Recent Papers

(Also available in DBLP list and Citations)
Approximation Schemes for Minimizing Average Weighted Completion Time with Release Dates (.PS Format)


In proceedings of FOCS99, 1999

Foto Afrati, Evripidis bampis, Chandra Chekuri , David Karger, Claire Kenyon, Sanjeen Khanna, Ioannis Milis, Maurice Queyranne, Martin Skutella, Cliff Stein  and Maxim Sviridenko

 Abstract. We consider the problem of scheduling n jobs with release dates on m machines so as to minimize their average weighted completion time. We present the first known polynomial time approximation schemes for several variants of this problem. Our results include PTASs for the case of identical parallel machines and a constant number of unrelated machines with and without preemption allowed. Our schemes are efficient: for all variants the running time for a (1+e) approximation is of the form ¦(1/e, m) poly(n).

Answering Queries Using Materialized Views with Disjunctions (.PS Format)


In proceedings of ICDT99, 1999

Foto Afrati, Manolis Gergatsoulis, and Theodoros Kavalieros.

Abstract: We consider the problem of answering datalog queries using materialized views. More specifically, queries are rewritten to refer to views instead of the base relations over which the queries were originally written. Much work has been done on program rewriting that produces an equivalent query. In the context of information integration, though, the importance of using views to infer as many answers as possible has been pointed out. Formally, the problem is: Given a datalog program r is there a datalog program ruwhich uses only views as EDB predicates and (i) produces a subset of the answers that r produces and (ii) any other program ru˘over the views with property (i) is contained in ru? In this paper we investigate the problem in the case of disjunctive view definitions.

Datalog Trees and Their Automata (.PS Format)
In proceedings of the 2nd Pan Hellenic Symposium on Logic, Delphi 1999
Foto Afrati, Eugenie Foustoucos, and Theodore Andronikos.
 
Definability and Compression  (.PS Format)


In proceedings of LICS, 2000

Foto Afrati, Hans Lei? and Michel de Rougemont

 Abstract. A compression algorithm takes a finite structure of a class K as input and produces a finite structure of a different class K' as output. Given a property P on a class K defined in a logic L, we study the definability of property P on the class K'. We consider two compression schemas on unary ordered structures (words), compression by run-length encoding and the classical Lemel-Ziv. First-order properties of strings are first-order on run-length compressed strings, but this fails for images, i.e. 2-dimentional strings. We present simple first-order properties of strings which are not first-order definable on strings compressed with the Lempel-Ziv compression schema. We show that all properties of strings that are first-order definable on strings are definable on Lempel-Ziv compressed strings in FO(TC), the extension of first-order logic with the transitive closure operator. We define a subclass F of the first-order properties of strings such that if L is defined by a property in F, it is also first-order definable on Lempel-Ziv compressed strings. Monadic second-order properties of strings are dyadic second order definable on lempel-Zev compressed strings.

Generating Efficient Plans for Queries Using Views (.PS Format)
Foto Afrati, Chen Li, and Jeff Ullman
In Proceedings of the 30th ACM SIGMOD Conference, Santa Barbara, CA, May, 2001.
 Abstract. We study the problem of generating efficient, equivalent rewritings using views to compute the answer to a query. We take the closed­world assumption, in which views are materialized from base relations, rather than views describing sources in terms of abstract predicates, as is common when the open­world assumption is used. In the closed­world model, there can be an infinite number of different rewritings that compute the same answer, yet have quite different performance. Query optimizers take a logical plan (a rewriting of the query) as an input, and generate efficient physical plans to compute the answer. Thus our goal is to generate a small subset of the possible logical plans without missing an optimal physical plan. We first consider a cost model that counts the number of subgoals in a physical plan, and show a search space that is guaranteed to include an optimal rewriting, if the query has a rewriting in terms of the views. We also develop an
efficient algorithm for finding rewritings with the minimum number of subgoals. We then consider a cost model that counts the sizes of intermediate relations of a physical plan, without dropping any attributes, and give a search space for finding optimal rewritings. Our final cost model allows attributes to be dropped in  intermediate relations. We show that, by careful variable renaming, it is possible to do better than the standard ``supplementary relation'' approach, by dropping attributes that the latter approach would retain. Experiments show that our algorithm of generating optimal rewritings has good efficiency and scalability.
Answering Queries Using Views with Arithmetic
   Comparisons. Foto Afrati, Chen Li, and Prasenjit Mitra. To appear in ACM Symposium on Principles of Database Systems (PODS), June 3-6, 2002 Madison, Wisconsin.(.PS Format)
 
Scheduling to minimize the average completion time of dedicated tasks(.PS Format)
Foto Afrati, Evripidis Bampis, Aleksei V. Fishkin, Klaus Jansen, and Claire Kenyon.
In Proceedings of the FSTTCS 2000, K. Sanjiv, P. Sanjiva (Eds), New Delhi, LNCS 1974, 2000, 454-464.
Designing PTASs for MIN-SUM Scheduling Problems.
(.PS Format)
Foto Afrati, Ioannis Milis
In proceedings of WEA 2001
 
On Approximation Algorithms for Data Mining Applications
(.PS Format)
Foto Afrati  (To be considered for publication in the book Approximation Algorithms to be edited by E. Bampis,K. Jansen and C. Kenyon)

 

IWe aim to present current trends in the theoretical computer science research on topics, which have applications in data mining. We briefly describe data mining tasks in various application contexts. We give an overview of some of the questions and algorithms issues that are of concern when mining huge amounts of data that do not fit in main memory.