Distribution-sensitive data structures attempt to exploit patterns in query distributions in order to allow many sequences of queries execute faster than in traditional data structures. In this paper, we survey the history of such data structures, outline open problems in the area, and offer some new results
We design novel, asymptotically more efficient data structures and algorithms for programs whose dat...
The demand of efficient data structures for query processing on massive data sets has grown tremendo...
Inductive databases are databases in which models and patterns are first class citizens. Having mode...
The time required for a sequence of operations on a data structure is usually measured in terms of t...
In spite of the amount of work recently devoted to distributed systems, distributed applications ar...
Many data sets follow certain distribution patterns, such as uniform distribution, normal distributi...
We study lazy structure sharing as a tool for optimizing equivalence testing on complex data types, ...
In this dissertation, we make progress on certain algorithmic problems broadly over two computationa...
zAlthough there are many advanced and specialized texts and handbooks on algorithms, until now there...
The purpose of this paper is to analyze the maxima properties (value and position) of some data stru...
Abstract. In recent past, work has been done to parallelize pattern detection queries over event str...
Modern large distributed applications, such as mobile communications and banking services, require f...
Distribution testing is a crucial area at the interface of statistics and algorithms, where one wish...
Distinguishing sequential patterns are useful in characterizing a given sequence class and contrasti...
Visualization applications implicitly run queries on the data to re-trieve distributions and statist...
We design novel, asymptotically more efficient data structures and algorithms for programs whose dat...
The demand of efficient data structures for query processing on massive data sets has grown tremendo...
Inductive databases are databases in which models and patterns are first class citizens. Having mode...
The time required for a sequence of operations on a data structure is usually measured in terms of t...
In spite of the amount of work recently devoted to distributed systems, distributed applications ar...
Many data sets follow certain distribution patterns, such as uniform distribution, normal distributi...
We study lazy structure sharing as a tool for optimizing equivalence testing on complex data types, ...
In this dissertation, we make progress on certain algorithmic problems broadly over two computationa...
zAlthough there are many advanced and specialized texts and handbooks on algorithms, until now there...
The purpose of this paper is to analyze the maxima properties (value and position) of some data stru...
Abstract. In recent past, work has been done to parallelize pattern detection queries over event str...
Modern large distributed applications, such as mobile communications and banking services, require f...
Distribution testing is a crucial area at the interface of statistics and algorithms, where one wish...
Distinguishing sequential patterns are useful in characterizing a given sequence class and contrasti...
Visualization applications implicitly run queries on the data to re-trieve distributions and statist...
We design novel, asymptotically more efficient data structures and algorithms for programs whose dat...
The demand of efficient data structures for query processing on massive data sets has grown tremendo...
Inductive databases are databases in which models and patterns are first class citizens. Having mode...