2021 Algorithm Supervised Learning 
Data Science Dojo
FEBRUARY 15, 2023
Ultimately, we can use two or three vital tools: 1) [either] a simple checklist, 2) [or,] the interdisciplinary field of project-management, and 3) algorithms and data structures. In addition to the mindful use of the above twelve elements, our Google-search might reveal that various authors suggest some vital algorithms for data science.
BAIR
APRIL 20, 2022
A demonstration of the RvS policy we learn with just supervised learning and a depth-two MLP. It uses no TD learning, advantage reweighting, or Transformers! Offline reinforcement learning (RL) is conventionally approached using value-based methods based on temporal difference (TD) learning.
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ML @ CMU
SEPTEMBER 15, 2023
At test time, we optimize only the reconstruction loss Our contributions are as follows: (i) We present an algorithm that significantly improves scene decomposition accuracy for out-of-distribution examples by performing test-time adaptation on each example in the test set independently. (ii) iv) Semantic-NeRF (Zhi et al.,
AWS Machine Learning Blog
DECEMBER 7, 2023
Amazon Forecast is a fully managed service that uses machine learning (ML) algorithms to deliver highly accurate time series forecasts. Calculating courier requirements The first step is to estimate hourly demand for each warehouse, as explained in the Algorithm selection section.
DrivenData Labs
JUNE 14, 2023
Accurate and performant algorithms are critical in flagging and removing inappropriate content. Self-supervision: As in the Image Similarity Challenge , all winning solutions used self-supervised learning and image augmentation (or models trained using these techniques) as the backbone of their solutions.
AWS Machine Learning Blog
SEPTEMBER 10, 2024
The final phase improved on the results of HEEC and PORPOISE—both of which have been trained in a supervised fashion—using a foundation model trained in a self-supervised manner, namely Hierarchical Image Pyramid Transformer (HIPT) ( Chen et al., CLAM extracts features from image patches of size 256×256 using a pre-trained ResNet50.
Hacker News
MARCH 25, 2022
They’re driving a wave of advances in machine learning some have dubbed transformer AI. Stanford researchers called transformers “foundation models” in an August 2021 paper because they see them driving a paradigm shift in AI. Transformers Replace CNNs, RNNs.
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