Classificazione degli algoritmi di Machine Learning: Regressione lineare, Classificazione e Clustering
Il Machine Learning ha grandi similitudini con l’ottimizzazione matematica, che fornisce metodi, ...
#classificazione #clustering #intelligenzaartificiale #MachineLearning #python #regressionelineare

https://bloginnovazione.it/machine-learning-algoritmi/3716/

'Clustering with Tangles: Algorithmic Framework and Theoretical Guarantees', by Solveig Klepper et al.

http://jmlr.org/papers/v24/21-1160.html

#cluster #clustering #tangle

Classificazione degli algoritmi di Machine Learning: Regressione lineare, Classificazione e Clustering
Il Machine Learning ha grandi similitudini con l’ottimizzazione matematica, che fornisce metodi, ...
#classificazione #clustering #intelligenzaartificiale #MachineLearning #python #regressionelineare

https://bloginnovazione.it/machine-learning-algoritmi/3716/

Weak supervision - Strong results! 💪

Smith and team introduce Perturbational Metric Learning (PeML) to extract biological relationships from noisy high-throughput perturbational datasets.

Team effort from preLighters Benjamin Dominik Maier & Anna Foix Romero – read their preLight! 👀

#preLight 👉 https://prelights.biologists.com/highlights/similarity-metric-learning-on-perturbational-datasets-improves-functional-identification-of-perturbations/

#bioinformatics #SystemsBiology #clustering #correlations #gsea #MachineLearning

Apart from #Wasserstein Distance (#EMD), other #metrics also play an important role in #MachineLearning tasks such as #clustering, #classification, and #InformationRetrieval. In this tutorial, you can find a discussion of five commonly used metrics: EMD, #KullbackLeiblerDivergence (KL Divergence), #JensenShannonDivergence (JS Divergence), #TotalVariationDistance (TV Distance), and #BhattacharyyaDistance.

🌎 https://www.fabriziomusacchio.com/blog/2023-07-28-probability_density_metrics/

Finding an off-the-shelf #clustering algorithm implementation that's able to work with sets as points, and Jaccard distance as the metric, has been a struggle. It's tested my knowledge of clustering algorithms and their implementations (which to be fair, isn't all that much yet). What I've learned so far:

- k-means clustering is designed and implemented only with Euclidean distances in mind.
- Hierarchical (either agglomerative or divisive) clustering can be used with arbitrary distance metrics.
- For clustering algorithms that can work with arbitrary metrics, scikit-learn's implementations all let you specify a custom metrics, but with a "precomputed" argument where you have to provide the full pairwise distance matrix. I'd rather not do that.
- Some implementations, like HDBSCAN, do have a Jaccard distance as an option, but they seem to operate on sets represented as bitsets. For my data, representing each set as a bitset is completely infeasible.
- It does look like you can also maybe pass in a custom distance function as callable to some implementations, but that still doesn't resolve the above bullet point.

Makes me want to read how some of these algorithms actually work.

Provably Personalized and Robust Federated Learning

https://openreview.net/forum?id=B0uBSSUy0G

#federated #cluster #clustering

The news came last month but I'm still feeling amused by it! My first Doc article in partnership with Carmelo Bastos-Filho, my Doctorate Advisor, entitled "Evaluating Multi-Level Clustering Approaches to Route Sales Agents" has been accepted for presentation at the IEEE LA-CCI 2023 (Latin American Conference in Computer Intelligence).

This great news gave me extra energy to go further. #lacci #computerintelligence #clustering #geneticalgorithm #metaheuristics

Tigase Advanced Clustering Strategy (#ACS) is our commercial #clustering solution, designed for typical XMPP installations, capable of #scaling easily to millions and beyond of online users without any limit on cluster nodes. In load tests, we included a user database with #100 #million accounts and an average roster size of up to 150, but the system can handle even more.

@geerlingguy @Raspberry_Pi @timebeatapp @adafruit

#WhatsMissing: A #RaspberryPi #clustering system that directly uses the #PCIe links and/or allows using the #CM4 / #CM3 as "coporcessors" or rather "co-nodes" that get interfaced like the #Apple #Afterburner card but can run on their own...

Think #VT69 meets #PiKVM & #PiBlade...

Referenced link: https://www.iotforall.com/exploring-the-basics-of-mqtt-broker-clustering-an-introduction
Discuss on https://discu.eu/q/https://www.iotforall.com/exploring-the-basics-of-mqtt-broker-clustering-an-introduction

Originally posted by IoT For All / @iotforall: http://nitter.platypush.tech/iotforall/status/1674402346376257537#m

#MQTTbroker #clustering, simply put, is a group of #MQTT brokers working together to ensure continuity and high availability. Learn more from @EMQTech about its key benefits. https://www.iotforall.com/exploring-the-basics-of-mqtt-broker-clustering-an-introduction

5 Minuten Zeit? Wir haben für das Modul Data Science einen Fragebogen erstellt, um an realen Daten Methodiken zu erlernen. Die Das Ziel ist es, einen Student Matcher zu erstellen, der abhängig von Interessen und Charaktereigenschaften passende Studierende vorschlägt (wenn nicht gewünscht, natürlich auch vollkommnen anonym).
Dauert nicht lang, tut nicht weh und hilft uns weiter! 😎

#data_science #nlp #clustering #machine_learning #dropna #hsd

https://docs.google.com/forms/d/e/1FAIpQLSfUvs0F2VifaLT3dKKlzzAVvVrx0wiywD9hrq0T-uYFxW3Szg/viewform

'Consistent Model-based Clustering using the Quasi-Bernoulli Stick-breaking Process', by Cheng Zeng, Jeffrey W Miller, Leo L Duan.

http://jmlr.org/papers/v24/22-0436.html

#clusters #clustering #mixture

'Selective inference for k-means clustering', by Yiqun T. Chen, Daniela M. Witten.

http://jmlr.org/papers/v24/22-0371.html

#clustering #clusters #sequencing

'Escaping The Curse of Dimensionality in Bayesian Model-Based Clustering', by Noirrit Kiran Chandra, Antonio Canale, David B. Dunson.

http://jmlr.org/papers/v24/21-1276.html

#clustering #clusters #cluster

Multi-dimensional concept discovery (MCD): A unifying framework with completeness guarantees

Johanna Vielhaben, Stefan Bluecher, Nils Strodthoff

Action editor: Hsuan-Tien Lin.

https://openreview.net/forum?id=KxBQPz7HKh

#concepts #concept #clustering

HIRING: Data Scientist / London, United Kingdom https://ai-jobs.net/J51875/ #AI #MachineLearning #DataJobs #MLjobs #bigdata #DataScience #AIjobs #AIcareers #hiringnow #London #UnitedKingdom #Athena #AWS #Clustering #DeepLearning #Engineering #MachineLearning #PowerBI #Python #R

Deep Plug-and-Play Clustering with Unknown Number of Clusters

An Xiao, Hanting Chen, Tianyu Guo, QINGHUA ZHANG, Yunhe Wang

Action editor: Bo Han.

https://openreview.net/forum?id=6rbcq0qacA

#clusters #clustering #classified

HIRING: Research Scientist (Computational Biology) / Toronto, Ontario https://ai-jobs.net/J48634/ #AI #MachineLearning #DataJobs #MLjobs #bigdata #DataScience #AIjobs #AIcareers #hiringnow #Toronto #Ontario #Bayesian #Biology #Clustering #ComputerScience #Engineering #Mathematics

HIRING: Senior Data Scientist / Tokyo, Japan https://ai-jobs.net/J48635/ #AI #MachineLearning #DataJobs #MLjobs #bigdata #DataScience #AIjobs #AIcareers #hiringnow #Tokyo #Japan #Banking #Clustering #ComputerScience #Consulting #Linux #MachineLearning #Mathematics #Physics #R