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4
votes
2answers
203 views

Intuitively, why is the complementary slackness condition true?

What's an intuitive proof that shows that the conditions of complementary slackness are indeed true: If $x^*_j > 0$ then the $j$-th constraint in the dual is binding. If the $j$-th constraint in ...
6
votes
1answer
187 views

Why is complementary slackness important?

Complementary slackness (CS) is commonly taught when talking about duality. It establishes a nice relation between the primal and the dual constraint/variables from a mathematical viewpoint. The two ...
2
votes
1answer
69 views

On the stopping criterion of coordinate descent method

I am trying to implement the coordinate descent method to solve the dual of linear SVM problem, but blocked at the stopping criterion. Consider the optimization problem \begin{equation} \min ...
1
vote
2answers
220 views

Applications of duality

We have recently covered linear programming and I am comfortable with the weak and strong duality theorems. However, I don't understand what the applications of duality are that are specific to TCS. ...
4
votes
1answer
338 views

LP Approximation: Primal relaxation + rounding vs. Dual relaxation. Why is the latter better?

Given any Integer Linear Program (ILP) there are 2 ways to approximate it: Write down ILP, convert to LP by relaxing the integer constraints and round the solution Write down the ILP, convert to LP ...
9
votes
2answers
700 views

An intuitive/informal proof for LP Duality?

What would be a good informal/intuitive proof for 'hitting the point home' about LP duality? How best to show that the minimized objective function is indeed the minimum with an intuitive way of ...
14
votes
1answer
311 views

Is it enough for linear program constraints to be satisfied in expectation?

In the paper Randomized Primal-Dual analysis of RANKING for Online Bipartite Matching, while proving that the RANKING algorithm is $\left(1 - \frac{1}{e}\right)$-competitive, the authors show that the ...
1
vote
1answer
549 views

Difference between weak duality and strong duality?

For an optimization problem $(P)$ and its dual $(D)$, I have read about two concepts: Weak Duality, and strong Duality. What I don't understand is how they are different: Weak duality: If $\bar{x}$ ...
1
vote
1answer
494 views

Primal vs dual decomposition methods

I noticed that dual decomposition methods tend to be preferred over primal ones in the large scale optimization literature (here are some examples: (1), (2)). The reason seems to be, from what I ...
7
votes
0answers
413 views

Difference between Primal Dual Algorithm for Proper and Uncrossable Functions

Williamson with many of his co-authors had worked on generalized primal dual algorithms on edge weighted graphs considering three types of functions: (1) super-modular functions (2) proper functions ...
3
votes
1answer
140 views

Primal Dual model in the continuous domain

The continuous max flow problem is posed as follows : sup $\int_\Omega p_s(x)dx$ subject to : $|p(x)| \le C(x); \forall x \in \Omega $ $p_s(x) \le C_s(x); \forall x \in \Omega $ $p_t(x) \le ...
30
votes
1answer
846 views

Toy Examples for Plotkin-Shmoys-Tardos and Arora-Kale solvers

I would like to understand how the Arora-Kale SDP solver approximates the Goemans-Williamson relaxation in nearly linear time, how the Plotkin-Shmoys-Tardos solver approximates fractional "packing" ...
2
votes
2answers
254 views

Necessary and sufficient conditions for the existence of a combinatorial algorithm for a given problem.

Last semester, I took a combinatorial optimization course where the reference book was Combinatorial Optimization by William J. Cook et al. It was very interesting for me to see the relationship ...
12
votes
2answers
1k views

Generalization of the Hungarian algorithm to general undirected graphs?

The Hungarian algorithm is a combinatorial optimization algorithm which solves the maximum weight bipartite matching problem in polynomial time and anticipated the later development of the important ...
4
votes
2answers
271 views

Use of Lagrangian dual information to prove optimalitiy of a solution : Any example?

Can anyone please tell me what is Lagrangian Dual Information and how can it be used to prove the optimality of a solution? I'm talking about the solution to NP-Complete problems. Is it something that ...
5
votes
2answers
341 views

Online learning: Perceptron updates

It seems that the perceptron updates come from some notion of primal-dual updates for convex programs. Can anyone explain how this is true or point to relevant literature?