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- Yossi Azar, Andrei Z. Broder, Anna R. Karlin, Eli Upfal
- SIAM J. Comput.
- 1999

Suppose that we sequentially place n balls into n boxes by putting each ball into a randomly chosen box. It is well known that when we are done, the fullest box has with high probability (1 + o(1)) lnn/ ln lnn balls in it. Suppose instead that for each ball we choose two boxes at random and place the ball into the one which is less full at the time of… (More)

- Prabhakar Raghavan, Eli Upfal
- STOC
- 1994

Communication in all-optical networks requires novel routing paradigms. The high bandwidth of the optic fiber is utilized through wavelengthdivision multiplexing: a single physical optical link can carry several logical signals, provided that they are transmitted on different wavelengths. We study the problem of routing a set of requests (each of which is a… (More)

The analysis of matrices associated with discrete, pairwise comparisons can be a very useful toolbox for a computer scientist. In particular, Spectral Graph Theory is based on the observation that eigenvalues and eigenvectors of these matrices betray a lot of properties of graphs associated with them. The first major section of this paper is a survey of key… (More)

- David Peleg, Eli Upfal
- J. ACM
- 1989

Two conflicting goals play a crucial role in the design of routing schemes for communication networks. A routing scheme should use paths that are as short as possible for routing messages in the network, while keeping the routing information stored in the processors' local memory as succinct as possible. The efficiency of a routing scheme is measured in… (More)

- Robert D. Kleinberg, Aleksandrs Slivkins, Eli Upfal
- STOC
- 2008

In a multi-armed bandit problem, an online algorithm chooses from a set of strategies in a sequence of $n$ trials so as to maximize the total payoff of the chosen strategies. While the performance of bandit algorithms with a small finite strategy set is quite well understood, bandit problems with large strategy sets are still a topic of very active… (More)

- Uriel Feige, Prabhakar Raghavan, David Peleg, Eli Upfal
- SIAM J. Comput.
- 1994

This paper studies the depth of noisy decision trees in which each node gives the wrong answer with some constant probability. In the noisy Boolean decision tree model, tight bounds are given on the number of queries to input variables required to compute threshold functions, the parity function and symmetric functions. In the noisy comparison tree model,… (More)

- Uriel Feige, David Peleg, Prabhakar Raghavan, Eli Upfal
- SIGAL International Symposium on Algorithms
- 1990

- Fabio Vandin, Eli Upfal, Benjamin J. Raphael
- RECOMB
- 2011

Next-generation DNA sequencing technologies are enabling genome-wide measurements of somatic mutations in large numbers of cancer patients. A major challenge in the interpretation of these data is to distinguish functional "driver mutations" important for cancer development from random "passenger mutations." A common approach for identifying driver… (More)

- Gopal Pandurangan, Prabhakar Raghavan, Eli Upfal
- COCOON
- 2002

Recent work on modeling the Web graph has dwelt on capturing the degree distributions observed on the Web. Pointing out that this represents a heavy reliance on “local” properties of the Web graph, we study the distribution of PageRank values (used in the Google search engine) on the Web. This distribution is of independent interest in optimizing search… (More)

- Andrei Z. Broder, Alan M. Frieze, Eli Upfal
- SODA
- 1993

We analyze the pure literal rule heuristic for computing a satisfying assignment to a random 3-CNF formula with n variables. We show that the pure literal rule by itself finds satisfying assignments for almost all 3-CNF formulas with up to 1.63n clauses, but it fails for more than 1.7n clauses. As an aside we show that the value of maximum satisfiability… (More)