Thank you so much, I appreciate it !
Check out the official release of the paper at : https://x.com/swann_bessa/status/2120200714630594911?a=GlH1k...
Minimizing Mean Squared Error between a dataset and a given number of centroids. In practice it can be used in deduplication, data curation, compression, Vector Search, and many others. It remains one of the most used…
Yes, right. That's more rigorous to say it like that. Note that at the scales of the paper it is in practice impossible with today's computational means.
BBD-tree is only for low dimensions because it suffers from the curse of dimensionality. Note that BBD-tree is orthogonal to e-means, they can combined very straightforwardly just like it is combined with k-means. The…
Careful tuning is provided by the scaling laws, so you don't need to set the hyperparameters yourself. I am quite skeptical about setting alpha=-0.1 tbh, but I'm curious to see what happens too lol.
Hi, I'm Swann Bessa, the author of the e-means paper. FYI, we get very good results on ARI and NMI on ImageNet and also synthetic data. We will release them in a later revision. If you have another distribution you have…
Hi, I'm the author of e-means. If you can send them, I would love to hear about the results you got !
Thanks for your kind responses. I'd be very interested if they have a reference. If you feel like it, you can always send me an e-mail at swann@meta.com with the references. I'll add them to my benchmarks. The fewer…
Hi, I'm Swann Bessa, the author of e-means. Thanks for your questions. The answer is that e-means consistently finds a better solution than Lloyd. It's impossible to know if it's the global minimum or not. Finding the…
Thanks for the feedback, thatsabadlook. This is my first PhD work so I’m really happy to hear that.
Hi, I’m the author of the paper. Thank you for trying e-means and detailing your results. This kind of results of e-means at 2 epochs compared with Lloyd is the typical kind of acceleration we want people to know about.…
Thank you for trying e-means, let me know if you have any questions !
Hi shiandow, I'm Swann Bessa, the author of the paper. The fact that the update rule keeps the centroid within the convex hull is indeed very important. If you look at Appendix E, the gradient descent methods don't have…
Hi, I'm Swann Bessa, the author of the paper. If you want, you can also play with it now in your browser at : https://e-means.github.io/playground.html Feel free to ask any questions, I'll be happy to answer.
Hi bashhq_r, I'm Swann Bessa, the author of the e-means paper. If you look at our paper on arxiv (https://arxiv.org/abs/2611.09501), Table 2, the hyperparameters laws have been validated on 4 datasets outside of the…
Hi Thomashuet, I'm Swann Bessa, the author of e-means. The goal of e-means is to be a drop-in replacement for k-means. It solves the exact same problem, with the exact same inputs and delivers better centroids and…
It's not a new kind of clustering. It solves exactly the same problem as k-means (minimize the mean squared distance to k centroids), returns the same thing (k centroids and an assignment), and has the same inputs (k…
Hi, I'm Swann Bessa, the author of e-means. Thanks for trying e-means. If I may I'd like to come back on a few of the points you made. "e-means wins by needing fewer passes over a huge dataset": the improvements of…
Why would you use run normal k-means if e-means gives lower loss and reliably goes much faster ? If you don't believe it you can try e-means at https://e-means.github.io/playground.html
Hi oofbey, If you look at Figure 3 of our paper, the baseline "Sculley" is precisely the well tuned mini batch kmeans of scikit-learn. We swept on batch sizes and threshold for dead cluster reassignment (Batch size:…
Hi saagarjha, I'm Swann Bessa, the author of the paper. Thank you for your message on the work. If I may I'd like to address a few points. "People have been doing minibatch k-means for a while, including with an EMA…
Thank you so much, I appreciate it !
Check out the official release of the paper at : https://x.com/swann_bessa/status/2120200714630594911?a=GlH1k...
Minimizing Mean Squared Error between a dataset and a given number of centroids. In practice it can be used in deduplication, data curation, compression, Vector Search, and many others. It remains one of the most used…
Yes, right. That's more rigorous to say it like that. Note that at the scales of the paper it is in practice impossible with today's computational means.
BBD-tree is only for low dimensions because it suffers from the curse of dimensionality. Note that BBD-tree is orthogonal to e-means, they can combined very straightforwardly just like it is combined with k-means. The…
Careful tuning is provided by the scaling laws, so you don't need to set the hyperparameters yourself. I am quite skeptical about setting alpha=-0.1 tbh, but I'm curious to see what happens too lol.
Hi, I'm Swann Bessa, the author of the e-means paper. FYI, we get very good results on ARI and NMI on ImageNet and also synthetic data. We will release them in a later revision. If you have another distribution you have…
Hi, I'm the author of e-means. If you can send them, I would love to hear about the results you got !
Thanks for your kind responses. I'd be very interested if they have a reference. If you feel like it, you can always send me an e-mail at swann@meta.com with the references. I'll add them to my benchmarks. The fewer…
Hi, I'm Swann Bessa, the author of e-means. Thanks for your questions. The answer is that e-means consistently finds a better solution than Lloyd. It's impossible to know if it's the global minimum or not. Finding the…
Thanks for the feedback, thatsabadlook. This is my first PhD work so I’m really happy to hear that.
Hi, I’m the author of the paper. Thank you for trying e-means and detailing your results. This kind of results of e-means at 2 epochs compared with Lloyd is the typical kind of acceleration we want people to know about.…
Thank you for trying e-means, let me know if you have any questions !
Hi shiandow, I'm Swann Bessa, the author of the paper. The fact that the update rule keeps the centroid within the convex hull is indeed very important. If you look at Appendix E, the gradient descent methods don't have…
Hi, I'm Swann Bessa, the author of the paper. If you want, you can also play with it now in your browser at : https://e-means.github.io/playground.html Feel free to ask any questions, I'll be happy to answer.
Hi bashhq_r, I'm Swann Bessa, the author of the e-means paper. If you look at our paper on arxiv (https://arxiv.org/abs/2611.09501), Table 2, the hyperparameters laws have been validated on 4 datasets outside of the…
Hi Thomashuet, I'm Swann Bessa, the author of e-means. The goal of e-means is to be a drop-in replacement for k-means. It solves the exact same problem, with the exact same inputs and delivers better centroids and…
It's not a new kind of clustering. It solves exactly the same problem as k-means (minimize the mean squared distance to k centroids), returns the same thing (k centroids and an assignment), and has the same inputs (k…
Hi, I'm Swann Bessa, the author of e-means. Thanks for trying e-means. If I may I'd like to come back on a few of the points you made. "e-means wins by needing fewer passes over a huge dataset": the improvements of…
Why would you use run normal k-means if e-means gives lower loss and reliably goes much faster ? If you don't believe it you can try e-means at https://e-means.github.io/playground.html
Hi oofbey, If you look at Figure 3 of our paper, the baseline "Sculley" is precisely the well tuned mini batch kmeans of scikit-learn. We swept on batch sizes and threshold for dead cluster reassignment (Batch size:…
Hi saagarjha, I'm Swann Bessa, the author of the paper. Thank you for your message on the work. If I may I'd like to address a few points. "People have been doing minibatch k-means for a while, including with an EMA…