Search Results for "cost sensitive"
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Showing 10 open source projects for "cost sensitive"
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1
faasd
A lightweight & portable faas engine
...When you don't have the bandwidth to learn or manage Kubernetes. To deploy embedded apps in IoT and edge use-cases. To distribute applications to a customer or client. You have a cost sensitive project - run faasd on a 1GB VM for 5-10 USD / mo or on your Raspberry Pi. When you just need a few functions or microservices, without the cost of a cluster. -
2
Munder Difflin
local multi-agent harness
...Each supported CLI runs as a real terminal process with its own identity, workspace, and visual avatar. A central orchestrator called Michael routes tasks, resolves routine coordination, and escalates sensitive actions for human approval. Agents communicate through local mailboxes, share a blackboard, and retain long-term memory across sessions. The app provides live terminals, task management, Git tools, cost telemetry, and optional per-agent worktrees. It supports major coding agents, bring-your-own keys, local LLMs, and desktop builds for macOS, Windows, and Linux. -
3
Paddler
Open-source LLM load balancer and serving platform for hosting LLMs
...It supports running models locally through engines such as llama.cpp while distributing requests across multiple compute nodes to improve performance and reliability. The architecture is designed with privacy and cost control in mind, making it suitable for organizations that handle sensitive data or require predictable operational costs. Paddler also includes tools for monitoring, request buffering, and autoscaling integration so that deployments can adapt dynamically to changing workloads. A built-in administrative interface allows developers and operations teams to manage models, observe system performance, and test inference endpoints. -
4
Light-4J
A fast, lightweight and more productive microservices framework
Light means lightweight, lightning-fast and shedding light on how to program with modern Java SE for cloud-native deployment. I had been working on the Java EE platforms since early 2000 and suffered performance and productivity issues. In 2014, I realized that the IT industry was moving from Monolithic to Microservices and from on-premise data centers to the public clouds. To reduce the production cost for my applications, I need to find a lightweight platform that has a small memory... -
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5
FastVLM
This repository contains the official implementation of FastVLM
FastVLM is an efficiency-focused vision-language modeling stack that introduces FastViTHD, a hybrid vision encoder engineered to emit fewer visual tokens and slash encoding time, especially for high-resolution images. Instead of elaborate pruning stages, the design trades off resolution and token count through input scaling, simplifying the pipeline while maintaining strong accuracy. Reported results highlight dramatic speedups in time-to-first-token and competitive quality versus... -
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NKTg AI NKTg AI Logo Language Decoding System Measure semantic structure. Extract Core Content. Support better decisions. Overview NKTg AI is a deterministic Language Decoding System that measures the semantic structure of text to identify its Core Content. Unlike traditional AI summarization systems, NKTg AI does not generate new information or rewrite documents. Instead, it analyzes the internal semantic structure of a text and extracts the sentence that carries the highest...
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7
MUMAL2
Multivariate analysis of MS/MS data using ML techniques
Program described in the paper: MUMAL2: Improving sensitivity in shotgun proteomics using cost sensitive artificial neural networks and a threshold selector algorithm, 2016. By Fabio R. Cerqueira; Adilson M. Ricardo; Alcione P. Oliveira; Armin Graber; Christian Baumgartner. -
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Cost-sensitive Classifiers
Adaboost extensions for cost-sentive classification
Adaboost extensions for cost-sentive classification CSExtension 1 CSExtension 2 CSExtension 3 CSExtension 4 CSExtension 5 AdaCost Boost CostBoost Uboost CostUBoost AdaBoostM1 Implementation of all the listed algorithms of the cluster "cost-sensitive classification". They are the meta algorithms which requires base algorithms e.g. Decision Tree Moreover, Voting criteria is also required e.g. -
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EGNLA
Heterogeneous cluster for acceleration of linear algebra computations
This project deals with a new concept of the heterogeneous grid for acceleration of the numerical linear algebra computing. We design this grid with respect to maximal ratio between cost and computational power. It allows a parallelization of scientific codes with minimal programming effort. We also optimize grid concept to be less sensitive to network parameters. -
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10
clinicalStudyTracker
Clinical study tracker tracks case study members through activities.
Developed at Medical Research Council UK to meet a common clinical trial need to track various types of clinical data. Users log dates of completed tasks against participant ID. Simple, useable, reduces lost data! Makes graphical progress reports.
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