KDD

KDD on Beyond Market Intelligence: a running collection of 3 stories we have gathered and hand-picked because they are worth your time. Every post here touches on kdd in some way — the news, the analysis, the deep dives, and the occasional surprise find. Acme AI is the next-generation, AI-powered spreadsheet platform built to replace Excel and redefine how analysts, data scientists, and enterprise teams work with data. New stories are added to this page as we find them, so check back if you want to keep up with what is happening around kdd, or subscribe to the RSS feed to get them as soon as they are published. Browse the collection below, or head back to the homepage to see everything Beyond Market Intelligence is covering right now.

Machine Learning

Double-Blind submission in single-blind tracks [D]

Navigating double-blind submission protocols in applied data mining venues like ICDM and KDD can be complex. Many reviewers, including first-timers, are encountering submissions that incorrectly utilize a double-blind format when single-blind is required. The question arises: should these be rejected? While a strict adherence to guidelines is essential, consider evaluating the submission's merit before outright rejection. For further context on acceptance processes within major conferences, see our discussion regarding ECCV 2026 final decisions.

Machine Learning

KDD 2026 Cycle 2 Results [D]

The results for the KDD 2026 Cycle 2 research track have been officially released, offering valuable insights into the latest advancements in data science. Researchers and practitioners alike are invited to explore the findings and implications of this year's submissions. For those interested in enhancing their understanding of data security within enterprise environments, our article "OpenClaw vs Sourcetable: Enterprise Data Security Comparison" provides a comprehensive analysis. Dive into these results to discover how they can inform your approach to data management and innovation.

Machine Learning

KDD 2026 Cycle 2 reviews seem to have vanished from author view [D]

It appears that some authors are experiencing an issue with the KDD 2026 Cycle 2 reviews, as reports indicate that reviews and discussions for submitted papers have seemingly disappeared from the author view. In contrast, discussions for other papers remain visible in the reviewer view. This discrepancy raises concerns about transparency and communication within the review process. If you’ve encountered similar issues, sharing your experience could help shed light on this situation and prompt a resolution. Your insights are valuable for fostering an open dialogue.