Hacker News: herrherr

Improving My Engine Sound Simulator with Real Data [video]

herrherr — Fri, 07 Nov 2025 14:25:33 +0000

Article URL: https://www.youtube.com/watch?v=sUdnJTC2w9I

Comments URL: https://news.ycombinator.com/item?id=45846706

Points: 1

# Comments: 0

Sequential Diagnosis with Language Models

herrherr — Mon, 07 Jul 2025 09:09:16 +0000

Article URL: https://arxiv.org/abs/2506.22405

Comments URL: https://news.ycombinator.com/item?id=44488254

Points: 4

# Comments: 0

Culture and business: Let's do things differently. It can be done

herrherr — Tue, 19 Mar 2024 12:40:30 +0000

Article URL: https://www.dominik-schwarz.net/it-can-be-done/

Comments URL: https://news.ycombinator.com/item?id=39755097

Points: 4

# Comments: 0

New comment by herrherr in "The Anatomy of SaaS Pricing Strategy (2017) [pdf]"

herrherr — Thu, 10 Nov 2022 14:14:02 +0000

As your products and services are targeted towards bigger clients, do you have any advice for smaller companies on who to talk to regarding pricing?

New comment by herrherr in "Voxel art"

herrherr — Tue, 31 May 2016 12:23:13 +0000

Any hints on where to start?

Drake, a kind of ‘make for data’

herrherr — Mon, 12 Oct 2015 15:12:51 +0000

Article URL: https://github.com/Factual/drake

Comments URL: https://news.ycombinator.com/item?id=10375001

Points: 5

# Comments: 0

Printing a wall-sized world map and what I've learned from it

herrherr — Thu, 30 Apr 2015 11:21:28 +0000

Article URL: http://www.dominik-schwarz.net/potpourri/worldmap/

Comments URL: https://news.ycombinator.com/item?id=9464348

Points: 919

# Comments: 220

Quantifiably unsane: Vessyl

herrherr — Thu, 26 Jun 2014 06:50:37 +0000

Article URL: https://scottlocklin.wordpress.com/2014/06/24/quantifiably-unsane-vessyl/

Comments URL: https://news.ycombinator.com/item?id=7948413

Points: 1

# Comments: 0

New comment by herrherr in "Parallel Locality Sensitive Hashing"

herrherr — Sat, 31 May 2014 07:35:06 +0000

First of all, thanks for open sourcing lmdb :)

The biggest problem currently is actually degrading performance, although I'm almost 100% sure that this isn't caused by lmdb itself, but rather by the bindings I've tried.

In the end, doing it directly in C is probably the only thing that will actually work.

New comment by herrherr in "Parallel Locality Sensitive Hashing"

herrherr — Fri, 30 May 2014 20:17:07 +0000

Actually I'm also using lmdb (together with Python/numpy) :) Added an email address to my profile, would be happy to exchange some experiences.

New comment by herrherr in "Parallel Locality Sensitive Hashing"

herrherr — Fri, 30 May 2014 19:56:02 +0000

I've been trying for weeks now to get a system running that can handle larger than RAM datasets and returns queries in an acceptable time. It's running ok now but far from optimal (size of DB is ~100 GB and it contains a few hundred million entries).

Does anyone here have experience with any implementations (such as likelike, lshkit, etc.) and can recommend something that can handle larger sets? All the implementations I have found were either not maintained, old, not running or not suitable for production use.

Will definitely take a look at the paper but unfortunately it's always a very long way from here to an actual implementation (there is no code published as far as I could see).

New comment by herrherr in "Ask HN: Your favorite YouTube channels?"

herrherr — Fri, 18 Apr 2014 18:00:47 +0000

Currently without a doubt: https://www.youtube.com/user/mathematicalmonk

An extensive series about machine learning (100+ videos).

Extensive video series about Machine Learning

herrherr — Tue, 15 Apr 2014 18:43:46 +0000

Article URL: https://www.youtube.com/user/mathematicalmonk

Comments URL: https://news.ycombinator.com/item?id=7593585

Points: 2

# Comments: 0

New comment by herrherr in "Detecting duplicate images with Python"

herrherr — Thu, 03 Apr 2014 13:59:28 +0000

I think you are on the right track there.

The thing is though, you won't have difficulties finding papers on those topics. However, you will probably not have any luck finding many concrete and practical implementations that you could look at.

So it's a far way from reading the papers to having something working.

If you find something, please let me know.

New comment by herrherr in "Detecting duplicate images with Python"

herrherr — Thu, 03 Apr 2014 12:37:49 +0000

We are currently using perceptual hashes (e.g. phash.org) to do hundreds of thousands of image comparisons per day.

As mentioned in another comment, you really have to test different hashing algorithms to find one that suits your needs best. In general though, I think it is in most cases not necessary to develop an algorithm from scratch :)

For us, the much more challenging part was/is to develop a system that can find similar images quickly. If you are interested in things like that have a look at VP/MVP data structures (e.g. http://pnylab.com/pny/papers/vptree/vptree/, http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.43.7...).