AbstractThe optimal competitive ratio for a randomized online list update algorithm is known to be at least 1.5 and at most 1.6, but the remaining gap is not yet closed. We present a new lower bound of 1.50084 for the partial cost model. The construction is based on game trees with incomplete information, which seem to be generally useful for the competitive analysis of online algorithms
We consider the list access problem and show that two unrealistic assumptions in the original cost m...
We study a fundamental model of online preference aggregation, where an algorithm maintains an order...
We consider the online Min-Sum Set Cover (MSSC), a natural and intriguing generalization of the clas...
AbstractThe optimal competitive ratio for a randomized online list update algorithm is known to be a...
COUNTER algorithms, a family of randomized algorithms for the list update problem, were introduced b...
The list update problem is a classical online problem, with an optimal competitive ratio that is sti...
The list update problem is a classical online problem, with an optimal competitive ratio that is sti...
We study the fundamental list update problem in the paid exchange model P^d. This cost model was int...
The best randomized on-line algorithms known so far for the list update problem achieve a competitiv...
AbstractWe consider the list update problem under a sequence of requests for sets of items, and for ...
AbstractWe consider the question of lookahead in the list update problem: What improvement can be ac...
Online search is a basic online problem. The fact that its optimal deterministic/randomized solution...
In this paper we present some deterministic and randomized algorithms for the Weight List Update Pro...
We use game theory techniques to automatically compute improved lower bounds on the competitive rati...
We consider the question of lookahead in the list update problem: What improvement can be achieved i...
We consider the list access problem and show that two unrealistic assumptions in the original cost m...
We study a fundamental model of online preference aggregation, where an algorithm maintains an order...
We consider the online Min-Sum Set Cover (MSSC), a natural and intriguing generalization of the clas...
AbstractThe optimal competitive ratio for a randomized online list update algorithm is known to be a...
COUNTER algorithms, a family of randomized algorithms for the list update problem, were introduced b...
The list update problem is a classical online problem, with an optimal competitive ratio that is sti...
The list update problem is a classical online problem, with an optimal competitive ratio that is sti...
We study the fundamental list update problem in the paid exchange model P^d. This cost model was int...
The best randomized on-line algorithms known so far for the list update problem achieve a competitiv...
AbstractWe consider the list update problem under a sequence of requests for sets of items, and for ...
AbstractWe consider the question of lookahead in the list update problem: What improvement can be ac...
Online search is a basic online problem. The fact that its optimal deterministic/randomized solution...
In this paper we present some deterministic and randomized algorithms for the Weight List Update Pro...
We use game theory techniques to automatically compute improved lower bounds on the competitive rati...
We consider the question of lookahead in the list update problem: What improvement can be achieved i...
We consider the list access problem and show that two unrealistic assumptions in the original cost m...
We study a fundamental model of online preference aggregation, where an algorithm maintains an order...
We consider the online Min-Sum Set Cover (MSSC), a natural and intriguing generalization of the clas...