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| Content Provider | ACM Digital Library |
|---|---|
| Author | Moran, Shlomo Snir, Marc Manber, Udi |
| Copyright Year | 1985 |
| Abstract | Combinatorial techniques for extending lower bound results for decision trees to general types of queries are presented. Problems that are defined by simple inequalities between inputs, called order invariant problems, are considered. A decision tree is called $\textit{k-bounded}$ if each query depends on at most $\textit{k}$ variables. No further assumptions on the type of queries are made. It is proved that one can replace the queries of any $\textit{k}-bounded$ decision tree that solves an order-invariant problem over a large enough input domain with $\textit{k}-bounded$ queries whose outcome depends only on the relative order of the inputs. As a consequence, all existing lower bounds for comparison-based algorithms are valid for general $\textit{k}-bounded$ decision trees, where $\textit{k}$ is a constant.An $&OHgr;(\textit{n}$ log $\textit{n})$ lower bound for the element uniqueness problem and several other problems for any $\textit{k}-bounded$ decision tree, such that $\textit{k}$ = $\textit{O}(\textit{nc})$ and $\textit{c}$ < 1/2 is proved. This lower bound is tight since there exist $\textit{n}1/2-bounded$ decision trees of complexity $\textit{O}(\textit{n})$ that solve the element-uniqueness problem. All the lower bounds mentioned above are shown to hold for nondeterministic and probabilistic decision trees as well. |
| Starting Page | 938 |
| Ending Page | 949 |
| Page Count | 12 |
| File Format | |
| ISSN | 00045411 |
| e-ISSN | 1557735X |
| DOI | 10.1145/4221.4259 |
| Journal | Journal of the ACM (JACM) |
| Volume Number | 32 |
| Issue Number | 4 |
| Language | English |
| Publisher | Association for Computing Machinery (ACM) |
| Publisher Date | 1985-10-01 |
| Publisher Place | New York |
| Access Restriction | One Nation One Subscription (ONOS) |
| Content Type | Text |
| Resource Type | Article |
| Subject | Hardware and Architecture Information Systems Control and Systems Engineering Artificial Intelligence Software |
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