SlideShare a Scribd company logo
1 of 31
Design and Analysis of Algorithms
(CS345/CS345A)

Lecture 6
Augmented BST for
ā€¢ Dynamic sequences
ā€¢ Orthogonal range searching
1
The fundamental question we answered in last
class
Question: What makes BST pervasive in the world of data structures ?
Answer: Augmentation : ā€œstoring extra fields at each nodeā€
: Additional information
DATA STRUCTURES FOR
DYNAMIC SEQUENCES

3
Dynamic Sequence

OR
OR

4
Representing sequence using a BST

: size field
8

3

4

1

2

1
1

1
u

6
T

We need to do the
rebalancing of
height later on.

7
Example 2: sequence of numbers

8
Performing Add(T,i,j,x)

View the entire tree T from
perspective of the paths from i
and j to the root.
How will T look like ?

LCA(i,j)

j
i

T
9
Performing Add(T,i,j,x)

What are the nodes whose values
has to be incremented by x ?

LCA(i,j)

j
i

T
10
Performing Add(T,i,j,x)

What are the nodes whose values
has to be incremented by x ?

LCA(i,j)

j
i

T
11
Performing Add(T,i,j,x)

What are the nodes whose values
has to be incremented by x ?

LCA(i,j)

j
i

T
12
Performing Add(T,i,j,x)

13
Key observations about the data structure

14
Homework

15
Example 2: sequence of bits

16
Example 3: sequence of numbers

17
ORTHOGONAL RANGE SEARCHING

Hopefully you have got a fair amount of understanding of augmenting a
BST by now. Think over this problem for a while before proceeding
further.

18
Orthogonal Range searching

Rectangle

No. of points in
query rectangle

19
Orthogonal Range searching

Rectangle

20
Orthogonal Range searching

21
LCA

T
22
ā€¢ Binary search tree on x-coordinates

LCA

T
23
ā€¢ Binary search tree on x-coordinates

LCA

T
24
ā€¢ Binary search tree on x-coordinates

LCA

T
25
How should we augment each node?
Augment each node v with
a pointer to another BST
storing all points of T(v)
according to y-oordinates.

value
Color-bit
Y-tree

left

right
v

BST storing
T(v)
according to
y-coordinate

26
LCA

T
27
Homework

28
Space of the data structure

1
2
3
4
...
...

T
BST before augmentation

29
Space of the data structure

...

...

T
BST before augmentation

30
Total time to build the data structure

p

31

More Related Content

What's hot

Big o notation
Big o notationBig o notation
Big o notationkeb97
Ā 
Snm Tauctv
Snm TauctvSnm Tauctv
Snm TauctvFNian
Ā 
9 a01701 finite element methods in civil engineering
9 a01701  finite element methods in civil engineering9 a01701  finite element methods in civil engineering
9 a01701 finite element methods in civil engineeringBaduru Muralikrishna
Ā 
Generalized Notions of Data Depth
Generalized Notions of Data DepthGeneralized Notions of Data Depth
Generalized Notions of Data DepthMukund Raj
Ā 
Principal Component Analysis
Principal Component AnalysisPrincipal Component Analysis
Principal Component Analysisamitpraseed
Ā 
2020 1ķ•™źø° ģ •źø°ģŠ¤ķ„°ė”” 1ģ£¼ģ°Ø
2020 1ķ•™źø° ģ •źø°ģŠ¤ķ„°ė”” 1ģ£¼ģ°Ø2020 1ķ•™źø° ģ •źø°ģŠ¤ķ„°ė”” 1ģ£¼ģ°Ø
2020 1ķ•™źø° ģ •źø°ģŠ¤ķ„°ė”” 1ģ£¼ģ°ØMoonki Choi
Ā 
Algorithms 101 for Data Scientists
Algorithms 101 for Data ScientistsAlgorithms 101 for Data Scientists
Algorithms 101 for Data ScientistsChristopher Conlan
Ā 
Lecture 5 Relationship between pixel-2
Lecture 5 Relationship between pixel-2Lecture 5 Relationship between pixel-2
Lecture 5 Relationship between pixel-2VARUN KUMAR
Ā 
R Packages for Time-Varying Networks and Extremal Dependence
R Packages for Time-Varying Networks and Extremal DependenceR Packages for Time-Varying Networks and Extremal Dependence
R Packages for Time-Varying Networks and Extremal DependenceWork-Bench
Ā 
R and Visualization: A match made in Heaven
R and Visualization: A match made in HeavenR and Visualization: A match made in Heaven
R and Visualization: A match made in HeavenEdureka!
Ā 
I Don't Want to Be a Dummy! Encoding Predictors for Trees
I Don't Want to Be a Dummy! Encoding Predictors for TreesI Don't Want to Be a Dummy! Encoding Predictors for Trees
I Don't Want to Be a Dummy! Encoding Predictors for TreesWork-Bench
Ā 
Introduction to R Graphics with ggplot2
Introduction to R Graphics with ggplot2Introduction to R Graphics with ggplot2
Introduction to R Graphics with ggplot2izahn
Ā 
Bringing personalisation to data discovery, Learning to Rank 101 by Pere Urbo...
Bringing personalisation to data discovery, Learning to Rank 101 by Pere Urbo...Bringing personalisation to data discovery, Learning to Rank 101 by Pere Urbo...
Bringing personalisation to data discovery, Learning to Rank 101 by Pere Urbo...Codemotion
Ā 
Lgm saarbrucken
Lgm saarbruckenLgm saarbrucken
Lgm saarbruckenYasuo Tabei
Ā 

What's hot (19)

Big o notation
Big o notationBig o notation
Big o notation
Ā 
Snm Tauctv
Snm TauctvSnm Tauctv
Snm Tauctv
Ā 
Tech appendix
Tech appendixTech appendix
Tech appendix
Ā 
9 a01701 finite element methods in civil engineering
9 a01701  finite element methods in civil engineering9 a01701  finite element methods in civil engineering
9 a01701 finite element methods in civil engineering
Ā 
1
11
1
Ā 
Integration
IntegrationIntegration
Integration
Ā 
Generalized Notions of Data Depth
Generalized Notions of Data DepthGeneralized Notions of Data Depth
Generalized Notions of Data Depth
Ā 
Lent Matlab H Ss
Lent Matlab H SsLent Matlab H Ss
Lent Matlab H Ss
Ā 
Principal Component Analysis
Principal Component AnalysisPrincipal Component Analysis
Principal Component Analysis
Ā 
2020 1ķ•™źø° ģ •źø°ģŠ¤ķ„°ė”” 1ģ£¼ģ°Ø
2020 1ķ•™źø° ģ •źø°ģŠ¤ķ„°ė”” 1ģ£¼ģ°Ø2020 1ķ•™źø° ģ •źø°ģŠ¤ķ„°ė”” 1ģ£¼ģ°Ø
2020 1ķ•™źø° ģ •źø°ģŠ¤ķ„°ė”” 1ģ£¼ģ°Ø
Ā 
Algorithms 101 for Data Scientists
Algorithms 101 for Data ScientistsAlgorithms 101 for Data Scientists
Algorithms 101 for Data Scientists
Ā 
Lecture 5 Relationship between pixel-2
Lecture 5 Relationship between pixel-2Lecture 5 Relationship between pixel-2
Lecture 5 Relationship between pixel-2
Ā 
Tabu search
Tabu searchTabu search
Tabu search
Ā 
R Packages for Time-Varying Networks and Extremal Dependence
R Packages for Time-Varying Networks and Extremal DependenceR Packages for Time-Varying Networks and Extremal Dependence
R Packages for Time-Varying Networks and Extremal Dependence
Ā 
R and Visualization: A match made in Heaven
R and Visualization: A match made in HeavenR and Visualization: A match made in Heaven
R and Visualization: A match made in Heaven
Ā 
I Don't Want to Be a Dummy! Encoding Predictors for Trees
I Don't Want to Be a Dummy! Encoding Predictors for TreesI Don't Want to Be a Dummy! Encoding Predictors for Trees
I Don't Want to Be a Dummy! Encoding Predictors for Trees
Ā 
Introduction to R Graphics with ggplot2
Introduction to R Graphics with ggplot2Introduction to R Graphics with ggplot2
Introduction to R Graphics with ggplot2
Ā 
Bringing personalisation to data discovery, Learning to Rank 101 by Pere Urbo...
Bringing personalisation to data discovery, Learning to Rank 101 by Pere Urbo...Bringing personalisation to data discovery, Learning to Rank 101 by Pere Urbo...
Bringing personalisation to data discovery, Learning to Rank 101 by Pere Urbo...
Ā 
Lgm saarbrucken
Lgm saarbruckenLgm saarbrucken
Lgm saarbrucken
Ā 

Viewers also liked

Lecture 7-cs345-2014
Lecture 7-cs345-2014Lecture 7-cs345-2014
Lecture 7-cs345-2014Rajiv Omar
Ā 
Slide Presentasi Stars United Network 2007
Slide Presentasi Stars United Network 2007Slide Presentasi Stars United Network 2007
Slide Presentasi Stars United Network 2007starsunitednetwork
Ā 
tabel comparativ programatori omfp 835 2015
tabel comparativ programatori omfp 835 2015tabel comparativ programatori omfp 835 2015
tabel comparativ programatori omfp 835 2015Laurentiu Marius
Ā 
Gators group softchalk presentation (1)
Gators group   softchalk presentation (1)Gators group   softchalk presentation (1)
Gators group softchalk presentation (1)hbrown5018
Ā 
Ų„Ų“Ų±Ų§Ł‚Ų§ŲŖ Ų§Ł„Ų„Ų³Ų±Ų§Ų” Ų¬2
Ų„Ų“Ų±Ų§Ł‚Ų§ŲŖ Ų§Ł„Ų„Ų³Ų±Ų§Ų” Ų¬2Ų„Ų“Ų±Ų§Ł‚Ų§ŲŖ Ų§Ł„Ų„Ų³Ų±Ų§Ų” Ų¬2
Ų„Ų“Ų±Ų§Ł‚Ų§ŲŖ Ų§Ł„Ų„Ų³Ų±Ų§Ų” Ų¬2Hassan Elagouz
Ā 
Topelite storm impatica_final_presentation (1)
Topelite storm impatica_final_presentation (1)Topelite storm impatica_final_presentation (1)
Topelite storm impatica_final_presentation (1)hbrown5018
Ā 
ŁƒŁŠŁ ŲŖŁƒŁˆŁ† ŲÆŲ§Ų¹ŁŠŲ§ Ų„Ł„Ł‰ Ų§Ł„Ł„Ł‡ Ų¹Ł„Ł‰ ŲØŲµŁŠŲ±Ų©
ŁƒŁŠŁ ŲŖŁƒŁˆŁ† ŲÆŲ§Ų¹ŁŠŲ§ Ų„Ł„Ł‰ Ų§Ł„Ł„Ł‡ Ų¹Ł„Ł‰ ŲØŲµŁŠŲ±Ų©ŁƒŁŠŁ ŲŖŁƒŁˆŁ† ŲÆŲ§Ų¹ŁŠŲ§ Ų„Ł„Ł‰ Ų§Ł„Ł„Ł‡ Ų¹Ł„Ł‰ ŲØŲµŁŠŲ±Ų©
ŁƒŁŠŁ ŲŖŁƒŁˆŁ† ŲÆŲ§Ų¹ŁŠŲ§ Ų„Ł„Ł‰ Ų§Ł„Ł„Ł‡ Ų¹Ł„Ł‰ ŲØŲµŁŠŲ±Ų©Hassan Elagouz
Ā 
Ų§Ł„Ł…Ų¬Ų§Ł‡ŲÆŲ© Ł„Ł„ŲµŁŲ§Ų” ŁˆŲ§Ł„Ł…Ų“Ų§Ł‡ŲÆŲ©
Ų§Ł„Ł…Ų¬Ų§Ł‡ŲÆŲ© Ł„Ł„ŲµŁŲ§Ų” ŁˆŲ§Ł„Ł…Ų“Ų§Ł‡ŲÆŲ©Ų§Ł„Ł…Ų¬Ų§Ł‡ŲÆŲ© Ł„Ł„ŲµŁŲ§Ų” ŁˆŲ§Ł„Ł…Ų“Ų§Ł‡ŲÆŲ©
Ų§Ł„Ł…Ų¬Ų§Ł‡ŲÆŲ© Ł„Ł„ŲµŁŲ§Ų” ŁˆŲ§Ł„Ł…Ų“Ų§Ł‡ŲÆŲ©Hassan Elagouz
Ā 
Cbse class-12-maths-question-paper-2012
Cbse class-12-maths-question-paper-2012Cbse class-12-maths-question-paper-2012
Cbse class-12-maths-question-paper-2012Abhishek Kumar
Ā 
PhDThesisPDF_MichaelMartin
PhDThesisPDF_MichaelMartinPhDThesisPDF_MichaelMartin
PhDThesisPDF_MichaelMartinMichael Martin
Ā 
Ł…ŁˆŲ§Ų²ŁŠŁ† Ų§Ł„ŲµŲ§ŲÆŁ‚ŁŠŁ† Ł„ŁŲ¶ŁŠŁ„Ų© Ų§Ł„Ų“ŁŠŲ® ŁŁˆŲ²Ł‰ Ł…Ų­Ł…ŲÆ Ų£ŲØŁˆŲ²ŁŠŲÆ
Ł…ŁˆŲ§Ų²ŁŠŁ† Ų§Ł„ŲµŲ§ŲÆŁ‚ŁŠŁ† Ł„ŁŲ¶ŁŠŁ„Ų© Ų§Ł„Ų“ŁŠŲ® ŁŁˆŲ²Ł‰ Ł…Ų­Ł…ŲÆ Ų£ŲØŁˆŲ²ŁŠŲÆŁ…ŁˆŲ§Ų²ŁŠŁ† Ų§Ł„ŲµŲ§ŲÆŁ‚ŁŠŁ† Ł„ŁŲ¶ŁŠŁ„Ų© Ų§Ł„Ų“ŁŠŲ® ŁŁˆŲ²Ł‰ Ł…Ų­Ł…ŲÆ Ų£ŲØŁˆŲ²ŁŠŲÆ
Ł…ŁˆŲ§Ų²ŁŠŁ† Ų§Ł„ŲµŲ§ŲÆŁ‚ŁŠŁ† Ł„ŁŲ¶ŁŠŁ„Ų© Ų§Ł„Ų“ŁŠŲ® ŁŁˆŲ²Ł‰ Ł…Ų­Ł…ŲÆ Ų£ŲØŁˆŲ²ŁŠŲÆHassan Elagouz
Ā 
28 m. ilham_syabani_xrpl1_tutorial_kabel_utp
28 m. ilham_syabani_xrpl1_tutorial_kabel_utp28 m. ilham_syabani_xrpl1_tutorial_kabel_utp
28 m. ilham_syabani_xrpl1_tutorial_kabel_utpMohammad Ilham Sya'bani
Ā 
Personal learning network fatima
Personal learning network fatimaPersonal learning network fatima
Personal learning network fatimaFatima Mejia
Ā 
Ų§Ł„ŁˆŁ„Ų§ŁŠŲ© ŁˆŲ§Ł„Ų£ŁˆŁ„ŁŠŲ§Ų” Ł„ŁŲ¶ŁŠŁ„Ų© Ų§Ł„Ų“ŁŠŲ® ŁŁˆŲ²Ł‰ Ł…Ų­Ł…ŲÆ Ų£ŲØŁˆŲ²ŁŠŲÆ
Ų§Ł„ŁˆŁ„Ų§ŁŠŲ© ŁˆŲ§Ł„Ų£ŁˆŁ„ŁŠŲ§Ų” Ł„ŁŲ¶ŁŠŁ„Ų© Ų§Ł„Ų“ŁŠŲ® ŁŁˆŲ²Ł‰ Ł…Ų­Ł…ŲÆ Ų£ŲØŁˆŲ²ŁŠŲÆ Ų§Ł„ŁˆŁ„Ų§ŁŠŲ© ŁˆŲ§Ł„Ų£ŁˆŁ„ŁŠŲ§Ų” Ł„ŁŲ¶ŁŠŁ„Ų© Ų§Ł„Ų“ŁŠŲ® ŁŁˆŲ²Ł‰ Ł…Ų­Ł…ŲÆ Ų£ŲØŁˆŲ²ŁŠŲÆ
Ų§Ł„ŁˆŁ„Ų§ŁŠŲ© ŁˆŲ§Ł„Ų£ŁˆŁ„ŁŠŲ§Ų” Ł„ŁŲ¶ŁŠŁ„Ų© Ų§Ł„Ų“ŁŠŲ® ŁŁˆŲ²Ł‰ Ł…Ų­Ł…ŲÆ Ų£ŲØŁˆŲ²ŁŠŲÆ Hassan Elagouz
Ā 
Legarabato
LegarabatoLegarabato
LegarabatoGretalucero
Ā 

Viewers also liked (20)

Lecture 7-cs345-2014
Lecture 7-cs345-2014Lecture 7-cs345-2014
Lecture 7-cs345-2014
Ā 
Panic Cord
Panic CordPanic Cord
Panic Cord
Ā 
Slide Presentasi Stars United Network 2007
Slide Presentasi Stars United Network 2007Slide Presentasi Stars United Network 2007
Slide Presentasi Stars United Network 2007
Ā 
tabel comparativ programatori omfp 835 2015
tabel comparativ programatori omfp 835 2015tabel comparativ programatori omfp 835 2015
tabel comparativ programatori omfp 835 2015
Ā 
Oficial
OficialOficial
Oficial
Ā 
Gators group softchalk presentation (1)
Gators group   softchalk presentation (1)Gators group   softchalk presentation (1)
Gators group softchalk presentation (1)
Ā 
Ų„Ų“Ų±Ų§Ł‚Ų§ŲŖ Ų§Ł„Ų„Ų³Ų±Ų§Ų” Ų¬2
Ų„Ų“Ų±Ų§Ł‚Ų§ŲŖ Ų§Ł„Ų„Ų³Ų±Ų§Ų” Ų¬2Ų„Ų“Ų±Ų§Ł‚Ų§ŲŖ Ų§Ł„Ų„Ų³Ų±Ų§Ų” Ų¬2
Ų„Ų“Ų±Ų§Ł‚Ų§ŲŖ Ų§Ł„Ų„Ų³Ų±Ų§Ų” Ų¬2
Ā 
Topelite storm impatica_final_presentation (1)
Topelite storm impatica_final_presentation (1)Topelite storm impatica_final_presentation (1)
Topelite storm impatica_final_presentation (1)
Ā 
ŁƒŁŠŁ ŲŖŁƒŁˆŁ† ŲÆŲ§Ų¹ŁŠŲ§ Ų„Ł„Ł‰ Ų§Ł„Ł„Ł‡ Ų¹Ł„Ł‰ ŲØŲµŁŠŲ±Ų©
ŁƒŁŠŁ ŲŖŁƒŁˆŁ† ŲÆŲ§Ų¹ŁŠŲ§ Ų„Ł„Ł‰ Ų§Ł„Ł„Ł‡ Ų¹Ł„Ł‰ ŲØŲµŁŠŲ±Ų©ŁƒŁŠŁ ŲŖŁƒŁˆŁ† ŲÆŲ§Ų¹ŁŠŲ§ Ų„Ł„Ł‰ Ų§Ł„Ł„Ł‡ Ų¹Ł„Ł‰ ŲØŲµŁŠŲ±Ų©
ŁƒŁŠŁ ŲŖŁƒŁˆŁ† ŲÆŲ§Ų¹ŁŠŲ§ Ų„Ł„Ł‰ Ų§Ł„Ł„Ł‡ Ų¹Ł„Ł‰ ŲØŲµŁŠŲ±Ų©
Ā 
Agile2014 Briefing Deck
Agile2014 Briefing DeckAgile2014 Briefing Deck
Agile2014 Briefing Deck
Ā 
Arbulot guillaume
Arbulot guillaumeArbulot guillaume
Arbulot guillaume
Ā 
Ų§Ł„Ł…Ų¬Ų§Ł‡ŲÆŲ© Ł„Ł„ŲµŁŲ§Ų” ŁˆŲ§Ł„Ł…Ų“Ų§Ł‡ŲÆŲ©
Ų§Ł„Ł…Ų¬Ų§Ł‡ŲÆŲ© Ł„Ł„ŲµŁŲ§Ų” ŁˆŲ§Ł„Ł…Ų“Ų§Ł‡ŲÆŲ©Ų§Ł„Ł…Ų¬Ų§Ł‡ŲÆŲ© Ł„Ł„ŲµŁŲ§Ų” ŁˆŲ§Ł„Ł…Ų“Ų§Ł‡ŲÆŲ©
Ų§Ł„Ł…Ų¬Ų§Ł‡ŲÆŲ© Ł„Ł„ŲµŁŲ§Ų” ŁˆŲ§Ł„Ł…Ų“Ų§Ł‡ŲÆŲ©
Ā 
Navigating The Digital Space
Navigating The Digital SpaceNavigating The Digital Space
Navigating The Digital Space
Ā 
Cbse class-12-maths-question-paper-2012
Cbse class-12-maths-question-paper-2012Cbse class-12-maths-question-paper-2012
Cbse class-12-maths-question-paper-2012
Ā 
PhDThesisPDF_MichaelMartin
PhDThesisPDF_MichaelMartinPhDThesisPDF_MichaelMartin
PhDThesisPDF_MichaelMartin
Ā 
Ł…ŁˆŲ§Ų²ŁŠŁ† Ų§Ł„ŲµŲ§ŲÆŁ‚ŁŠŁ† Ł„ŁŲ¶ŁŠŁ„Ų© Ų§Ł„Ų“ŁŠŲ® ŁŁˆŲ²Ł‰ Ł…Ų­Ł…ŲÆ Ų£ŲØŁˆŲ²ŁŠŲÆ
Ł…ŁˆŲ§Ų²ŁŠŁ† Ų§Ł„ŲµŲ§ŲÆŁ‚ŁŠŁ† Ł„ŁŲ¶ŁŠŁ„Ų© Ų§Ł„Ų“ŁŠŲ® ŁŁˆŲ²Ł‰ Ł…Ų­Ł…ŲÆ Ų£ŲØŁˆŲ²ŁŠŲÆŁ…ŁˆŲ§Ų²ŁŠŁ† Ų§Ł„ŲµŲ§ŲÆŁ‚ŁŠŁ† Ł„ŁŲ¶ŁŠŁ„Ų© Ų§Ł„Ų“ŁŠŲ® ŁŁˆŲ²Ł‰ Ł…Ų­Ł…ŲÆ Ų£ŲØŁˆŲ²ŁŠŲÆ
Ł…ŁˆŲ§Ų²ŁŠŁ† Ų§Ł„ŲµŲ§ŲÆŁ‚ŁŠŁ† Ł„ŁŲ¶ŁŠŁ„Ų© Ų§Ł„Ų“ŁŠŲ® ŁŁˆŲ²Ł‰ Ł…Ų­Ł…ŲÆ Ų£ŲØŁˆŲ²ŁŠŲÆ
Ā 
28 m. ilham_syabani_xrpl1_tutorial_kabel_utp
28 m. ilham_syabani_xrpl1_tutorial_kabel_utp28 m. ilham_syabani_xrpl1_tutorial_kabel_utp
28 m. ilham_syabani_xrpl1_tutorial_kabel_utp
Ā 
Personal learning network fatima
Personal learning network fatimaPersonal learning network fatima
Personal learning network fatima
Ā 
Ų§Ł„ŁˆŁ„Ų§ŁŠŲ© ŁˆŲ§Ł„Ų£ŁˆŁ„ŁŠŲ§Ų” Ł„ŁŲ¶ŁŠŁ„Ų© Ų§Ł„Ų“ŁŠŲ® ŁŁˆŲ²Ł‰ Ł…Ų­Ł…ŲÆ Ų£ŲØŁˆŲ²ŁŠŲÆ
Ų§Ł„ŁˆŁ„Ų§ŁŠŲ© ŁˆŲ§Ł„Ų£ŁˆŁ„ŁŠŲ§Ų” Ł„ŁŲ¶ŁŠŁ„Ų© Ų§Ł„Ų“ŁŠŲ® ŁŁˆŲ²Ł‰ Ł…Ų­Ł…ŲÆ Ų£ŲØŁˆŲ²ŁŠŲÆ Ų§Ł„ŁˆŁ„Ų§ŁŠŲ© ŁˆŲ§Ł„Ų£ŁˆŁ„ŁŠŲ§Ų” Ł„ŁŲ¶ŁŠŁ„Ų© Ų§Ł„Ų“ŁŠŲ® ŁŁˆŲ²Ł‰ Ł…Ų­Ł…ŲÆ Ų£ŲØŁˆŲ²ŁŠŲÆ
Ų§Ł„ŁˆŁ„Ų§ŁŠŲ© ŁˆŲ§Ł„Ų£ŁˆŁ„ŁŠŲ§Ų” Ł„ŁŲ¶ŁŠŁ„Ų© Ų§Ł„Ų“ŁŠŲ® ŁŁˆŲ²Ł‰ Ł…Ų­Ł…ŲÆ Ų£ŲØŁˆŲ²ŁŠŲÆ
Ā 
Legarabato
LegarabatoLegarabato
Legarabato
Ā 

Similar to Lecture 6-cs345-2014

Data structure-question-bank
Data structure-question-bankData structure-question-bank
Data structure-question-bankJagan Mohan Bishoyi
Ā 
Week2-stacks-queues.pptx
Week2-stacks-queues.pptxWeek2-stacks-queues.pptx
Week2-stacks-queues.pptxVandanaBharti21
Ā 
EC202 SIGNALS & SYSTEMS PREVIOUS QUESTION PAPER
EC202 SIGNALS & SYSTEMS PREVIOUS QUESTION PAPEREC202 SIGNALS & SYSTEMS PREVIOUS QUESTION PAPER
EC202 SIGNALS & SYSTEMS PREVIOUS QUESTION PAPERVISHNUPRABHANKAIMAL
Ā 
WeightWatcher LLM Update
WeightWatcher LLM UpdateWeightWatcher LLM Update
WeightWatcher LLM UpdateCharles Martin
Ā 
theory of computation lecture 01
theory of computation lecture 01theory of computation lecture 01
theory of computation lecture 018threspecter
Ā 
Introduction to Machine Learning
Introduction to Machine LearningIntroduction to Machine Learning
Introduction to Machine LearningBig_Data_Ukraine
Ā 
Data Structures and Algorithm - Week 8 - Minimum Spanning Trees
Data Structures and Algorithm - Week 8 - Minimum Spanning TreesData Structures and Algorithm - Week 8 - Minimum Spanning Trees
Data Structures and Algorithm - Week 8 - Minimum Spanning TreesFerdin Joe John Joseph PhD
Ā 
A common fixed point theorem for two random operators using random mann itera...
A common fixed point theorem for two random operators using random mann itera...A common fixed point theorem for two random operators using random mann itera...
A common fixed point theorem for two random operators using random mann itera...Alexander Decker
Ā 
SMU BSC IT FALL / SUMMER 2013 SOLVED ASSIGNMENTS
SMU BSC IT FALL / SUMMER 2013 SOLVED ASSIGNMENTSSMU BSC IT FALL / SUMMER 2013 SOLVED ASSIGNMENTS
SMU BSC IT FALL / SUMMER 2013 SOLVED ASSIGNMENTSsmumbahelp
Ā 
lecture 12
lecture 12lecture 12
lecture 12sajinsc
Ā 
Smu bsc it Spring 2014 solved assignments
Smu bsc it Spring 2014  solved assignmentsSmu bsc it Spring 2014  solved assignments
Smu bsc it Spring 2014 solved assignmentssmumbahelp
Ā 
GNU octave
GNU octaveGNU octave
GNU octavegauravmalav
Ā 
IR-ranking
IR-rankingIR-ranking
IR-rankingFELIX75
Ā 
19. Java data structures algorithms and complexity
19. Java data structures algorithms and complexity19. Java data structures algorithms and complexity
19. Java data structures algorithms and complexityIntro C# Book
Ā 
Sample Questions.docx
Sample Questions.docxSample Questions.docx
Sample Questions.docxAndrewsJose
Ā 
Joint optimization framework for learning with noisy labels
Joint optimization framework for learning with noisy labelsJoint optimization framework for learning with noisy labels
Joint optimization framework for learning with noisy labelsCheng-You Lu
Ā 

Similar to Lecture 6-cs345-2014 (20)

Data structure-question-bank
Data structure-question-bankData structure-question-bank
Data structure-question-bank
Ā 
Week2-stacks-queues.pptx
Week2-stacks-queues.pptxWeek2-stacks-queues.pptx
Week2-stacks-queues.pptx
Ā 
EC202 SIGNALS & SYSTEMS PREVIOUS QUESTION PAPER
EC202 SIGNALS & SYSTEMS PREVIOUS QUESTION PAPEREC202 SIGNALS & SYSTEMS PREVIOUS QUESTION PAPER
EC202 SIGNALS & SYSTEMS PREVIOUS QUESTION PAPER
Ā 
WeightWatcher LLM Update
WeightWatcher LLM UpdateWeightWatcher LLM Update
WeightWatcher LLM Update
Ā 
theory of computation lecture 01
theory of computation lecture 01theory of computation lecture 01
theory of computation lecture 01
Ā 
Introduction to Machine Learning
Introduction to Machine LearningIntroduction to Machine Learning
Introduction to Machine Learning
Ā 
Data Structures and Algorithm - Week 8 - Minimum Spanning Trees
Data Structures and Algorithm - Week 8 - Minimum Spanning TreesData Structures and Algorithm - Week 8 - Minimum Spanning Trees
Data Structures and Algorithm - Week 8 - Minimum Spanning Trees
Ā 
A common fixed point theorem for two random operators using random mann itera...
A common fixed point theorem for two random operators using random mann itera...A common fixed point theorem for two random operators using random mann itera...
A common fixed point theorem for two random operators using random mann itera...
Ā 
SMU BSC IT FALL / SUMMER 2013 SOLVED ASSIGNMENTS
SMU BSC IT FALL / SUMMER 2013 SOLVED ASSIGNMENTSSMU BSC IT FALL / SUMMER 2013 SOLVED ASSIGNMENTS
SMU BSC IT FALL / SUMMER 2013 SOLVED ASSIGNMENTS
Ā 
lecture 12
lecture 12lecture 12
lecture 12
Ā 
Smu bsc it Spring 2014 solved assignments
Smu bsc it Spring 2014  solved assignmentsSmu bsc it Spring 2014  solved assignments
Smu bsc it Spring 2014 solved assignments
Ā 
GNU octave
GNU octaveGNU octave
GNU octave
Ā 
1st and 2nd Semester M Tech: Computer Science and Engineering (Dec-2015; Jan-...
1st and 2nd Semester M Tech: Computer Science and Engineering (Dec-2015; Jan-...1st and 2nd Semester M Tech: Computer Science and Engineering (Dec-2015; Jan-...
1st and 2nd Semester M Tech: Computer Science and Engineering (Dec-2015; Jan-...
Ā 
ictir2016
ictir2016ictir2016
ictir2016
Ā 
IR-ranking
IR-rankingIR-ranking
IR-ranking
Ā 
Midterm sols
Midterm solsMidterm sols
Midterm sols
Ā 
19. Java data structures algorithms and complexity
19. Java data structures algorithms and complexity19. Java data structures algorithms and complexity
19. Java data structures algorithms and complexity
Ā 
Sample Questions.docx
Sample Questions.docxSample Questions.docx
Sample Questions.docx
Ā 
Joint optimization framework for learning with noisy labels
Joint optimization framework for learning with noisy labelsJoint optimization framework for learning with noisy labels
Joint optimization framework for learning with noisy labels
Ā 
Q
QQ
Q
Ā 

More from Rajiv Omar

Lecture 14-2013
Lecture 14-2013Lecture 14-2013
Lecture 14-2013Rajiv Omar
Ā 
Lecture 2-cs648
Lecture 2-cs648Lecture 2-cs648
Lecture 2-cs648Rajiv Omar
Ā 
Lecture 15
Lecture 15Lecture 15
Lecture 15Rajiv Omar
Ā 
Lecture 16
Lecture 16Lecture 16
Lecture 16Rajiv Omar
Ā 
Lecture 13-cs648
Lecture 13-cs648Lecture 13-cs648
Lecture 13-cs648Rajiv Omar
Ā 
Lecture 14-cs648-2013
Lecture 14-cs648-2013Lecture 14-cs648-2013
Lecture 14-cs648-2013Rajiv Omar
Ā 
Lecture 17-cs648
Lecture 17-cs648Lecture 17-cs648
Lecture 17-cs648Rajiv Omar
Ā 
Lecture 18-cs648
Lecture 18-cs648Lecture 18-cs648
Lecture 18-cs648Rajiv Omar
Ā 
Lecture 19-cs648
Lecture 19-cs648Lecture 19-cs648
Lecture 19-cs648Rajiv Omar
Ā 
Lecture 20-cs648
Lecture 20-cs648Lecture 20-cs648
Lecture 20-cs648Rajiv Omar
Ā 
Lecture 22-cs648
Lecture 22-cs648Lecture 22-cs648
Lecture 22-cs648Rajiv Omar
Ā 
Lecture 3-cs648
Lecture 3-cs648Lecture 3-cs648
Lecture 3-cs648Rajiv Omar
Ā 
Lecture 4-cs648
Lecture 4-cs648Lecture 4-cs648
Lecture 4-cs648Rajiv Omar
Ā 
Lecture 5-cs648
Lecture 5-cs648Lecture 5-cs648
Lecture 5-cs648Rajiv Omar
Ā 
Lecture 6-cs648
Lecture 6-cs648Lecture 6-cs648
Lecture 6-cs648Rajiv Omar
Ā 
Lecture 7-cs648
Lecture 7-cs648Lecture 7-cs648
Lecture 7-cs648Rajiv Omar
Ā 
Lecture 8-cs648-2013
Lecture 8-cs648-2013Lecture 8-cs648-2013
Lecture 8-cs648-2013Rajiv Omar
Ā 
Lecture 9-cs648-2013
Lecture 9-cs648-2013Lecture 9-cs648-2013
Lecture 9-cs648-2013Rajiv Omar
Ā 
Lecture 1-cs648
Lecture 1-cs648Lecture 1-cs648
Lecture 1-cs648Rajiv Omar
Ā 
Lecture 10-cs648=2013
Lecture 10-cs648=2013Lecture 10-cs648=2013
Lecture 10-cs648=2013Rajiv Omar
Ā 

More from Rajiv Omar (20)

Lecture 14-2013
Lecture 14-2013Lecture 14-2013
Lecture 14-2013
Ā 
Lecture 2-cs648
Lecture 2-cs648Lecture 2-cs648
Lecture 2-cs648
Ā 
Lecture 15
Lecture 15Lecture 15
Lecture 15
Ā 
Lecture 16
Lecture 16Lecture 16
Lecture 16
Ā 
Lecture 13-cs648
Lecture 13-cs648Lecture 13-cs648
Lecture 13-cs648
Ā 
Lecture 14-cs648-2013
Lecture 14-cs648-2013Lecture 14-cs648-2013
Lecture 14-cs648-2013
Ā 
Lecture 17-cs648
Lecture 17-cs648Lecture 17-cs648
Lecture 17-cs648
Ā 
Lecture 18-cs648
Lecture 18-cs648Lecture 18-cs648
Lecture 18-cs648
Ā 
Lecture 19-cs648
Lecture 19-cs648Lecture 19-cs648
Lecture 19-cs648
Ā 
Lecture 20-cs648
Lecture 20-cs648Lecture 20-cs648
Lecture 20-cs648
Ā 
Lecture 22-cs648
Lecture 22-cs648Lecture 22-cs648
Lecture 22-cs648
Ā 
Lecture 3-cs648
Lecture 3-cs648Lecture 3-cs648
Lecture 3-cs648
Ā 
Lecture 4-cs648
Lecture 4-cs648Lecture 4-cs648
Lecture 4-cs648
Ā 
Lecture 5-cs648
Lecture 5-cs648Lecture 5-cs648
Lecture 5-cs648
Ā 
Lecture 6-cs648
Lecture 6-cs648Lecture 6-cs648
Lecture 6-cs648
Ā 
Lecture 7-cs648
Lecture 7-cs648Lecture 7-cs648
Lecture 7-cs648
Ā 
Lecture 8-cs648-2013
Lecture 8-cs648-2013Lecture 8-cs648-2013
Lecture 8-cs648-2013
Ā 
Lecture 9-cs648-2013
Lecture 9-cs648-2013Lecture 9-cs648-2013
Lecture 9-cs648-2013
Ā 
Lecture 1-cs648
Lecture 1-cs648Lecture 1-cs648
Lecture 1-cs648
Ā 
Lecture 10-cs648=2013
Lecture 10-cs648=2013Lecture 10-cs648=2013
Lecture 10-cs648=2013
Ā 

Recently uploaded

How to Troubleshoot Apps for the Modern Connected Worker
How to Troubleshoot Apps for the Modern Connected WorkerHow to Troubleshoot Apps for the Modern Connected Worker
How to Troubleshoot Apps for the Modern Connected WorkerThousandEyes
Ā 
Boost PC performance: How more available memory can improve productivity
Boost PC performance: How more available memory can improve productivityBoost PC performance: How more available memory can improve productivity
Boost PC performance: How more available memory can improve productivityPrincipled Technologies
Ā 
Apidays New York 2024 - The Good, the Bad and the Governed by David O'Neill, ...
Apidays New York 2024 - The Good, the Bad and the Governed by David O'Neill, ...Apidays New York 2024 - The Good, the Bad and the Governed by David O'Neill, ...
Apidays New York 2024 - The Good, the Bad and the Governed by David O'Neill, ...apidays
Ā 
A Year of the Servo Reboot: Where Are We Now?
A Year of the Servo Reboot: Where Are We Now?A Year of the Servo Reboot: Where Are We Now?
A Year of the Servo Reboot: Where Are We Now?Igalia
Ā 
TrustArc Webinar - Unlock the Power of AI-Driven Data Discovery
TrustArc Webinar - Unlock the Power of AI-Driven Data DiscoveryTrustArc Webinar - Unlock the Power of AI-Driven Data Discovery
TrustArc Webinar - Unlock the Power of AI-Driven Data DiscoveryTrustArc
Ā 
presentation ICT roal in 21st century education
presentation ICT roal in 21st century educationpresentation ICT roal in 21st century education
presentation ICT roal in 21st century educationjfdjdjcjdnsjd
Ā 
Mastering MySQL Database Architecture: Deep Dive into MySQL Shell and MySQL R...
Mastering MySQL Database Architecture: Deep Dive into MySQL Shell and MySQL R...Mastering MySQL Database Architecture: Deep Dive into MySQL Shell and MySQL R...
Mastering MySQL Database Architecture: Deep Dive into MySQL Shell and MySQL R...Miguel AraĆŗjo
Ā 
Apidays New York 2024 - The value of a flexible API Management solution for O...
Apidays New York 2024 - The value of a flexible API Management solution for O...Apidays New York 2024 - The value of a flexible API Management solution for O...
Apidays New York 2024 - The value of a flexible API Management solution for O...apidays
Ā 
Partners Life - Insurer Innovation Award 2024
Partners Life - Insurer Innovation Award 2024Partners Life - Insurer Innovation Award 2024
Partners Life - Insurer Innovation Award 2024The Digital Insurer
Ā 
MINDCTI Revenue Release Quarter One 2024
MINDCTI Revenue Release Quarter One 2024MINDCTI Revenue Release Quarter One 2024
MINDCTI Revenue Release Quarter One 2024MIND CTI
Ā 
ProductAnonymous-April2024-WinProductDiscovery-MelissaKlemke
ProductAnonymous-April2024-WinProductDiscovery-MelissaKlemkeProductAnonymous-April2024-WinProductDiscovery-MelissaKlemke
ProductAnonymous-April2024-WinProductDiscovery-MelissaKlemkeProduct Anonymous
Ā 
Bajaj Allianz Life Insurance Company - Insurer Innovation Award 2024
Bajaj Allianz Life Insurance Company - Insurer Innovation Award 2024Bajaj Allianz Life Insurance Company - Insurer Innovation Award 2024
Bajaj Allianz Life Insurance Company - Insurer Innovation Award 2024The Digital Insurer
Ā 
Boost Fertility New Invention Ups Success Rates.pdf
Boost Fertility New Invention Ups Success Rates.pdfBoost Fertility New Invention Ups Success Rates.pdf
Boost Fertility New Invention Ups Success Rates.pdfsudhanshuwaghmare1
Ā 
The 7 Things I Know About Cyber Security After 25 Years | April 2024
The 7 Things I Know About Cyber Security After 25 Years | April 2024The 7 Things I Know About Cyber Security After 25 Years | April 2024
The 7 Things I Know About Cyber Security After 25 Years | April 2024Rafal Los
Ā 
šŸ¬ The future of MySQL is Postgres šŸ˜
šŸ¬  The future of MySQL is Postgres   šŸ˜šŸ¬  The future of MySQL is Postgres   šŸ˜
šŸ¬ The future of MySQL is Postgres šŸ˜RTylerCroy
Ā 
Strategies for Unlocking Knowledge Management in Microsoft 365 in the Copilot...
Strategies for Unlocking Knowledge Management in Microsoft 365 in the Copilot...Strategies for Unlocking Knowledge Management in Microsoft 365 in the Copilot...
Strategies for Unlocking Knowledge Management in Microsoft 365 in the Copilot...Drew Madelung
Ā 
Exploring the Future Potential of AI-Enabled Smartphone Processors
Exploring the Future Potential of AI-Enabled Smartphone ProcessorsExploring the Future Potential of AI-Enabled Smartphone Processors
Exploring the Future Potential of AI-Enabled Smartphone Processorsdebabhi2
Ā 
Artificial Intelligence Chap.5 : Uncertainty
Artificial Intelligence Chap.5 : UncertaintyArtificial Intelligence Chap.5 : Uncertainty
Artificial Intelligence Chap.5 : UncertaintyKhushali Kathiriya
Ā 
GenAI Risks & Security Meetup 01052024.pdf
GenAI Risks & Security Meetup 01052024.pdfGenAI Risks & Security Meetup 01052024.pdf
GenAI Risks & Security Meetup 01052024.pdflior mazor
Ā 

Recently uploaded (20)

How to Troubleshoot Apps for the Modern Connected Worker
How to Troubleshoot Apps for the Modern Connected WorkerHow to Troubleshoot Apps for the Modern Connected Worker
How to Troubleshoot Apps for the Modern Connected Worker
Ā 
Boost PC performance: How more available memory can improve productivity
Boost PC performance: How more available memory can improve productivityBoost PC performance: How more available memory can improve productivity
Boost PC performance: How more available memory can improve productivity
Ā 
+971581248768>> SAFE AND ORIGINAL ABORTION PILLS FOR SALE IN DUBAI AND ABUDHA...
+971581248768>> SAFE AND ORIGINAL ABORTION PILLS FOR SALE IN DUBAI AND ABUDHA...+971581248768>> SAFE AND ORIGINAL ABORTION PILLS FOR SALE IN DUBAI AND ABUDHA...
+971581248768>> SAFE AND ORIGINAL ABORTION PILLS FOR SALE IN DUBAI AND ABUDHA...
Ā 
Apidays New York 2024 - The Good, the Bad and the Governed by David O'Neill, ...
Apidays New York 2024 - The Good, the Bad and the Governed by David O'Neill, ...Apidays New York 2024 - The Good, the Bad and the Governed by David O'Neill, ...
Apidays New York 2024 - The Good, the Bad and the Governed by David O'Neill, ...
Ā 
A Year of the Servo Reboot: Where Are We Now?
A Year of the Servo Reboot: Where Are We Now?A Year of the Servo Reboot: Where Are We Now?
A Year of the Servo Reboot: Where Are We Now?
Ā 
TrustArc Webinar - Unlock the Power of AI-Driven Data Discovery
TrustArc Webinar - Unlock the Power of AI-Driven Data DiscoveryTrustArc Webinar - Unlock the Power of AI-Driven Data Discovery
TrustArc Webinar - Unlock the Power of AI-Driven Data Discovery
Ā 
presentation ICT roal in 21st century education
presentation ICT roal in 21st century educationpresentation ICT roal in 21st century education
presentation ICT roal in 21st century education
Ā 
Mastering MySQL Database Architecture: Deep Dive into MySQL Shell and MySQL R...
Mastering MySQL Database Architecture: Deep Dive into MySQL Shell and MySQL R...Mastering MySQL Database Architecture: Deep Dive into MySQL Shell and MySQL R...
Mastering MySQL Database Architecture: Deep Dive into MySQL Shell and MySQL R...
Ā 
Apidays New York 2024 - The value of a flexible API Management solution for O...
Apidays New York 2024 - The value of a flexible API Management solution for O...Apidays New York 2024 - The value of a flexible API Management solution for O...
Apidays New York 2024 - The value of a flexible API Management solution for O...
Ā 
Partners Life - Insurer Innovation Award 2024
Partners Life - Insurer Innovation Award 2024Partners Life - Insurer Innovation Award 2024
Partners Life - Insurer Innovation Award 2024
Ā 
MINDCTI Revenue Release Quarter One 2024
MINDCTI Revenue Release Quarter One 2024MINDCTI Revenue Release Quarter One 2024
MINDCTI Revenue Release Quarter One 2024
Ā 
ProductAnonymous-April2024-WinProductDiscovery-MelissaKlemke
ProductAnonymous-April2024-WinProductDiscovery-MelissaKlemkeProductAnonymous-April2024-WinProductDiscovery-MelissaKlemke
ProductAnonymous-April2024-WinProductDiscovery-MelissaKlemke
Ā 
Bajaj Allianz Life Insurance Company - Insurer Innovation Award 2024
Bajaj Allianz Life Insurance Company - Insurer Innovation Award 2024Bajaj Allianz Life Insurance Company - Insurer Innovation Award 2024
Bajaj Allianz Life Insurance Company - Insurer Innovation Award 2024
Ā 
Boost Fertility New Invention Ups Success Rates.pdf
Boost Fertility New Invention Ups Success Rates.pdfBoost Fertility New Invention Ups Success Rates.pdf
Boost Fertility New Invention Ups Success Rates.pdf
Ā 
The 7 Things I Know About Cyber Security After 25 Years | April 2024
The 7 Things I Know About Cyber Security After 25 Years | April 2024The 7 Things I Know About Cyber Security After 25 Years | April 2024
The 7 Things I Know About Cyber Security After 25 Years | April 2024
Ā 
šŸ¬ The future of MySQL is Postgres šŸ˜
šŸ¬  The future of MySQL is Postgres   šŸ˜šŸ¬  The future of MySQL is Postgres   šŸ˜
šŸ¬ The future of MySQL is Postgres šŸ˜
Ā 
Strategies for Unlocking Knowledge Management in Microsoft 365 in the Copilot...
Strategies for Unlocking Knowledge Management in Microsoft 365 in the Copilot...Strategies for Unlocking Knowledge Management in Microsoft 365 in the Copilot...
Strategies for Unlocking Knowledge Management in Microsoft 365 in the Copilot...
Ā 
Exploring the Future Potential of AI-Enabled Smartphone Processors
Exploring the Future Potential of AI-Enabled Smartphone ProcessorsExploring the Future Potential of AI-Enabled Smartphone Processors
Exploring the Future Potential of AI-Enabled Smartphone Processors
Ā 
Artificial Intelligence Chap.5 : Uncertainty
Artificial Intelligence Chap.5 : UncertaintyArtificial Intelligence Chap.5 : Uncertainty
Artificial Intelligence Chap.5 : Uncertainty
Ā 
GenAI Risks & Security Meetup 01052024.pdf
GenAI Risks & Security Meetup 01052024.pdfGenAI Risks & Security Meetup 01052024.pdf
GenAI Risks & Security Meetup 01052024.pdf
Ā 

Lecture 6-cs345-2014