstract to the journal's rule and word limit, organize the body to the article type, and apply the required reference style from the first citation. Complete every declaration (ethics, competing interests, funding, data availability) the Foundations and Trends in Machine Learning guide for authors lists, and cite figures and tables in order.
What separates a clean submission from one that gets kicked back:
The common failure modes are formatting or reference style that does not match the guide for authors, missing required statements, and an incomplete portal checklist. Clear all three against the Foundations and Trends in Machine Learning guide for authors before you submit.
What does this Foundations and Trends in Machine Learning Template include?
The shell mirrors what editorial staff check first: article-type fit, the abstract rules, required declarations, and the journal's reference style. For more detail see the author resources. When your draft is ready, upload it through the journal's editorial office.
Steps to Use This Template with SciSpace Agent
- Click Start Writing on this page. The SciSpace Agent prompt screen opens with the template loaded.
- Use the loaded template, or upload a version your group already uses for Foundations Trends Machine Learning.
- Edit the prompt with your topic and article type, and note any requirement from the Foundations and Trends in Machine Learning guide for authors.
- Run the prompt. The agent drafts into the correct structure and reference style.
- Use View Outputs to verify required statements and formatting are present.
- Export and submit through the journal's editorial office.
Foundations and Trends in Machine Learning Template Structure at a Glance
| Element | Foundations Trends Machine Learning requirement |
|---|---|
| Abstract | Structured abstract required with 4 mandatory fields (100 word limit to each field): Purpose, Design/methodology/approach, Findings, and Originality. Optional fields (also 100 word limit each) may include: Research limitations/implications, Practical implications, and Social implications. The abstract should describe what the paper reviews and for whom it is of interest |
| Main text | Long review and tutorial papers of approximately 100 pages (± 100 pages). Literature surveys and original research papers do not fall within the journal's aims. Monographs should provide an in-depth, self-contained treatment of topics with significant mathematical detail |
| Declarations | Ethics approval/consent as applicable; competing interests; funding; data availability |
| Figures/tables | Publication-ready; cited in order |
| Supplemental | Upload separately when used |
| Keywords | Authors are free to assign any keywords and/or subject-specific keywords such as JEL codes to the article. No specific count or range is mandated |
| References | Harvard referencing style. References should be in alphabetical order with complete information including DOI when available. In-text citations: single author (Adams, 2006), two authors (Adams and Brown, 2006), three or more authors (Adams et al., 2006) with 'et al' in italics. Page numbers written in full (175-179, not 175-9) |
| Peer review | Single-anonymous peer review (also called single-blind peer review). The full draft paper is subject to a reviewing process to ensure quality standards and balance before being finally accepted |
| Submission | Email: dkielty@emerald.com |
Quick Tips for Using the Foundations and Trends in Machine Learning Template
Read the Foundations and Trends in Machine Learning guide for authors once before drafting and once before upload. Draft the abstract after results are stable. Set the reference style before adding citations. Keep a cover letter that states your contribution and fit to Foundations and Trends in Machine Learning in under a page.
Best Practices
Skim two or three recent Foundations Trends Machine Learning papers to calibrate depth and figure style. Make the novelty clear in the first two pages. Deposit data and code when the policy on the Foundations and Trends in Machine Learning journal page requires it. Disclose any preprint or conference version with identifiers in the cover letter.
Before You Submit: Final Check
Do one focused pass against the Foundations and Trends in Machine Learning guide for authors: scope, length, reference style, required declarations, and figure quality. Then submit through the journal's editorial office.
