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- Sidharth Jaggi, Peter Sanders, +4 authors Ludo M. G. M. Tolhuizen
- IEEE Transactions on Information Theory
- 2005

The famous max-flow min-cut theorem states that a source node s can send information through a network (V, E) to a sink node t at a rate determined by the min-cut separating s and t. Recently, it has been shown that this rate can also be achieved for multicasting to several sinks provided that the intermediate nodes are allowed to re-encode the information… (More)

- Sidharth Jaggi, Michael Langberg, +4 authors Michelle Effros
- IEEE Transactions on Information Theory
- 2007

Network coding substantially increases network throughput. But since it involves mixing of information inside the network, a single corrupted packet generated by a malicious node can end up contaminating all the information reaching a destination, preventing decoding. This paper introduces distributed polynomial-time rate-optimal network codes that work in… (More)

- Yaping Li, Hongyi Yao, Minghua Chen, Sidharth Jaggi, Alon Rosen
- INFOCOM
- 2010

By allowing routers to randomly mix the information content in packets before forwarding them, network coding can maximize network throughput in a distributed manner with low complexity. However, such mixing also renders the transmission vulnerable to pollution attacks, where a malicious node injects corrupted packets into the information flow. In a worst… (More)

- Chun Lam Chan, Pak Hou Che, Sidharth Jaggi, Venkatesh Saligrama
- 2011 49th Annual Allerton Conference on…
- 2011

We consider the problem of detecting a small subset of defective items from a large set via non-adaptive “random pooling” group tests. We consider both the case when the measurements are noiseless, and the case2 when the measurements are noisy (the outcome of each group test may be independently faulty with probability q). Order-optimal… (More)

- Chun Lam Chan, Sidharth Jaggi, Venkatesh Saligrama, Samar Agnihotri
- IEEE Transactions on Information Theory
- 2012

We consider some computationally efficient and provably correct algorithms with near-optimal sample complexity for the problem of noisy nonadaptive group testing. Group testing involves grouping arbitrary subsets of items into pools. Each pool is then tested to identify the defective items, which are usually assumed to be sparse. We consider nonadaptive… (More)

- Sidharth Jaggi, M. Langberg, Tracey Ho, Michelle Effros
- Proceedings. International Symposium on…
- 2005

We design codes to transmit information over a network, some subset of which is controlled by a malicious adversary. The computationally unbounded, hidden adversary knows the message to be transmitted, and can observe and change information over the part of the network being controlled. The network nodes do not share resources such as shared randomness or a… (More)

- Girja Sharma, Sidharth Jaggi, B.k. Dey
- 2008 Information Theory and Applications Workshop
- 2008

In this work we show how existing network coding algorithms can be used to perform network tomography, i.e., estimate network topology. We first examine a simple variant of the popular distributed random network codes proposed by (Ho et al.) and show how it can enable each network node to passively estimate the network topology upstream of it at no cost to… (More)

- Pak Hou Che, Mayank Bakshi, Sidharth Jaggi
- 2013 IEEE International Symposium on Information…
- 2013

Alice may wish to reliably send a message to Bob over a binary symmetric channel (BSC) while ensuring that her transmission is deniable from an eavesdropper Willie. That is, if Willie observes a “significantly noisier” transmission than Bob does, he should be unable to estimate even whether Alice is transmitting or not. Even when Alice's… (More)

- Vishal Doshi, Devavrat Shah, Muriel Médard, Sidharth Jaggi
- 2007 Data Compression Conference (DCC'07)
- 2007

We consider the distributed computation of a function of random sources with minimal communication. Specifically, given two discrete memoryless sources, X and Y, a receiver wishes to compute f(X, Y) based on (encoded) information sent from X and Y in a distributed manner. A special case, f(X, Y) = (X, Y), is the classical question of distributed source… (More)

- Mayank Bakshi, Sidharth Jaggi, Michelle Effros
- 2010 IEEE International Symposium on Information…
- 2010

Polar codes have attracted much recent attention as one of the first codes with low computational complexity that provably achieve optimal rate-regions for a large class of information-theoretic problems. One significant drawback, however, is that for current constructions the probability of error decays sub-exponentially in the block-length (more detailed… (More)