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Chen, Jingsen
Publications (10 of 28) Show all publications
Chen, J., Edelkamp, S., Elmasry, A. & Katajainen, J. (2012). In-place heap construction with optimized comparisons, moves, and cache misses (ed.). In: (Ed.), Branislav Rovan; Vladimiro Sassone ; Peter Widmayer (Ed.), Mathematical foundations of computer science 2012: 37th international symposium, MFCS 2012, Bratislava, Slovakia, August 27-31, 2012 : proceedings. Paper presented at International Symposium on Mathematical Foundations of Computer Science : 27/08/2012 - 31/08/2012 (pp. 259-270). Berlin: Encyclopedia of Global Archaeology/Springer Verlag
Open this publication in new window or tab >>In-place heap construction with optimized comparisons, moves, and cache misses
2012 (English)In: Mathematical foundations of computer science 2012: 37th international symposium, MFCS 2012, Bratislava, Slovakia, August 27-31, 2012 : proceedings / [ed] Branislav Rovan; Vladimiro Sassone ; Peter Widmayer, Berlin: Encyclopedia of Global Archaeology/Springer Verlag, 2012, p. 259-270Conference paper, Published paper (Refereed)
Abstract [en]

We show how to build a binary heap in-place in linear time by performing ~ 1.625n element comparisons, at most ~ 2.125n element moves, and ~ n/B cache misses, where n is the size of the input array, B the capacity of the cache line, and ~ f(n) approaches f(n) as n grows. The same bound for element comparisons was derived and conjectured to be optimal by Gonnet and Munro; however, their procedure requires Θ(n) pointers and does not have optimal cache behaviour. Our main idea is to mimic the Gonnet-Munro algorithm by converting a navigation pile into a binary heap. To construct a binary heap in-place, we use this algorithm to build bottom heaps of size and adjust the heap order at the upper levels using Floyd's sift-down procedure. On another frontier, we compare different heap-construction alternatives in practice.

Place, publisher, year, edition, pages
Berlin: Encyclopedia of Global Archaeology/Springer Verlag, 2012
Series
Lecture Notes in Computer Science, ISSN 0302-9743 ; 7464
National Category
Computer Sciences
Research subject
Dependable Communication and Computation Systems
Identifiers
urn:nbn:se:ltu:diva-27310 (URN)10.1007/978-3-642-32589-2_25 (DOI)2-s2.0-84864976736 (Scopus ID)0b993c78-df53-4868-92c0-a861554a87a6 (Local ID)9783642325885 (ISBN)0b993c78-df53-4868-92c0-a861554a87a6 (Archive number)0b993c78-df53-4868-92c0-a861554a87a6 (OAI)
Conference
International Symposium on Mathematical Foundations of Computer Science : 27/08/2012 - 31/08/2012
Note
Validerad; 2012; 20120827 (andbra)Available from: 2016-09-30 Created: 2016-09-30 Last updated: 2018-07-10Bibliographically approved
Bengtsson, F. & Chen, J. (2007). Computing maximum-scoring segments optimally (ed.). Luleå: Luleå tekniska universitet
Open this publication in new window or tab >>Computing maximum-scoring segments optimally
2007 (English)Report (Other academic)
Abstract [en]

Given a sequence of length n, the problem studied in this report is to find a set of k disjoint subsequences of consecutive elements such that the total sum of all elements in the set is maximized. This problem arises in the analysis of DNA sequences. The previous best known algorithm requires time proportional to n times the inverse Ackermann function of (n,n), in the worst case. We present a linear-time algorithm, which is optimal, for this problem.

Place, publisher, year, edition, pages
Luleå: Luleå tekniska universitet, 2007. p. 10
Series
Research report / Luleå University of Technology, ISSN 1402-1528 ; 2007:3
National Category
Computer Sciences
Research subject
Dependable Communication and Computation Systems
Identifiers
urn:nbn:se:ltu:diva-22852 (URN)48a93dc0-5d75-11dc-8151-000ea68e967b (Local ID)48a93dc0-5d75-11dc-8151-000ea68e967b (Archive number)48a93dc0-5d75-11dc-8151-000ea68e967b (OAI)
Note
Godkänd; 2007; 20070907 (ysko)Available from: 2016-09-29 Created: 2016-09-29 Last updated: 2018-01-10Bibliographically approved
Bengtsson, F. & Chen, J. (2007). Ranking k maximum sums (ed.). Theoretical Computer Science, 377(1-3), 229-237
Open this publication in new window or tab >>Ranking k maximum sums
2007 (English)In: Theoretical Computer Science, ISSN 0304-3975, E-ISSN 1879-2294, Vol. 377, no 1-3, p. 229-237Article in journal (Refereed) Published
Abstract [en]

Given a sequence of n real numbers and an integer parameter k, the problem studied in this paper is to compute k subsequences of consecutive elements with the sums of their elements being the largest, the second largest, and the kth largest among all possible range sums of the input sequence. For any value of k, 1 <= k <= n (n + 1)/2, we design a fast algorithm that takes O (n + k log n) time in the worst case to compute and rank all such subsequences. We also prove that our algorithm is optimal for k = O (n) by providing a matching lower bound.Moreover, our algorithm is an improvement over the previous results on the maximum sum subsequences problem (where only the subsequences are requested and no ordering with respect to their relative sums will be determined).Furthermore, given the fact that we have computed the fth largest sums, our algorithm retrieves the (l + 1)th largest sum in O (log n) time, after O (n) time of preprocessing.

National Category
Computer Sciences
Research subject
Dependable Communication and Computation Systems
Identifiers
urn:nbn:se:ltu:diva-2927 (URN)10.1016/j.tcs.2007.03.011 (DOI)000247279200017 ()2-s2.0-34247634994 (Scopus ID)0a9d4820-5ac1-11dc-8a1d-000ea68e967b (Local ID)0a9d4820-5ac1-11dc-8a1d-000ea68e967b (Archive number)0a9d4820-5ac1-11dc-8a1d-000ea68e967b (OAI)
Note
Validerad; 2007; 20070904 (pafi)Available from: 2016-09-29 Created: 2016-09-29 Last updated: 2018-07-10Bibliographically approved
Bengtsson, F. & Chen, J. (2006). Computing maximum-scoring segments in almost linear time (ed.). Luleå: Luleå tekniska universitet
Open this publication in new window or tab >>Computing maximum-scoring segments in almost linear time
2006 (English)Report (Other academic)
Abstract [en]

Given a sequence, the problem studied in this paper is to find a set of k disjoint continuous subsequences such that the total sum of all elements in the set is maximized. This problem arises naturally in the analysis of DNA sequences. The previous best known algorithm requires n log n time in the worst case. For a given sequence of length n, we present an almost linear-time algorithm for this problem. Our algorithm uses a disjoint-set data structure and requires O(n a(n, n) ) time in the worst case, where a(n,n) is the inverse Ackermann function.

Place, publisher, year, edition, pages
Luleå: Luleå tekniska universitet, 2006. p. 21
Series
Research report / Luleå University of Technology, ISSN 1402-1528 ; 2006:14
National Category
Computer Sciences
Research subject
Dependable Communication and Computation Systems
Identifiers
urn:nbn:se:ltu:diva-25447 (URN)f3c6bb30-b210-11db-bf9d-000ea68e967b (Local ID)f3c6bb30-b210-11db-bf9d-000ea68e967b (Archive number)f3c6bb30-b210-11db-bf9d-000ea68e967b (OAI)
Note
Godkänd; 2006; 20070201 (ysko)Available from: 2016-09-29 Created: 2016-09-29 Last updated: 2018-01-10Bibliographically approved
Bengtsson, F. & Chen, J. (2006). Computing maximum-scoring segments in almost linear time (ed.). In: (Ed.), Danny Z. Chen (Ed.), Computing and Combinatorics: 12th annual international conference, COCOON 2006, Taipei, Taiwan, August 15 - 18, 2006 ; proceedings. Paper presented at Annual International Computing and Combinatorics Conference : 15/08/2006 - 18/08/2006 (pp. 255-264). : Encyclopedia of Global Archaeology/Springer Verlag
Open this publication in new window or tab >>Computing maximum-scoring segments in almost linear time
2006 (English)In: Computing and Combinatorics: 12th annual international conference, COCOON 2006, Taipei, Taiwan, August 15 - 18, 2006 ; proceedings / [ed] Danny Z. Chen, Encyclopedia of Global Archaeology/Springer Verlag, 2006, p. 255-264Conference paper, Published paper (Refereed)
Abstract [en]

Given a sequence, the problem studied in this paper is to find a set of k disjoint continuous subsequences such that the total sum of all elements in the set is maximized. This problem arises naturally in the analysis of DNA sequences. The previous best known algorithm requires Θ(n log n) time in the worst case. For a given sequence of length n, we present an almost linear-time algorithm for this problem. Our algorithm uses a disjoint-set data structure and requires O(nα(n, n)) time in the worst case, where α(n, n) is the inverse Ackermann function.

Place, publisher, year, edition, pages
Encyclopedia of Global Archaeology/Springer Verlag, 2006
Series
Lecture Notes in Computer Science, ISSN 0302-9743 ; 4112
National Category
Computer Sciences
Research subject
Dependable Communication and Computation Systems
Identifiers
urn:nbn:se:ltu:diva-31459 (URN)10.1007/11809678_28 (DOI)2-s2.0-33749543482 (Scopus ID)5a2a9d00-7bed-11dc-a72d-000ea68e967b (Local ID)978-3-540-36925-7 (ISBN)5a2a9d00-7bed-11dc-a72d-000ea68e967b (Archive number)5a2a9d00-7bed-11dc-a72d-000ea68e967b (OAI)
Conference
Annual International Computing and Combinatorics Conference : 15/08/2006 - 18/08/2006
Note
Validerad; 2006; 20071016 (bson)Available from: 2016-09-30 Created: 2016-09-30 Last updated: 2020-08-26Bibliographically approved
Bengtsson, F. & Chen, J. (2006). Efficient algorithms for k maximum sums (ed.). Algorithmica, 46(1), 27-41
Open this publication in new window or tab >>Efficient algorithms for k maximum sums
2006 (English)In: Algorithmica, ISSN 0178-4617, E-ISSN 1432-0541, Vol. 46, no 1, p. 27-41Article in journal (Refereed) Published
Abstract [en]

We study the problem of computing the k maximum sum subsequences. Given a sequence of real numbers {x1,x2,...,xn} and an integer parameter k, 1 ≤ k ≤ 1/2n(n-1),the problem involves finding the k largest values of ∑ℓ=ijxℓ for 1 ≤ i ≤ j ≤ n.The problem for fixed k = 1, also known as the maximum sum subsequence problem, has received much attention in the literature and is linear-time solvable. Recently, Bae and Takaoka presented a Θ(nk)-time algorithm for the k maximum sum subsequences problem. In this paper we design an efficient algorithm that solves the above problem in O(min {k+nlog2n,n√k} ) time in the worst case. Our algorithm is optimal for k = Ω(n log 2 n) and improves over the previously best known result for any value of the user-defined parameter k < 1. Moreover, our results are also extended to the multi-dimensional versions of the k maximum sum subsequences problem; resulting in fast algorithms as well.

Keywords
Algorithm complexity, Algorithm design, Maximum subarray, Maximum subsequence, Maximum sum
National Category
Computer Sciences
Research subject
Dependable Communication and Computation Systems
Identifiers
urn:nbn:se:ltu:diva-15460 (URN)10.1007/s00453-006-0076-x (DOI)000240060500004 ()2-s2.0-33747888787 (Scopus ID)ef8af840-7bed-11dc-a72d-000ea68e967b (Local ID)ef8af840-7bed-11dc-a72d-000ea68e967b (Archive number)ef8af840-7bed-11dc-a72d-000ea68e967b (OAI)
Note

Validerad; 2006; 20071016 (bson)

Available from: 2016-09-29 Created: 2016-09-29 Last updated: 2023-11-09Bibliographically approved
Bengtsson, F. & Chen, J. (2005). A note on ranking k maximum sums (ed.). Luleå: Luleå tekniska universitet
Open this publication in new window or tab >>A note on ranking k maximum sums
2005 (English)Report (Other academic)
Abstract [en]

In this paper, we design a fast algorithm for ranking the k maximum sum subsequences. Given a sequence of real numbers and an integer parameter k, the problem is to compute k subsequences of consecutive elements with the sums of their elements being the largest, second largest, ..., and the k:th largest among all possible range sums. For any value of k, 1 <= k <= n(n+1)/2, our algorithm takes O(n + k log n) time in the worst case to rank all such subsequences. Our algorithm is optimal for k <= n.

Place, publisher, year, edition, pages
Luleå: Luleå tekniska universitet, 2005. p. 9
Series
Research report / Luleå University of Technology, ISSN 1402-1528 ; 2005:08
National Category
Computer Sciences
Research subject
Dependable Communication and Computation Systems
Identifiers
urn:nbn:se:ltu:diva-23826 (URN)894036c0-b2a0-11db-bf9d-000ea68e967b (Local ID)894036c0-b2a0-11db-bf9d-000ea68e967b (Archive number)894036c0-b2a0-11db-bf9d-000ea68e967b (OAI)
Note
Godkänd; 2005; 20070202 (ysko)Available from: 2016-09-29 Created: 2016-09-29 Last updated: 2018-01-10Bibliographically approved
Bengtsson, F. & Chen, J. (2004). Computing the k maximum subarrays fast (ed.). Luleå: Luleå tekniska universitet
Open this publication in new window or tab >>Computing the k maximum subarrays fast
2004 (English)Report (Other academic)
Abstract [en]

We study the problem of computing the k maximum sum subarrays. Given an array of real numbers and an integer, k, the problem involves finding the k largest values of the sum from i to j of the array, for any i and j. The problem for fixed k=1, also known as the maximum sum subsequence problem, has received much attention in the literature and is linear-time solvable. In this paper, we develop an algorithm requiring time proportional to n times square root of k for an array of length n. Moreover, for two-dimensional version of the problem, which computes the k largest sums over all rectangular subregions of an m times n array of real numbers, we show that it can be solved efficiently in the worst case as well.

Place, publisher, year, edition, pages
Luleå: Luleå tekniska universitet, 2004. p. 7
Series
Research report / Luleå University of Technology, ISSN 1402-1528 ; 2004:07
National Category
Computer Sciences
Research subject
Dependable Communication and Computation Systems
Identifiers
urn:nbn:se:ltu:diva-25205 (URN)e2ef04f0-ece6-11db-bc0c-000ea68e967b (Local ID)e2ef04f0-ece6-11db-bc0c-000ea68e967b (Archive number)e2ef04f0-ece6-11db-bc0c-000ea68e967b (OAI)
Note
Godkänd; 2004; 20070417 (ysko)Available from: 2016-09-29 Created: 2016-09-29 Last updated: 2018-01-10Bibliographically approved
Bengtsson, F. & Chen, J. (2004). Efficient algorithms for k maximum sums (ed.). In: (Ed.), Rudolf Fleischer; Gerhard Trippen (Ed.), Algorithms and Computation: 15th International Symposium, ISAAC 2004, Hong Kong, China, December 20-22, 2004, Proceedings. Paper presented at International Symposium on Algorithms and Computation : 20/12/2004 - 22/12/2004 (pp. 137-148). Berlin: Encyclopedia of Global Archaeology/Springer Verlag
Open this publication in new window or tab >>Efficient algorithms for k maximum sums
2004 (English)In: Algorithms and Computation: 15th International Symposium, ISAAC 2004, Hong Kong, China, December 20-22, 2004, Proceedings / [ed] Rudolf Fleischer; Gerhard Trippen, Berlin: Encyclopedia of Global Archaeology/Springer Verlag, 2004, p. 137-148Conference paper, Published paper (Refereed)
Abstract [en]

We study the problem of computing the k maximum sum subsequences. Given a sequence of real numbers (x1,x2,⋯,xn) and an integer parameter k, l ≤ k ≤ 1/2n(n -1), the problem involves finding the k largest values of Σl=ij xl for 1 ≤ i ≤ j ≤ n. The problem for fixed k = 1, also known as the maximum sum subsequence problem, has received much attention in the literature and is linear-time solvable. Recently, Bae and Takaoka presented a θ(nk)-time algorithm for the k maximum sum subsequences problem. In this paper, we design efficient algorithms that solve the above problem in O (min{k + n log2 n, n √k}) time in the worst case. Our algorithm is optimal for k ≥ n log2 n and improves over the previously best known result for any value of the user-defined parameter k. Moreover, our results are also extended to the multi-dimensional versions of the k maximum sum subsequences problem; resulting in fast algorithms as well.

Place, publisher, year, edition, pages
Berlin: Encyclopedia of Global Archaeology/Springer Verlag, 2004
Series
Lecture Notes in Computer Science, ISSN 0302-9743 ; 3341
National Category
Computer Sciences
Research subject
Dependable Communication and Computation Systems
Identifiers
urn:nbn:se:ltu:diva-35524 (URN)10.1007/978-3-540-30551-4_14 (DOI)2-s2.0-26844581198 (Scopus ID)a13f3f40-7beb-11dc-a72d-000ea68e967b (Local ID)978-3-540-24131-7 (ISBN)978-3-540-30551-4 (ISBN)a13f3f40-7beb-11dc-a72d-000ea68e967b (Archive number)a13f3f40-7beb-11dc-a72d-000ea68e967b (OAI)
Conference
International Symposium on Algorithms and Computation : 20/12/2004 - 22/12/2004
Note

Validerad; 2004; 20071016 (bson)

Available from: 2016-09-30 Created: 2016-09-30 Last updated: 2023-11-09Bibliographically approved
Bengtsson, F. & Chen, J. (2004). Space-efficient range-sum queries in OLAP (ed.). In: (Ed.), Yahiko Kambayashi; Mukesh Mohania; Wolfram Wöß (Ed.), Data Warehousing and Knowledge Discovery. Proceedings: 6th international conference, DaWaK 2004, Zaragoza, Spain, September 1 - 3, 2004 : proceedings. Paper presented at International Conference on Data Warehousing and Knowledge Discovery : 01/09/2004 - 03/09/2004 (pp. 87-96). Encyclopedia of Global Archaeology/Springer Verlag
Open this publication in new window or tab >>Space-efficient range-sum queries in OLAP
2004 (English)In: Data Warehousing and Knowledge Discovery. Proceedings: 6th international conference, DaWaK 2004, Zaragoza, Spain, September 1 - 3, 2004 : proceedings / [ed] Yahiko Kambayashi; Mukesh Mohania; Wolfram Wöß, Encyclopedia of Global Archaeology/Springer Verlag, 2004, p. 87-96Conference paper, Published paper (Refereed)
Abstract [en]

In this paper, we present a fast algorithm to answer range-sum queries in OLAP data cubes. Our algorithm supports constant-time queries while maintaining sub-linear time update and using minimum space. Furthermore, we study the trade-off between query time and update time. The complexity for query is O(2ℓd) and for updates O((2ℓ2ℓ√n)d) on a data cube of nd elements, where ℓ is a trade-off parameter. Our algorithm improve over previous best known results

Place, publisher, year, edition, pages
Encyclopedia of Global Archaeology/Springer Verlag, 2004
Series
Lecture Notes in Computer Science, ISSN 0302-9743 ; 3181
National Category
Computer Sciences
Research subject
Dependable Communication and Computation Systems
Identifiers
urn:nbn:se:ltu:diva-34204 (URN)10.1007/978-3-540-30076-2_9 (DOI)2-s2.0-33845655201 (Scopus ID)8563f470-c1ea-11db-9ea3-000ea68e967b (Local ID)978-3-540-22937-7 (ISBN)978-3-540-30076-2 (ISBN)8563f470-c1ea-11db-9ea3-000ea68e967b (Archive number)8563f470-c1ea-11db-9ea3-000ea68e967b (OAI)
Conference
International Conference on Data Warehousing and Knowledge Discovery : 01/09/2004 - 03/09/2004
Note

Validerad; 2004; 20070105 (pafi)

Available from: 2016-09-30 Created: 2016-09-30 Last updated: 2020-08-26Bibliographically approved
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