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There has been a lot of recent work on Bayesian methods for reinforcement learning exhibiting near-optimal online performance. The main obstacle facing such methods is that in most problems of interest, the optimal solution involves planning in an infinite ...
We study the problem of distributed estimation, where a set of nodes are required to collectively estimate some parameter of interest from their measurements. Diffusion algorithms have been shown to achieve good performance, increased robustness and are am ...
Many read-intensive systems where fast access to data is more important than the rate at which data can change make use of multidimensional index structures, like the generalized search tree (GiST). Although in these systems the indexed data are rarely upd ...
We present a novel approach to 3D delineation of dendritic networks in noisy image stacks. We achieve a level of automation beyond that of state-of-the-art systems, which model dendrites as continuous tubular structures and postulate simple appearance mode ...
We initiate a program to generalize the standard eikonal approximation to compute amplitudes in Anti-de Sitter spacetimes. Inspired by the shock wave derivation of the eikonal amplitude in flat space, we study the two-point function epsilon similar to < O1 ...
Top-k query processing is a fundamental building block for efficient ranking in a large number of applications. Efficiency is a central issue, especially for distributed settings, when the data is spread across different nodes in a network. This paper intr ...
Multiple-input multiple-output (MIMO) detection algorithms providing soft information for a subsequent channel decoder pose significant implementation challenges due to their high computational complexity. In this paper, we show how sphere decoding can be ...
This paper presents a receiver-driven video delivery algorithm that exploits a novel Randomized Network Coding (RNC) scheme for unequal error protection (UEP). The main idea of our approach is to account for the unequal importance of media packets in the n ...
Many different algorithms developed in statistical physics, coding theory, signal processing, and artificial intelligence can be expressed by graphical models and solved (either exactly or approximately) with iterative message-passing algorithms on the mod ...
This paper proposes a tree-based pursuit algorithm that efficiently trades off complexity and approximation performance for overcomplete signal expansions. Finding the sparsest representation of a signal using a redundant dictionary is, in general, a NP-Ha ...