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BTrees with Relaxed Balance
 In Proceedings of the 9th International Parallel Processing Symposium
, 1993
"... Btrees with relaxed balance have been defined to facilitate fast updating on sharedmemory asynchronous parallel architectures. To obtain this, rebalancing has been uncoupled from the updating such that extensive locking can be avoided in connection with updates. We analyze Btrees with relaxed bal ..."
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Cited by 13 (6 self)
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Btrees with relaxed balance have been defined to facilitate fast updating on sharedmemory asynchronous parallel architectures. To obtain this, rebalancing has been uncoupled from the updating such that extensive locking can be avoided in connection with updates. We analyze Btrees with relaxed
Variants of (a, b)Trees with Relaxed Balance
, 1999
"... New variants of (a, b)trees with relaxed balance are proposed. These variants have better space utilization than the earlier proposals, while the asymptotic complexity of rebalancing is unchanged. The proof of complexity, which is derived, is much simpler than the ones previously published. Through ..."
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New variants of (a, b)trees with relaxed balance are proposed. These variants have better space utilization than the earlier proposals, while the asymptotic complexity of rebalancing is unchanged. The proof of complexity, which is derived, is much simpler than the ones previously published
Bslack trees: Space Efficient Btrees
"... Abstract. Bslack trees, a subclass of Btrees that have substantially better worstcase space complexity, are introduced. They store n keys in height O(logb n), where b is the maximum node degree. Updates can be performed in O(log b 2 n) amortized time. A relaxed balance version, which is well suit ..."
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Abstract. Bslack trees, a subclass of Btrees that have substantially better worstcase space complexity, are introduced. They store n keys in height O(logb n), where b is the maximum node degree. Updates can be performed in O(log b 2 n) amortized time. A relaxed balance version, which is well
Algorithms for simultaneous sparse approximation. Part II: Convex relaxation
, 2004
"... Abstract. A simultaneous sparse approximation problem requests a good approximation of several input signals at once using different linear combinations of the same elementary signals. At the same time, the problem balances the error in approximation against the total number of elementary signals th ..."
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Cited by 366 (5 self)
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Abstract. A simultaneous sparse approximation problem requests a good approximation of several input signals at once using different linear combinations of the same elementary signals. At the same time, the problem balances the error in approximation against the total number of elementary signals
Topology BTrees and Their Applications
"... . The wellknown Btree data structure provides a mechanism for dynamically maintaining balanced binary trees in external memory. We present an externalmemory dynamic data structure for maintaining arbitrary binary trees. Our data structure, which we call the topology Btree, is an externalmemory ..."
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Cited by 16 (0 self)
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. The wellknown Btree data structure provides a mechanism for dynamically maintaining balanced binary trees in external memory. We present an externalmemory dynamic data structure for maintaining arbitrary binary trees. Our data structure, which we call the topology Btree, is an external
Expander Flows, Geometric Embeddings and Graph Partitioning
 IN 36TH ANNUAL SYMPOSIUM ON THE THEORY OF COMPUTING
, 2004
"... We give a O( log n)approximation algorithm for sparsest cut, balanced separator, and graph conductance problems. This improves the O(log n)approximation of Leighton and Rao (1988). We use a wellknown semidefinite relaxation with triangle inequality constraints. Central to our analysis is a ..."
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Cited by 312 (18 self)
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We give a O( log n)approximation algorithm for sparsest cut, balanced separator, and graph conductance problems. This improves the O(log n)approximation of Leighton and Rao (1988). We use a wellknown semidefinite relaxation with triangle inequality constraints. Central to our analysis is a
How Can Manage Balance Tree (BTree)
"... Abstract — In Btrees, internal (nonleaf) nodes can have a variable number of child nodes within some predefined range. When data is inserted or removed from a node, its number of child nodes changes. In order to maintain the predefined range, internal nodes may be joined or split. Because a range ..."
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range of child nodes is permitted, Btrees do not need rebalancing as frequently as other selfbalancing search trees, but may waste some space, since nodes are not entirely full. The lower and upper bounds on the number of child nodes are typically fixed for a particular implementation. For example
Highly Scalable Data Balanced Distributed Btrees
, 1995
"... Scalable distributed search structures are needed to maintain large volumes of data and for parallel databases. In this paper, we analyze the performance of two large scale databalanced distributed search structures, the dBtree and the dEtree. The dBtree is a distributed Btree that replicates i ..."
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Cited by 2 (1 self)
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Scalable distributed search structures are needed to maintain large volumes of data and for parallel databases. In this paper, we analyze the performance of two large scale databalanced distributed search structures, the dBtree and the dEtree. The dBtree is a distributed Btree that replicates
Robust balancing in Btrees (Extended Abstract)
"... Robust balancing is a technique for maintaining generalized Btrees with a cumulative rebalancing cost that is asymptotically linear. It is especially significant in conjunction with fingers, which can make cumulative search cost linear. We define a new family of robust balancing algorithms which in ..."
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Robust balancing is a technique for maintaining generalized Btrees with a cumulative rebalancing cost that is asymptotically linear. It is especially significant in conjunction with fingers, which can make cumulative search cost linear. We define a new family of robust balancing algorithms which
Lecture Notes: WeightBalanced Btree
"... In this lecture, we will study a technique called weightbalancing, which is very important in designing data structures, as we will see in later lectures. We will introduce the technique on the Btree, which can be regarded as the EM equivalent of the binary search tree in RAM. 1 Btree Structure. ..."
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In this lecture, we will study a technique called weightbalancing, which is very important in designing data structures, as we will see in later lectures. We will introduce the technique on the Btree, which can be regarded as the EM equivalent of the binary search tree in RAM. 1 Btree Structure
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