Johnson–Lindenstrauss lemma
노트
위키데이터
- ID : Q6268577
말뭉치
- The Johnson-Lindenstrauss Lemma (JL lemma) tells us that we need dimension , and that the mapping is a (random) linear mapping.[1]
- A variant of the Johnson–Lindenstrauss lemma for circulant matrices.[2]
- A simple short proof of the Johnson-Lindenstrauss lemma (concerning nearly isometric embeddings of finite point sets in lower-dimensional spaces) is given.[3]
- Earlier versions of the Johnson-Lindenstrauss lemma used a slightly different function .[4]
- It turns out that the Johnson-Lindenstrauss lemma is almost optimal.[4]
- Then, if we map the ‘s to points in while preserving distances up to a factor , then the dimension must be at least , which is nearly what the Johnson-Lindenstrauss lemma would give.[4]
- The Johnson-Lindenstrauss lemma very strongly depends on properties of the Euclidean norm.[4]
소스
메타데이터
위키데이터
- ID : Q6268577