Skill UI

This powerful tool calculates detailed cryptocurrency tax obligations by processing transaction history from multiple exchanges. It supports various cost basis methods (FIFO, LIFO, HIFO) to accurately determine capital gains and losses. Key features include identifying staking, airdrop, and mining income, and generating comprehensive reports compatible with Form 8949, simplifying complex tax filing processes.

This skill automates the process of renting, managing, and terminating cloud GPU instances on vast.ai. It analyzes your AI/ML task—determining VRAM, required GPU count, and estimated runtime—and then searches for the most cost-effective and reliable GPU offers, presenting optimized options for your training workflow.

A comprehensive guide for researchers determining the best conference or journal for their signal processing contribution. It helps users identify the core signal-processing primitive (e.g., estimator, transform, representation) to correctly route work between major venues like ICASSP, Interspeech, ICIP, or general ML conferences.

This guide details the specialized review mechanics for top data mining conferences like ICDM. It covers the triple-blind process, the unique Accept-as-Short outcome, and the no-rebuttal posture. Learn how to structure your paper and interpret complex decision packets to maximize acceptance chances.

This skill offers a comprehensive project management framework for the end-to-end submission process of data mining research to major conferences like ICDM. It guides users through critical milestones, including topic selection, experimental design, abstract submission, and final camera-ready preparation. It emphasizes backward planning from the final deadline, addressing unique constraints such as no-rebuttal policies, short-paper contingencies, and strict page limits.

This guide models the rigorous, multi-cycle decision-making process for top-tier data mining conferences like KDD. It details how decisions are weighed, considering reviewer scores, rebuttal strategies, area chair synthesis, and specific criteria (e.g., reproducibility, ethics, industrial feasibility) across outcomes like Accept, Resubmit, and Reject. Essential for understanding academic publishing rigor.

A comprehensive pre-writing guide for researchers determining the optimal venue and track for a data science contribution. It outlines a two-stage decision process: first, assessing if the work aligns with the KDD focus on data regimes (scale, drift, heterogeneity); and second, selecting the correct track (Research, ADS, Datasets & Benchmarks, etc.) based on the strongest, most honest evidence available—especially emphasizing real-world deployment outcomes.

A comprehensive guide detailing the rigorous, multi-stage academic review process for top-tier data mining conferences (e.g., WSDM). It analyzes the hybrid single/double-blind architecture, the impact of no rebuttal phase, and the distinct perspectives of academic and industry reviewers. Use this guide to understand the requirements for writing and structuring submissions that maximize acceptance chances.