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NIPS
2007
13 years 10 months ago
A neural network implementing optimal state estimation based on dynamic spike train decoding
It is becoming increasingly evident that organisms acting in uncertain dynamical environments often employ exact or approximate Bayesian statistical calculations in order to conti...
Omer Bobrowski, Ron Meir, Shy Shoham, Yonina C. El...
ATAL
2010
Springer
13 years 9 months ago
Closing the learning-planning loop with predictive state representations
A central problem in artificial intelligence is to choose actions to maximize reward in a partially observable, uncertain environment. To do so, we must learn an accurate model of ...
Byron Boots, Sajid M. Siddiqi, Geoffrey J. Gordon
ICDT
2010
ACM
219views Database» more  ICDT 2010»
14 years 6 months ago
Aggregate Queries for Discrete and Continuous Probabilistic XML
Sources of data uncertainty and imprecision are numerous. A way to handle this uncertainty is to associate probabilistic annotations to data. Many such probabilistic database mode...
Serge Abiteboul, T.-H Hubert Chan, Evgeny Kharlamo...
IROS
2009
IEEE
185views Robotics» more  IROS 2009»
14 years 3 months ago
Scalable and convergent multi-robot passive and active sensing
— A major barrier preventing the wide employment of mobile networks of robots in tasks such as exploration, mapping, surveillance, and environmental monitoring is the lack of efï...
Elias B. Kosmatopoulos, Lefteris Doitsidis, Konsta...
GLOBECOM
2008
IEEE
14 years 3 months ago
Network Resource Allocation for Competing Multiple Description Transmissions
Providing real-time multimedia services over a best-effort network is challenging due to the stringent delay requirements in the presence of complex network dynamics. Multiple des...
Ying Li, Chao Tian, Suhas N. Diggavi, Mung Chiang,...