github.com/p-lambda/wilds
p-lambda/wilds
A machine learning benchmark of in-the-wild distribution shifts, with data loaders, evaluators, and default models. (⭐ 592)
arxiv.org/abs/2210.12369v1
Explanation Shift: Detecting distribution shifts on tabular data via the explana…
As input data distributions evolve, the predictive performance of machine learning models tends to deteriorate. In the past, predictive performance was considered the key indicator to monitor. However, explanation aspects have come to attention withi...
arxiv.org/abs/2207.14650v3
SYNTA: A novel approach for deep learning-based image analysis in muscle histopa…
Artificial intelligence (AI), machine learning, and deep learning (DL) methods are becoming increasingly important in the field of biomedical image analysis. However, to exploit the full potential of such methods, a representative number of experimen...
en.wikipedia.org/wiki/Windmill
Windmill - Wikipedia
windmill is a machine operated by the force of wind acting on vanes or sails to mill grain (gristmills), pump water, generate electricity, or drive other machinery
www.reddit.com/r/MilitaryPorn/comments/1ljzce7/german_soldier_carries_two_mg42_machine_guns/
German soldier carries two MG-42 machine guns, during the surrender of the 512th…
https://x.com/asummerof44/status/1937186041049280887?s=46 ...
arxiv.org/abs/2410.10894v1
COME: Test-time adaption by Conservatively Minimizing Entropy
Machine learning models must continuously self-adjust themselves for novel data distribution in the open world. As the predominant principle, entropy minimization (EM) has been proven to be a simple yet effective cornerstone in existing test-time ada...
github.com/chirag1992m/Algorithmic-Trading-Challenge---Kaggle
chirag1992m/Algorithmic-Trading-Challenge---Kaggle
Algorithmic Trading Challenge implemented as part of the term project for Foundations of Machine Learning at NYU Courant in Fall 2016 (http://cs.nyu.edu/courses/fall16/CSCI-GA.2566-001/index.html/) (⭐ 27)
arxiv.org/abs/2407.15389v1
Poisoning with A Pill: Circumventing Detection in Federated Learning
Without direct access to the client's data, federated learning (FL) is well-known for its unique strength in data privacy protection among existing distributed machine learning techniques. However, its distributive and iterative nature makes FL inher...
arxiv.org/abs/2006.03970v1
An Efficient Semi-smooth Newton Augmented Lagrangian Method for Elastic Net
Feature selection is an important and active research area in statistics and machine learning. The Elastic Net is often used to perform selection when the features present non-negligible collinearity or practitioners wish to incorporate additional kn...
arxiv.org/abs/2504.05618v1
Technical Report: Full Version of Analyzing and Optimizing Perturbation of DP-SG…
Differential privacy (DP) has become a prevalent privacy model in a wide range of machine learning tasks, especially after the debut of DP-SGD. However, DP-SGD, which directly perturbs gradients in the training iterations, fails to mitigate the negat...
arxiv.org/abs/2409.10081v1
Messy Code Makes Managing ML Pipelines Difficult? Just Let LLMs Rewrite the Code…
Machine learning (ML) applications that learn from data are increasingly used to automate impactful decisions. Unfortunately, these applications often fall short of adequately managing critical data and complying with upcoming regulations. A technica...
arxiv.org/abs/2602.02671v1
MARA: Continuous SE(3)-Equivariant Attention for Molecular Force Fields
Machine learning force fields (MLFFs) have become essential for accurate and efficient atomistic modeling. Despite their high accuracy, most existing approaches rely on fixed angular expansions, limiting flexibility in weighting local geometric inter...
www.bing.com/ck/a?!&&p=9cebdccd3b4ad285c3a2445cc8e62453d7d05c000ae6ad3f6e5a4f2282f68bceJmltdHM9MTc3MjQ5NjAwMA&ptn=3&ver=2&hsh=4&fclid=10a07e97-bc30-6b6b-05b8-6985bd856aff&u=a1aHR0cHM6Ly93d3cubm9ydGhlcm5pbHBvdHRlcnl0b3VyLmNvbS9zYW5kd2ljaA&ntb=1
Sandwich - Northern Illinois Pottery Tour
Cory grew up at the foot of a sewing machine. Everyday she would watch her mother break down design ideas into pattern pieces that fit together into 3d creations. Cory embraces this method of creation to …
en.wikipedia.org/wiki/Mechanical_advantage
Mechanical advantage - Wikipedia
Mechanical advantage is a measure of the force amplification achieved by using a tool, mechanical device or machine system. The device trades off input
github.com/giotto-ai/giotto-tda
giotto-ai/giotto-tda
A high-performance topological machine learning toolbox in Python (⭐ 974)
www.arxiv.org/abs/2407.09468
Guide to Machine Learning with Geometric, Topological, and Algebraic Structures
Points: 176 | Comments: 27 | Author: johmathe
www.bing.com/ck/a?!&&p=aa4fdb33bcb7f40348597c47063d52ef4e4e06b96131fa91c56feee742321c76JmltdHM9MTc3MjQ5NjAwMA&ptn=3&ver=2&hsh=4&fclid=00e301fd-31a0-690d-2213-16ef30fe68ce&u=a1aHR0cHM6Ly93d3cuZGVmaW5pdGlvbnMubmV0L2RlZmluaXRpb24vT0xE&ntb=1
What does OLD mean? - Definitions.net
If you were looking for the Dexys Midnight Runners song called Old, see here."Old" is a song recorded by American heavy metal band Machine Head. It was released as a single in two different versions.
arxiv.org/abs/2310.18542v3
End-to-end Feature Selection Approach for Learning Skinny Trees
We propose a new optimization-based approach for feature selection in tree ensembles, an important problem in statistics and machine learning. Popular tree ensemble toolkits e.g., Gradient Boosted Trees and Random Forests support feature selection po...
arxiv.org/abs/2011.04389v2
EDEN: Multimodal Synthetic Dataset of Enclosed GarDEN Scenes
Multimodal large-scale datasets for outdoor scenes are mostly designed for urban driving problems. The scenes are highly structured and semantically different from scenarios seen in nature-centered scenes such as gardens or parks. To promote machine...
github.com/pbharrin/machinelearninginaction
pbharrin/machinelearninginaction
Source Code for the book: Machine Learning in Action published by Manning (⭐ 2399)