Results 1 - 10 of 403

On the Approximability of Reachability Preserving Network Orientations

by Michael Elberfeld, Vineet Bafna, Iftah Gamzu, Alexander Medvedovsky, Danny Segev, Dana Silverbush, Uri Zwick, Roded Sharan
"... We introduce a graph orientation problem arising in the study of biological networks. Given an undirected graph and a list of ordered source-target vertex pairs, the goal is to orient the graph such that a maximum number of pairs admit a directed source-to-target path. We study the complexity and ap ..."
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We introduce a graph orientation problem arising in the study of biological networks. Given an undirected graph and a list of ordered source-target vertex pairs, the goal is to orient the graph such that a maximum number of pairs admit a directed source-to-target path. We study the complexity

Policy gradient methods for reinforcement learning with function approximation.

by Richard S Sutton , David Mcallester , Satinder Singh , Yishay Mansour - In NIPS, , 1999
"... Abstract Function approximation is essential to reinforcement learning, but the standard approach of approximating a value function and determining a policy from it has so far proven theoretically intractable. In this paper we explore an alternative approach in which the policy is explicitly repres ..."
Abstract - Cited by 439 (20 self) - Add to MetaCart
policy. Large applications of reinforcement learning (RL) require the use of generalizing function approximators such neural networks, decision-trees, or instance-based methods. The dominant approach for the last decade has been the value-function approach, in which all function approximation effort goes

Taming the computational complexity of combinatorial auctions: Optimal and approximate approaches

by Yuzo Fujishima, Kevin Leyton-brown, Yoav Shoham , 1999
"... In combinatorial auctions, multiple goods are sold simultaneously and bidders may bid for arbitrary combinations of goods. Determining the outcome of such an auction is an optimization problem that is NP-complete in the general case. We propose two methods of overcoming this apparent intractability. ..."
Abstract - Cited by 288 (9 self) - Add to MetaCart
. For example, auctions and other market mechanisms are used in network bandwidth allocation, distributed configuration design, factory scheduling, and operating system memory allocation [Clearwater, 1996]. Market-oriented programming has

Approximation Algorithms for NETWORK DESIGN AND ORIENTEERING

by Nitish John Korula , 2010
"... This thesis presents approximation algorithms for some N P-Hard combinatorial optimization problems on graphs and networks; in particular, we study problems related to Network Design. Under the widely-believed complexity-theoretic assumption that P ̸ = N P, there are no efficient (i.e., polynomial-t ..."
Abstract - Cited by 1 (0 self) - Add to MetaCart
This thesis presents approximation algorithms for some N P-Hard combinatorial optimization problems on graphs and networks; in particular, we study problems related to Network Design. Under the widely-believed complexity-theoretic assumption that P ̸ = N P, there are no efficient (i.e., polynomial

Approximation Algorithms for Orienting Mixed Graphs

by Michael Elberfeld, Danny Segev, Colin R. Davidson, Dana Silverbush, Roded Sharan
"... Abstract. Graph orientation is a fundamental problem in graph theory that has recently arisen in the study of signaling-regulatory pathways in protein networks. Given a graph and a list of ordered source-target vertex pairs, it calls for assigning directions to the edges of the graph so as to maximi ..."
Abstract - Cited by 8 (2 self) - Add to MetaCart
, was left open. Here we give the first approximation algorithm to this problem. Our algorithm provides a sub-linear guarantee in the general case, and logarithmic guarantees for structured instances. Key words: protein-protein interaction network, mixed graph, graph orientation, approximation algorithm 1

RANDOM SAMPLING IN CUT, FLOW, AND NETWORK DESIGN PROBLEMS

by David R. Karger , 1999
"... We use random sampling as a tool for solving undirected graph problems. We show that the sparse graph, or skeleton, that arises when we randomly sample a graph’s edges will accurately approximate the value of all cuts in the original graph with high probability. This makes sampling effective for pro ..."
Abstract - Cited by 101 (12 self) - Add to MetaCart
other cut-based problems, including approximating the best balanced cut of a graph, finding a k-connected orientation of a 2k-connected graph, and finding integral multicommodity flows in graphs with a great deal of excess capacity. Our methods also improve the efficiency of some parallel cut and flow

Improved Orientations of Physical Networks

by Iftah Gamzu, Danny Segev, Roded Sharan
"... Abstract. The orientation of physical networks is a prime task in deciphering the signaling-regulatory circuitry of the cell. One manifestation of this computational task is as a maximum graph orientation problem, where given an undirected graph on n vertices and a collection of vertex pairs, the go ..."
Abstract - Cited by 10 (5 self) - Add to MetaCart
Abstract. The orientation of physical networks is a prime task in deciphering the signaling-regulatory circuitry of the cell. One manifestation of this computational task is as a maximum graph orientation problem, where given an undirected graph on n vertices and a collection of vertex pairs

Improved Algorithms for Orienteering and Related Problems

by Chandra Chekuri, Nitish Korula, Martin Pal , 2007
"... In this paper we consider the orienteering problem in undirected and directed graphs and obtain improved approximation algorithms. The point to point-orienteering-problem is the following: Given an edgeweighted graph G = (V, E) (directed or undirected), two nodes s, t ∈ V and a budget B, find an s-t ..."
Abstract - Cited by 53 (5 self) - Add to MetaCart
In this paper we consider the orienteering problem in undirected and directed graphs and obtain improved approximation algorithms. The point to point-orienteering-problem is the following: Given an edgeweighted graph G = (V, E) (directed or undirected), two nodes s, t ∈ V and a budget B, find an s

Rate performance objectives of multihop wireless networks

by Bozidar Radunovic, Jean-Yves Le Boudec - IEEE TRANS. MOB. COMPUT , 2004
"... We consider the question of what performance metric to maximize when designing ad hoc wireless network protocols such as routing or MAC. We focus on maximizing rates under battery-lifetime and power constraints. Commonly used metrics are total capacity (in the case of cellular networks) and transpo ..."
Abstract - Cited by 89 (1 self) - Add to MetaCart
) and transport capacity (in the case of ad hoc networks). However, it is known in traditional wired networking that maximizing total capacity conflicts with fairness, and this is why fairness-oriented rate allocations, such as maxmin fairness, are often used. We review this issue for wireless ad hoc networks

Optimally orienting physical networks

by Dana Silverbush, Michael Elberfeld, Roded Sharan - In Proceedings of the 15th Annual International Conference on Research in Computational Molecular Biology (RECOMB 2011), volume 6577 of LNCS , 2011
"... Abstract. In a network orientation problem one is given a mixed graph, consisting of directed and undirected edges, and a set of source-target vertex pairs. The goal is to orient the undirected edges so that a maximum number of pairs admit a directed path from the source to the target. This problem ..."
Abstract - Cited by 9 (4 self) - Add to MetaCart
Abstract. In a network orientation problem one is given a mixed graph, consisting of directed and undirected edges, and a set of source-target vertex pairs. The goal is to orient the undirected edges so that a maximum number of pairs admit a directed path from the source to the target. This problem
Results 1 - 10 of 403