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- Don Coppersmith, Lisa Fleischer, Atri Rudra
- ACM Trans. Algorithms
- 2005

We consider the following simple algorithm for feedback arc set problem in weighted tournaments --- order the vertices by their weighted indegrees. We show that this algorithm has an approximation guarantee of 5 if the weights satisfy <i>probability constraints</i> (for any pair of vertices <i>u</i> and <i>v, w</i><inf><i>uv</i></inf> +… (More)

- Venkatesan Guruswami, Atri Rudra
- IEEE Transactions on Information Theory
- 2008

In this paper, we present error-correcting codes that achieve the information-theoretically best possible tradeoff between the rate and error-correction radius. Specifically, for every 0 < R < 1 and epsiv < 0, we present an explicit construction of error-correcting codes of rate that can be list decoded in polynomial time up to a fraction (1- R -… (More)

- Ning Chen, Nicole Immorlica, Anna R. Karlin, Mohammad Mahdian, Atri Rudra
- ICALP
- 2009

Motivated by applications in online dating and kidney exchange , we study a stochastic matching problem in which we have a random graph G given by a node set V and probabilities p(i, j) on all pairs i, j ∈ V representing the probability that edge (i, j) exists. Additionally, each node has an integer weight t(i) called its patience parameter. Nodes represent… (More)

- Avrim Blum, Vijay Kumar, Atri Rudra, Felix Wu
- SODA
- 2003

We consider the problem of revenue maximization in online auctions, that is, auctions in which bids are received and dealt with one-by-one. In this paper, we demonstrate that results from online learning can be usefully applied in this context, and we derive a new auction for digital goods that achieves a constant competitive ratio with respect to the… (More)

- Venkatesan Guruswami, Atri Rudra
- STOC
- 2005

For every 0 < R < 1 and ε > 0, we present an explicit construction of error-correcting codes of rate R that can be list decoded in polynomial time up to a fraction (1-R-ε) of errors. These codes achieve the "capacity" for decoding from <i>adversarial</i> errors, i.e., achieve the <i>optimal</i> trade-off between rate and error-correction… (More)

- Nikhil Bansal, Anupam Gupta, Jian Li, Julián Mestre, Viswanath Nagarajan, Atri Rudra
- Algorithmica
- 2010

Consider a random graph model where each possible edge e is present independently with some probability p e . Given these probabilities, we want to build a large/heavy matching in the randomly generated graph. However, the only way we can find out whether an edge is present or not is to query it, and if the edge is indeed present in the graph, we are forced… (More)

- Ning Chen, Roee Engelberg, C. Thach Nguyen, Prasad Raghavendra, Atri Rudra, Gyanit Singh
- Algorithmica
- 2007

A star graph is a tree of diameter at most two. A star forest is a graph that consists of node-disjoint star graphs. In the spanning star forest problem, given an unweighted graph G, the objective is to find a star forest that contains all vertices of G and has the maximum number of edges. This problem is the complement of the dominating set problem in the… (More)

We explore the use of subfield arithmetic for efficient implementations of Galois Field arithmetic especially in the context of the Rijndael block cipher. Our technique involves mapping field elements to a composite field representation. We describe how to select a representation which minimizes the computation cost of the relevant arithmetic, taking into… (More)

- Piotr Indyk, Hung Q. Ngo, Atri Rudra
- SODA
- 2010

We consider the following "efficiently decodable" non-adaptive group testing problem. There is an unknown string <i>x</i> ∈ {0, 1}<i><sup>n</sup></i> with at most <i>d</i> ones in it. We are allowed to test any subset <i>S</i> ⊆ [<i>n</i>] of the indices. The answer to the test tells whether <i>x</i><sub><i>i</i></sub> = 0 for all <i>i</i>… (More)

- Hung Q. Ngo, Ely Porat, Christopher Ré, Atri Rudra
- PODS
- 2012

Efficient join processing is one of the most fundamental and well-studied tasks in database research. In this work, we examine algorithms for natural join queries over many relations and describe a novel algorithm to process these queries optimally in terms of worst-case data complexity. Our result builds on recent work by Atserias, Grohe, and Marx, who… (More)