**arXiv ID:** 2102.01345 **Authors:** Etienne Dupuis, David Novo, Ian O'Connor, Alberto Bosio **Published:** 2021-02-02T06:45:56Z **Abstract:** The computational workload involved in Convolutional Neural Networks (CNNs) is typically out of reach for low-power embedded devices. There are a large number of approximation techniques to address this problem. These methods have hyper-parameters that need to be optimized for each CNNs using design space exploration (DSE). The goal of this work is to...
Scanned 9/11/2026
Install to Claude Code
Skills Directorynpx -y skills add hiyenwong/ai_collection --skill fast-exploration-of-weight-sharing-opportunities-for-cnn-compression --agent claude-codeInstalls into .claude/skills of the current project.
Are you the author of Fast Exploration Of Weight Sharing Opportunities For Cnn Compression?
Add the live security badge to your README — it updates automatically with every re-scan.
[](https://www.skillsdirectory.com/skills/hiyenwong-fast-exploration-of-weight-sharing-opportunities-f)More formats (shields.io, HTML) on the badges page.
# Fast Exploration of Weight Sharing Opportunities for CNN Compression
**arXiv ID:** 2102.01345
**Authors:** Etienne Dupuis, David Novo, Ian O'Connor, Alberto Bosio
**Published:** 2021-02-02T06:45:56Z
**Abstract:**
The computational workload involved in Convolutional Neural Networks (CNNs) is typically out of reach for low-power embedded devices. There are a large number of approximation techniques to address this problem. These methods have hyper-parameters that need to be optimized for each CNNs using design space exploration (DSE). The goal of this work is to demonstrate that the DSE phase time can easily explode for state of the art CNN. We thus propose the use of an optimized exploration process to drastically reduce the exploration time without sacrificing the quality of the output.
## Skill Description
This skill is generated from the arXiv paper: Fast Exploration of Weight Sharing Opportunities for CNN Compression (2102.01345).
## How to Use
[To be filled in by the user or by future automation]
## References
- [arXiv:2102.01345](http://arxiv.org/abs/2102.01345v1)
Is this your skill, or is something wrong with this listing? Request removal or report an issue. Author removals are honored within 72 hours.
No comments yet. Be the first to comment!
Playbook for creating and editing uCoz landing pages via MCP tools (`templates_tool`, `ftp_tool`, `modules_tool`). Use for tasks such as: "build a landing page", "update the homepage as a landing page", "create a promo page on the homepage", "add a lead form / menu / SEO to the homepage". Homepage: `page_list`, `page_get`; first publish — `page_update` with full `page_tmpl`; HTML edits after generation — `patch_template` (module_id=2, template_id=1), not `update_template`. Activate the mail f...
Interact with the Paperclip control plane API to manage tasks, coordinate with other agents, and follow company governance. Use when you need to check assignments, update task status, delegate work, post comments, set up or manage routines (recurring scheduled tasks), or call any Paperclip API endpoint. Do NOT use for the actual domain work itself (writing code, research, etc.) — only for Paperclip coordination.
Digital Audio Workstation usage, music composition, interactive music systems, and game audio implementation for immersive soundscapes.
Instantly.ai cold email outreach API - manage campaigns, leads, accounts, and analytics. Use for cold email automation, lead management, campaign creation/monitoring, and email account warmup.
Compress natural language memory files (CLAUDE.md, todos, preferences) into caveman format to save input tokens. Preserves all technical substance, code, URLs, and structure. Compressed version overwrites the original file. Human-readable backup saved as FILE.original.md. Trigger: /caveman-compress FILEPATH or "compress memory file"
