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関連する概念動画

Distillation: Vapor–Liquid Equilibria01:01

Distillation: Vapor–Liquid Equilibria

4.7K
Distillation is a separation technique that takes advantage of the boiling point properties of disparate elements in a mixture. To perform distillation, we begin by heating a miscible mixture of two liquids with a significant difference in boiling points (at least 20°C). As the solution heats up and reaches the bubble point of the more volatile component, some molecules of the more volatile component transition into the gas phase and travel upward into the condenser, which is a glass tube...
4.7K
pH Scale02:41

pH Scale

80.5K
Hydronium and hydroxide ions are present both in pure water and in all aqueous solutions, and their concentrations are inversely proportional as determined by the ion product of water (Kw). The concentrations of these ions in a solution are often critical determinants of the solution’s properties and the chemical behaviors of its other solutes. Two different solutions can differ in their hydronium or hydroxide ion concentrations by a million, billion, or even trillion times. A common means of...
80.5K
Scaling01:26

Scaling

601
In designing and analyzing filters, resonant circuits, or circuit analysis at large, working with standard element values like 1 ohm, 1 henry, or 1 farad can be convenient before scaling these values to more realistic figures. This approach is widely utilized by not employing realistic element values in numerous examples and problems; it simplifies mastering circuit analysis through convenient component values. The complexity of calculations is thereby reduced, with the understanding that...
601
Thermometers and Temperature Scales01:22

Thermometers and Temperature Scales

7.8K
Any physical property that depends consistently and reproducibly on temperature can be used as the basis of a thermometer. For example, volume increases with temperature for most substances. This property is the basis for the common alcohol thermometer and the original mercury thermometers. Other properties used to measure temperature include electrical resistance, color, and the emission of infrared radiation.
As many physical properties depend on temperature, the variety of thermometers is...
7.8K
Labeling Emotion01:20

Labeling Emotion

745
Emotional labeling is a cognitive process that involves identifying and naming one's emotions, such as anger, fear, happiness, or sadness. It allows individuals to recognize and express their internal emotional states, a critical aspect of emotional regulation and communication. Labeling emotions requires more than mere recognition; it also involves drawing upon memory and contextual cues to understand the current situation and apply a corresponding emotional label. For instance, feeling...
745
Gas Thermometers and the Kelvin Scale01:22

Gas Thermometers and the Kelvin Scale

6.5K
The definition of temperature in terms of molecular motion suggests that there should be a lowest possible temperature, where the average kinetic energy of molecules is zero (or the minimum allowed by quantum mechanics). Experiments confirm the existence of such a temperature, called absolute zero. An absolute temperature scale is one whose zero point is absolute zero. Such scales are convenient in science because several physical quantities, such as the volume of an ideal gas, are directly...
6.5K

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A User-friendly and Powerful R Analysis of Large-scale Datasets
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A User-friendly and Powerful R Analysis of Large-scale Datasets

Published on: November 4, 2025

403

大規模なデータセットの蒸留のためのソフトラベル剪定と定量化.

Lingao Xiao, Yang He

    IEEE transactions on pattern analysis and machine intelligence
    |February 13, 2026
    PubMed
    まとめ
    この要約は機械生成です。

    データセットの蒸留は,大きなソフトラベルによる貯蔵上の課題に直面しています. LPQLDの方法は,ラベルのサイズを大幅に削減し,ImageNet.Netのような大規模なデータセットの精度を向上させます.

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    Scaled Anatomical Model Creation of Biomedical Tomographic Imaging Data and Associated Labels for Subsequent Sub-surface Laser Engraving SSLE of Glass Crystals
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    Label-Free Immunoprecipitation Mass Spectrometry Workflow for Large-scale Nuclear Interactome Profiling
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    科学分野:

    • コンピュータビジョン コンピュータビジョン
    • 機械学習 (Machine Learning) とは,機械学習 (Machine Learning) について学ぶことです.
    • データ圧縮 データ圧縮

    背景:

    • 大規模なデータセットの蒸留は,補助的なソフトラベルを大量に保管する必要があり,しばしば凝縮された画像よりも数百倍大きい.
    • 既存の方法は,画像の多様性と監視の多様性が不十分で,高圧縮速度で性能が低下することを妨げています.

    研究 の 目的:

    • 大規模なデータセットの蒸留における貯蔵と性能の問題に対処するために.
    • 効率的なデータセット圧縮のための新しい方法,ラベル剪定と大規模蒸留のための定量化 (LPQLD) を提案する.

    主な方法:

    • 合成データ生成中のクラス別バッチングとバッチ標準化 (BN) 監督を通じて画像の多様性を高める.
    • ダイナミックな知識の再利用によるレタルの剪定と,校正された生徒と教師の調整によるレタルの定量化による監督の多様性の改善.

    主要な成果:

    • ImageNet-1Kのソフトラベルストレージは78倍,ImageNet-21Kのソフトラベルストレージは500倍減少しました.
    • ImageNet-1Kでは7.2%,ImageNet-21Kでは2.8%の精度向上を達成しました.
    • 様々なネットワークアーキテクチャで優位性を証明し,他の蒸留方法と比較した.

    結論:

    • LPQLDは,データセット蒸留における大規模なソフトラベル保存の限界を効果的に克服します.
    • 提案された方法は,モデルの精度を高めながら,重要な圧縮比を達成します.
    • LPQLDは,効率的な大規模データセットの蒸留のための優れたアプローチを表しています.