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Average-Time Games

by Marcin Jurdziński, Ashutosh Trivedi - FSTTCS 2008 , 2008
"... ABSTRACT. An average-time game is played on the infinite graph of configurations of a finite timed automaton. The two players, Min and Max, construct an infinite run of the automaton by taking turns to perform a timed transition. Player Min wants to minimize the average time per transition and playe ..."
Abstract - Cited by 4 (3 self) - Add to MetaCart
ABSTRACT. An average-time game is played on the infinite graph of configurations of a finite timed automaton. The two players, Min and Max, construct an infinite run of the automaton by taking turns to perform a timed transition. Player Min wants to minimize the average time per transition

On Average Time Hierarchies

by Mikael Goldmann, Per Grape, Johan Håstad - Information Processing Letters , 1997
"... For a time-constructible function T we give an explicit language L T which can be recognized in time T (n). We prove that any Turing machine that recognizes L T requires time close to T (n) for most inputs, thus forming an average time hierarchy. The existence of the average time hierarchy was kn ..."
Abstract - Cited by 2 (0 self) - Add to MetaCart
For a time-constructible function T we give an explicit language L T which can be recognized in time T (n). We prove that any Turing machine that recognizes L T requires time close to T (n) for most inputs, thus forming an average time hierarchy. The existence of the average time hierarchy

Average Time Complexity Classes

by Jin-yi Cai, Alan Selman , 1995
"... We extend Levin's theory of average polynomial time to arbitrary time bounds and prove that average time complexity classes form as fine a hierarchy as do deterministic time complexity classes. Keywords: computational complexity, average time complexity classes, hierarchy, Average-P, logarithm ..."
Abstract - Cited by 2 (0 self) - Add to MetaCart
We extend Levin's theory of average polynomial time to arbitrary time bounds and prove that average time complexity classes form as fine a hierarchy as do deterministic time complexity classes. Keywords: computational complexity, average time complexity classes, hierarchy, Average

Drift analysis and average time complexity of evolutionary algorithms

by Jun He, Xin Yao - Artificial Intelligence , 2001
"... The computational time complexity is an important topic in the theory of evolutionary algorithms (EAs). This paper reports some new results on the average time complexity of EAs. Based on drift analysis, some useful drift conditions for deriving the time complexity of EAs are studied, including cond ..."
Abstract - Cited by 107 (33 self) - Add to MetaCart
The computational time complexity is an important topic in the theory of evolutionary algorithms (EAs). This paper reports some new results on the average time complexity of EAs. Based on drift analysis, some useful drift conditions for deriving the time complexity of EAs are studied, including

Average Time Fast SVP . . .

by Claus P. Schnorr , 2009
"... ..."
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Abstract not found

Illiquidity and stock returns: cross-section and time-series effects,

by Yakov Amihud - Journal of Financial Markets , 2002
"... Abstract This paper shows that over time, expected market illiquidity positively affects ex ante stock excess return, suggesting that expected stock excess return partly represents an illiquidity premium. This complements the cross-sectional positive return-illiquidity relationship. Also, stock ret ..."
Abstract - Cited by 864 (9 self) - Add to MetaCart
returns are negatively related over time to contemporaneous unexpected illiquidity. The illiquidity measure here is the average across stocks of the daily ratio of absolute stock return to dollar volume, which is easily obtained from daily stock data for long time series in most stock markets. Illiquidity

Consensus Problems in Networks of Agents with Switching Topology and Time-Delays

by Reza Olfati Saber, Richard M. Murray , 2003
"... In this paper, we discuss consensus problems for a network of dynamic agents with fixed and switching topologies. We analyze three cases: i) networks with switching topology and no time-delays, ii) networks with fixed topology and communication time-delays, and iii) max-consensus problems (or leader ..."
Abstract - Cited by 1112 (21 self) - Add to MetaCart
In this paper, we discuss consensus problems for a network of dynamic agents with fixed and switching topologies. We analyze three cases: i) networks with switching topology and no time-delays, ii) networks with fixed topology and communication time-delays, and iii) max-consensus problems (or

Distributed space-time-coded protocols for exploiting cooperative diversity in wireless networks

by J. Nicholas Laneman, Gregory W. Wornell - IEEE TRANS. INF. THEORY , 2003
"... We develop and analyze space–time coded cooperative diversity protocols for combating multipath fading across multiple protocol layers in a wireless network. The protocols exploit spatial diversity available among a collection of distributed terminals that relay messages for one another in such a m ..."
Abstract - Cited by 622 (5 self) - Add to MetaCart
We develop and analyze space–time coded cooperative diversity protocols for combating multipath fading across multiple protocol layers in a wireless network. The protocols exploit spatial diversity available among a collection of distributed terminals that relay messages for one another in such a

Minimum Average Time Broadcast Graphs

by Arthur L. Liestman, Natasa Przuli, Nata Sa, Pr Zulj
"... We initiate the study of minimum average time broadcast graphs - those graphs on n vertices with the fewest edges in which every vertex can broadcast in minimum average time. We find minimum average time broadcast graphs for all even n and for more than half of all odd n. In addition, we give som ..."
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We initiate the study of minimum average time broadcast graphs - those graphs on n vertices with the fewest edges in which every vertex can broadcast in minimum average time. We find minimum average time broadcast graphs for all even n and for more than half of all odd n. In addition, we give

Graphs over Time: Densification Laws, Shrinking Diameters and Possible Explanations

by Jure Leskovec, Jon Kleinberg, Christos Faloutsos , 2005
"... How do real graphs evolve over time? What are “normal” growth patterns in social, technological, and information networks? Many studies have discovered patterns in static graphs, identifying properties in a single snapshot of a large network, or in a very small number of snapshots; these include hea ..."
Abstract - Cited by 541 (48 self) - Add to MetaCart
, and we observe some surprising phenomena. First, most of these graphs densify over time, with the number of edges growing superlinearly in the number of nodes. Second, the average distance between nodes often shrinks over time, in contrast to the conventional wisdom that such distance parameters should
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