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ICML
2005
IEEE
14 years 9 months ago
Learning predictive representations from a history
Predictive State Representations (PSRs) have shown a great deal of promise as an alternative to Markov models. However, learning a PSR from a single stream of data generated from ...
Eric Wiewiora
BIRTHDAY
2003
Springer
14 years 2 months ago
Computational Proof as Experiment: Probabilistic Algorithms from a Thermodynamic Perspective
Abstract. A novel framework for the design and analysis of energy-aware algorithms is presented, centered around a deterministic Bit-level (Boltzmann) Random Access Machine or BRAM...
Krishna V. Palem
ICMLA
2010
13 years 7 months ago
Multi-Agent Inverse Reinforcement Learning
Learning the reward function of an agent by observing its behavior is termed inverse reinforcement learning and has applications in learning from demonstration or apprenticeship l...
Sriraam Natarajan, Gautam Kunapuli, Kshitij Judah,...
COLT
1993
Springer
14 years 1 months ago
Learning from a Population of Hypotheses
We introduce a new formal model in which a learning algorithm must combine a collection of potentially poor but statistically independent hypothesis functions in order to approxima...
Michael J. Kearns, H. Sebastian Seung
ALT
2009
Springer
14 years 1 months ago
The Follow Perturbed Leader Algorithm Protected from Unbounded One-Step Losses
In this paper the sequential prediction problem with expert advice is considered for the case when the losses of experts suffered at each step can be unbounded. We present some mo...
Vladimir V. V'yugin