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» On the Convergence of Bound Optimization Algorithms
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AAAI
2004
15 years 5 months ago
Performance Bounded Reinforcement Learning in Strategic Interactions
Despite increasing deployment of agent technologies in several business and industry domains, user confidence in fully automated agent driven applications is noticeably lacking. T...
Bikramjit Banerjee, Jing Peng
AAMAS
2007
Springer
15 years 4 months ago
Generalized multiagent learning with performance bound
Abstract – Despite increasing deployment of agent technologies in several business and industry domains, user confidence in fully automated agent driven applications is noticeab...
Bikramjit Banerjee, Jing Peng
ICML
2005
IEEE
16 years 5 months ago
Bounded real-time dynamic programming: RTDP with monotone upper bounds and performance guarantees
MDPs are an attractive formalization for planning, but realistic problems often have intractably large state spaces. When we only need a partial policy to get from a fixed start s...
H. Brendan McMahan, Maxim Likhachev, Geoffrey J. G...
ICML
2009
IEEE
16 years 5 months ago
Proximal regularization for online and batch learning
Many learning algorithms rely on the curvature (in particular, strong convexity) of regularized objective functions to provide good theoretical performance guarantees. In practice...
Chuong B. Do, Quoc V. Le, Chuan-Sheng Foo
CORR
2008
Springer
125views Education» more  CORR 2008»
15 years 4 months ago
Adversary lower bounds for nonadaptive quantum algorithms
We present two general methods for proving lower bounds on the query complexity of nonadaptive quantum algorithms. Both methods are based on the adversary method of Ambainis. We sh...
Pascal Koiran, Jürgen Landes, Natacha Portier...