Notes

• LoRA[note]

  • llm

  2025 Feb 24
• Knapsack[note]

  • algorithms

  2023 Oct 20
• Gradient Through Concatenation[note]

  • computational-graph

  2023 Oct 02
• Gradient Boosting[note]

  • machine-learning

  2022 Apr 14
• Attribute Selection in Decision Trees[note]

  • machine-learning

  2022 Apr 14
• Reservoir Sampling[note]

  • probability, distributed-computing

  2022 Apr 01
• Quick Select[note]

  • algorithms

  2022 Mar 14
• Canny Edge detector[note]

  • computer-vision

  2022 Mar 12
• Histogram of Oriented Gradients[note]

  • computer-vision

  2022 Mar 12
• KKT conditions and Lagrange multipliers[note]

  • optimisation

  2022 Mar 11
• BFGS[note]

  • optimisation

  2022 Mar 11
• Bias and Variance[note]

  • machine-learning

  2022 Mar 10
• Statistics from Streaming Data[note]

  • algorithms, statistics

  2022 Feb 16
• Newton's Method[note]

  • optimisation

  2022 Jan 04
• Common Optimisers[note]

  • machine-learning, deep-learning

  2021 Oct 24
• Focal Loss[note]

  • machine-learning, deep-learning

  2021 Oct 10
• RankNet and LambdaRank[note]

  • ranking, search

  2021 Sep 25
• Movie Reviews and Gradient Descent[note]

  • applied-ml

  2021 Apr 13
• Softmax Classifier[note]

  • machine-learning

  2020 Jan 13
• Gradient Through Addition with Broadcasting[note]

  • computational-graph

  2018 Sep 18
• Linear Classifiers[note]

  • machine-learning

  2018 Feb 18
• Bayes Error[note]

  • machine-learning

  2018 Feb 11