南京大学:《高级算法 Advanced Algorithms》课程教学资源(课件讲稿)02 Fingerprinting

Advanced Algorithms Fingerprinting 尹一通Nanjing University,2022Fall
尹⼀通 Nanjing University, 2022 Fall Advanced Algorithms Fingerprinting

Checking Matrix Multiplication three n x n matrices A,B,C: A X B 是 C
• three n × n matrices A, B,C: Checking Matrix Multiplication A × B = C ?

Matrix Multiplication Algorithms n Xn matrix Running time:O(n) 2.9 Year 0 Authors Strassen apovani,Romani,Lotti 1969 2.8074 Strassen 28 1978 2.796 Pan 1979 2.780 Bini,Capovani,Romani 1981 2.522 Schonhage 1981 2.517 Romani 1981 2.496 Coppersmith,Winograd 1986 2.479 Strassen ■g年市n车a年 1990 2.3755 26 Coppersmith,Winograd 2010 2.3737 Stothers Romani smith, 2013 2.3729 Williams Copp ssen 2014 2.3728639 Le Gall 2.5 age 2020 2.3728596 Alman,Williams 2.4 Coppersmith.Winograd 1970 1975 1980 1985 1990 1995 2000 2005 2010 2015 2020 Year
Matrix Multiplication Algorithms matrix Running time: n × n O(nω) Year ω Authors 1969 2.8074 Strassen 1978 2.796 Pan 1979 2.780 Bini, Capovani, Romani 1981 2.522 Schönhage 1981 2.517 Romani 1981 2.496 Coppersmith, Winograd 1986 2.479 Strassen 1990 2.3755 Coppersmith, Winograd 2010 2.3737 Stothers 2013 2.3729 Williams 2014 2.3728639 Le Gall 2020 2.3728596 Alman, Williams

Checking Matrix Multiplication three n xn matrices A,B,C: A X B 名 C Freivald's Algorithm: pick a uniform random r∈{0,l}n; check whether A(Br)=Cr; time:O(n2) if AB C:always correct ifAB≠C:
• three n × n matrices A, B,C: Checking Matrix Multiplication A × B = C ? Freivald’s Algorithm: pick a uniform random ; check whether ; r ∈ {0,1}n A(Br) = Cr time: O(n if AB = C: always correct 2 ) if AB ≠ C:

Freivald's Algorithm: pick a uniform random r∈{0,l}, check whether A(Br)=Cr; fAB≠C: letD=AB-C卡0xn suppose Dii卡0 1 Pr[ABr =Cr]=Pr[Dr=0]< 三 2 (Dr,=∑D4=0 D r k=1 i 之2
Freivald’s Algorithm: pick a uniform random ; check whether ; r ∈ {0,1}n A(Br) = Cr if AB ≠ C: let D = AB − C ≠ 0n×n D r i suppose Dij ≠ 0 Pr[ABr = Cr] = Pr[Dr = 0] ≤ (Dr)i = n ∑ k=1 Dikrk = 0 rj = − 1 Dij ∑ k≠j Dikrk = 1 2 2 n 2n−1

Freivald's Algorithm: pick a uniform random r {0,1)"; check whether A(Br)=Cr; if AB C:always correct Theorem(Feivald 1979). For n X n matrices A,B,C,ifAB≠C,for uniform random r∈{0,l}n, Pr[ABr=Cr]≤ 2 repeat independently for O(log n)times Total running time:O(n2log n) Correct with high probability (w.h.p.)
Freivald’s Algorithm: pick a uniform random ; check whether ; r ∈ {0,1}n A(Br) = Cr Theorem (Feivald 1979). For n × n matrices A, B,C, if AB ≠ C, for uniform random r ∈ {0,1} , n Pr[ABr = Cr] ≤ 1 2 if AB = C: always correct repeat independently for O(log n) times Total running time: Correct with high probability (w.h.p.). O(n2 log n)

Polynomial Identity Testing (PIT) Input:two polynomials fg E Fx]of degree d. Output:f三g? Fx]:polynomial ring in x over field F f∈rL]of degree d:f)=∑a where a,∈F =0 field Input:a polynomial fE Fx]of degree d. Output:f三0? fis given as black-box
Polynomial Identity Testing (PIT) Input: two polynomials of degree . Output: ? f, g ∈ 𝔽[x] d f ≡ g Input: a polynomial of degree . Output: ? f ∈ 𝔽[x] d f ≡ 0 f ∈ 𝔽[x] of degree d: f(x) = where d ∑ i=0 ai xi ai ∈ 𝔽 f is given as black-box field 𝔽[x]: polynomial ring in x over field 𝔽

Input:a polynomial fE Fx]of degree d. Output:f三0? Deterministic algorithm (polynomial interpolation): pick arbitrary distinct., check if f(x)=0 for all0≤i≤d; Fundamental Theorem of Algebra. Any non-zero d-degree polynomial fE Fx]has at most d roots. Randomized algorithm(fingerprinting): pick a uniform random re S; let S Fbe arbitrary check if f(r)=0; (whose size to be fixed later)
Input: a polynomial of degree . Output: ? f ∈ 𝔽[x] d f ≡ 0 • Deterministic algorithm (polynomial interpolation): pick arbitrary distinct ; check if for all ; x0, x1, …, xd ∈ 𝔽 f(xi ) = 0 0 ≤ i ≤ d • Randomized algorithm (fingerprinting): pick a uniform random ; check if ; r f(r) = 0 ∈ S let be arbitrary (whose size to be fixed later) S ⊆ 𝔽 Fundamental Theorem of Algebra. Any non-zero d-degree polynomial f ∈ 𝔽[x] has at most d roots

Input:a polynomial fE Fx]of degree d. Output:f三0? pick a uniform random re S; let S Fbe arbitrary check if f(r)=0; (whose size to-be fixed later) |S|=2d iff≡O:always correct ff丰0: Pr[fr)=O]≤ d 1 ISI 2 Fundamental Theorem of Algebra. Any non-zero d-degree polynomial f Fx]has at most d roots
pick a uniform random ; check if ; r f(r) = 0 ∈ S let be arbitrary (whose size to be fixed later) S ⊆ 𝔽 if f ≡ 0: always correct Input: a polynomial of degree . Output: ? f ∈ 𝔽[x] d f ≡ 0 if f ≢ 0: Pr[f(r) = 0] ≤ |S| Fundamental Theorem of Algebra. Any non-zero d-degree polynomial f ∈ 𝔽[x] has at most d roots. d |S| = 2d = 1 2

Checking Identity 北京 database 1 Are they identical? 南京 database 2
Checking Identity database 1 database 2 Are they identical? 北京 南京
按次数下载不扣除下载券;
注册用户24小时内重复下载只扣除一次;
顺序:VIP每日次数-->可用次数-->下载券;
- 南京大学:《高级算法 Advanced Algorithms》课程教学资源(课件讲稿)01 Introduction - Min-Cut and Max-Cut(尹⼀通).pdf
- 南京大学:《高级算法 Advanced Algorithms》课程教学资源(课件讲稿)03 Balls-into-Bins Model and Chernoff Bounds.pptx
- 《量子计算》课程教学资源(阅读文献)Lecture Notes on Quantum Algorithms(Andrew M. Childs).pdf
- 《量子计算》课程教学资源(阅读文献)Quantum Computation and Quantum Information(10th Anniversary Edition,Michael A. Nielsen & Isaac L. Chuang).pdf
- 《理论计算机科学》课程教学资源(阅读文献)Computational Complexity - A Modern Approach.pdf
- 《理论计算机科学》课程教学资源(阅读文献)Approximation via Correlation Decay when Strong Spatial Mixing Fails(HIS).pdf
- 《理论计算机科学》课程教学资源(阅读文献)Galton–Watson process - Branching.pdf
- 《理论计算机科学》课程教学资源(阅读文献)Analysis Of Boolean Functions(Ryan O’Donnell).pdf
- 南京大学:《概率论与数理统计 Probability and Statistics》课程教学资源(PPT课件讲稿)Lecture 14 假设检验.pptx
- 南京大学:《概率论与数理统计 Probability and Statistics》课程教学资源(PPT课件讲稿)Lecture 13 区间估计(参数估计).pptx
- 南京大学:《概率论与数理统计 Probability and Statistics》课程教学资源(PPT课件讲稿)Lecture 12 点估计(参数估计).pptx
- 南京大学:《概率论与数理统计 Probability and Statistics》课程教学资源(PPT课件讲稿)Lecture 11 统计量与抽样分布.pptx
- 南京大学:《概率论与数理统计 Probability and Statistics》课程教学资源(PPT课件讲稿)Lecture 10 极限理论.pptx
- 南京大学:《概率论与数理统计 Probability and Statistics》课程教学资源(PPT课件讲稿)Lecture 09 典型二维连续型随机变量、相关系数.pptx
- 南京大学:《概率论与数理统计 Probability and Statistics》课程教学资源(PPT课件讲稿)Lecture 08 典型连续型随机变量的分布.pptx
- 南京大学:《概率论与数理统计 Probability and Statistics》课程教学资源(PPT课件讲稿)Lecture 07 连续型随机变量.pptx
- 南京大学:《概率论与数理统计 Probability and Statistics》课程教学资源(PPT课件讲稿)Lecture 06 概率化方法(主讲:唐斌).pptx
- 南京大学:《概率论与数理统计 Probability and Statistics》课程教学资源(PPT课件讲稿)Lecture 05 条件期望、方差.pptx
- 南京大学:《概率论与数理统计 Probability and Statistics》课程教学资源(PPT课件讲稿)Lecture 04 几个典型的离散型随机变量.pptx
- 南京大学:《概率论与数理统计 Probability and Statistics》课程教学资源(PPT课件讲稿)Lecture 03 离散型随机变量.pptx
- 南京大学:《高级算法 Advanced Algorithms》课程教学资源(课件讲稿)03 Balls into Bins.pdf
- 南京大学:《高级算法 Advanced Algorithms》课程教学资源(课件讲稿)04 Hashing and Sketching.pdf
- 南京大学:《高级算法 Advanced Algorithms》课程教学资源(课件讲稿)05 Concentration of measure.pdf
- 南京大学:《高级算法 Advanced Algorithms》课程教学资源(课件讲稿)06 Dimension Reduction.pdf
- 南京大学:《高级算法 Advanced Algorithms》课程教学资源(课件讲稿)07 Lovász Local Lemma.pdf
- 南京大学:《高级算法 Advanced Algorithms》课程教学资源(课件讲稿)08 Greedy and Local Search.pdf
- 南京大学:《高级算法 Advanced Algorithms》课程教学资源(课件讲稿)09 Rounding Dynamic Programs.pdf
- 南京大学:《高级算法 Advanced Algorithms》课程教学资源(课件讲稿)10 Rounding Linear Programs.pdf
- 南京大学:《高级算法 Advanced Algorithms》课程教学资源(课件讲稿)11 The Primal-Dual Schema.pdf
- 南京大学:《高级算法 Advanced Algorithms》课程教学资源(课件讲稿)12 SDP-Based Algorithms.pdf
- 电子科技大学:《图论及其应用 Graph Theory and its Applications》研究生课程教学资源(教学大纲,杨春).pdf
- 电子科技大学:《图论及其应用 Graph Theory and its Applications》研究生课程教学资源(课件讲稿)01 图论简介、图的定义及其相关概念、图的同构.pdf
- 电子科技大学:《图论及其应用 Graph Theory and its Applications》研究生课程教学资源(课件讲稿)02 完全图、偶图与补图、顶点的度与图的度序列.pdf
- 电子科技大学:《图论及其应用 Graph Theory and its Applications》研究生课程教学资源(课件讲稿)03 子图的相关概念、几种典型的图运算、路与连通性.pdf
- 电子科技大学:《图论及其应用 Graph Theory and its Applications》研究生课程教学资源(课件讲稿)04 图的代数表示、最短路算法.pdf
- 电子科技大学:《图论及其应用 Graph Theory and its Applications》研究生课程教学资源(课件讲稿)05 邻接谱、邻接代数与图空间、托兰定理.pdf
- 电子科技大学:《图论及其应用 Graph Theory and its Applications》研究生课程教学资源(课件讲稿)06 树的概念与应用、树的性质、树的中心与形心.pdf
- 电子科技大学:《图论及其应用 Graph Theory and its Applications》研究生课程教学资源(课件讲稿)07 生成树的概念与性质、生成树的计数、回路系统简介.pdf
- 电子科技大学:《图论及其应用 Graph Theory and its Applications》研究生课程教学资源(课件讲稿)08 克鲁斯克尔算法、管梅谷的破圈法、Prim算法、根树简介.pdf
- 电子科技大学:《图论及其应用 Graph Theory and its Applications》研究生课程教学资源(课件讲稿)09 图的连通性(割边、割点和块).pdf