AbstractIn this paper we propose a family of algorithms combining tree-clustering with conditioning that trade space for time. Such algorithms are useful for reasoning in probabilistic and deterministic networks as well as for accomplishing optimization tasks. By analyzing the problem structure, the user can select from a spectrum of algorithms, the one that best meets a given time-space specification. To determine the potential of this approach we analyze the structural properties of problems coming from the circuit diagnosis domain. The analysis demonstrates how the tradeoffs associated with various hybrids can be used for each problem instance
We prove the first time-space lower bound tradeoffs for randomized computation of decision problems....
Faced with massive data, is it possible to trade off (statistical) risk, and (computational) space a...
AbstractWe obtain the first non-trivial time–space tradeoff lower bound for functions f:{0, 1}n→{0, ...
AbstractIn this paper we propose a family of algorithms combining tree-clustering with conditioning ...
In this paper we propose a family of algorithms combining treeclustering with conditioning that trad...
AbstractWe present a family of randomized algorithms that enjoys a wide range of time–space trade-of...
AbstractWe investigate time-space tradeoffs for traversing undirected graphs, using a variety of str...
Thesis (M.S.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer S...
We study the fundamental problem of sorting in a sequential model of computation and in particular c...
We extend recent techniques for time-space tradeoff lower bounds using multiparty communication comp...
Recursive Conditioning, RC, is an any-space algorithm for exact inference in Bayesian networks, whi...
. We initiate a study of space-time tradeoffs in the cell-probe model under restricted preprocessing...
We consider data-structures for answering reachability and distance queries on constant-treewidth gr...
Dynamic programming on path and tree decompositions of graphs is a technique that is ubiquitous in t...
For many algorithmic problems on graphs of treewidth t , a standard dynamic programming approach giv...
We prove the first time-space lower bound tradeoffs for randomized computation of decision problems....
Faced with massive data, is it possible to trade off (statistical) risk, and (computational) space a...
AbstractWe obtain the first non-trivial time–space tradeoff lower bound for functions f:{0, 1}n→{0, ...
AbstractIn this paper we propose a family of algorithms combining tree-clustering with conditioning ...
In this paper we propose a family of algorithms combining treeclustering with conditioning that trad...
AbstractWe present a family of randomized algorithms that enjoys a wide range of time–space trade-of...
AbstractWe investigate time-space tradeoffs for traversing undirected graphs, using a variety of str...
Thesis (M.S.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer S...
We study the fundamental problem of sorting in a sequential model of computation and in particular c...
We extend recent techniques for time-space tradeoff lower bounds using multiparty communication comp...
Recursive Conditioning, RC, is an any-space algorithm for exact inference in Bayesian networks, whi...
. We initiate a study of space-time tradeoffs in the cell-probe model under restricted preprocessing...
We consider data-structures for answering reachability and distance queries on constant-treewidth gr...
Dynamic programming on path and tree decompositions of graphs is a technique that is ubiquitous in t...
For many algorithmic problems on graphs of treewidth t , a standard dynamic programming approach giv...
We prove the first time-space lower bound tradeoffs for randomized computation of decision problems....
Faced with massive data, is it possible to trade off (statistical) risk, and (computational) space a...
AbstractWe obtain the first non-trivial time–space tradeoff lower bound for functions f:{0, 1}n→{0, ...