Bounds for exponential sums
WebSums of sub-exponential random variables Let Xi be independent(⌧ 2 i,bi)-sub-exponential random variables. Then Pn i=1 Xi is (Pn i=1 ⌧ 2 i,b⇤)-sub-exponential, where b⇤ = maxi bi Corollary: If Xi satisfy above, then P 1 n Xn i=1 Xi E[Xi] t! 2exp min (nt2 2 1 n Pn i=1 ⌧ 2 i, nt 2b⇤)!. Prof. John Duchi WebDec 1, 2024 · Here we provide some new bounds on quadrinomial exponential sums using the techniques in [13]. We thus define (1.1) Ψ ( X) = a X k + b X ℓ + c X m + d X n. …
Bounds for exponential sums
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WebMar 25, 2003 · Estimates are given for the exponential sum $\sum_ {x=1}^p \exp (2\pi i f (x)/p)$, $p$ a prime and $f$ a nonzero integer polynomial, of interest in cases where the … WebJul 3, 2024 · We also obtain explicit bounds for quadrilinear exponential sums. Download to read the full article text References E. Aksoy Yazici, B. Murphy, M. Rudnev and I. D. …
WebApr 20, 2024 · Consider the following norm of exponenetial sum: I ( N, p, k) = ∫ 0 1 ∫ 0 1 ∑ n = 0 N e 2 π i ( n x + n k y) p d x d y. Bourgain mentioned on Page 118 of. … WebAbstract. We prove, for a sufficiently small subset A of a prime residue field, an estimate on the number of solutions to the equation ( a 1 − a 2) ( a 3 − a 4) = ( a 5 − a 6) ( a 7 − a 8) …
WebDec 1, 2024 · Bounds on multilinear exponential sums We recall the following classical bound of bilinear sums, see, for example, [2, Equation (1.4)] or [10, Lemma 4.1]. Lemma 2.5 For any sets X, Y ⊆ F p and any α = ( α x) x ∈ X, β = ( β y) y ∈ Y, with ∑ x ∈ X α x 2 = A and ∑ y ∈ Y β y 2 = B, we have ∑ x ∈ X ∑ y ∈ Y α x β y e p ( x y) ⩽ p A B. WebThe boundary of K − 1 ( A) is ∂ K − 1 ( A) = ⋃ m = 1 N − 1 [ K − 1 ( A) ∩ ( { 0 R m } × R N − m)] ⏟ B m. Using the method of Lagrange multipliers, we show that E has a maximum on …
WebWe have been looking at deviation inequalities, i.e., bounds on tail probabilities like P(Xn ≥ t)for some statistic Xn. 1. Using moment generating function bounds, for sums of independent r.v.s: Chernoff; Hoeffding; sub-Gaussian, sub-exponential random variables; Bernstein. Today: Johnson-Lindenstrauss. 2. Martingale methods:
WebSub-exponential time Sum-of-Squares lower bounds for Principal Components Analysis. Part of Advances in Neural Information Processing Systems 35 (NeurIPS ... In this work, we study the limits of the powerful Sum of Squares (SoS) family of algorithms for Sparse PCA. SoS algorithms have recently revolutionized robust statistics, leading to ... how far is marco island florida from miamiWebMar 20, 2015 · 1. Let τ ( n) be the divisor function. Let a be either a constant, or a function of X that is slowly varying with X, say X / log ( X) < a ( X) < X log ( X), for example. I want to lower bound sums of the following form. ∑ 1 ≤ n ≤ X a 1 − τ ( n) D, ( 1) and. ∑ 1 ≤ n ≤ X: n ∈ I a 1 − τ ( n) D, ( 2) where I is an index set of ... highbix.comWebFeb 1, 2024 · Here we propose a new approach to bounding such sums. The bound we obtain is always weaker than (1.2) however it applies to more general sums, essentially … how far is marcy ny from meWebNov 1, 2014 · In the paper we obtain some new upper bounds for exponential sums over multiplicative subgroups @C@?F"p^@? having sizes in the range [p^c^"^1,p^c^"^2], where c"1, c"2 are some absolute constants cl... On exponential sums over multiplicative subgroups of medium size Finite Fields and Their Applications Advanced Search … how far is mareeba from port douglasWebMar 19, 2015 · 1. Let τ ( n) be the divisor function. Let a be either a constant, or a function of X that is slowly varying with X, say X / log ( X) < a ( X) < X log ( X), for example. I want to … highbix bellsWebJul 11, 2024 · This answer will requires that: ∫ c r x d x = E i ( r x ln ( c)) ln ( 1 / r) + C. and the bounds: 1 2 exp ( − x) ln ( 1 + ( 2 / x)) ≤ E 1 ( x) ≤ exp ( − x) ln ( 1 + ( 1 / x)) for x ≥ 0, where: E 1 ( x) = − E i ( − x) Since i ↦ c r i is increasing, we have that: ∑ i = 1 n c r i ≤ ∫ i = 1 n + 1 c r x d x = E i ( r n + 1 ln ... highbit technologiesWebPossible applications include (but are not limited to) complexity theory, random number generation, cryptography, and coding theory. The main method discussed is based on bounds of exponential sums. Accordingly, the book contains many estimates of such sums, including new estimates of classical Gaussian sums. high bit systems inc