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SSPR
2010
Springer
14 years 10 months ago
Information Theoretical Kernels for Generative Embeddings Based on Hidden Markov Models
Many approaches to learning classifiers for structured objects (e.g., shapes) use generative models in a Bayesian framework. However, state-of-the-art classifiers for vectorial d...
André F. T. Martins, Manuele Bicego, Vittor...
PODC
2009
ACM
16 years 12 days ago
Load balancing without regret in the bulletin board model
We analyze the performance of protocols for load balancing in distributed systems based on no-regret algorithms from online learning theory. These protocols treat load balancing a...
Éva Tardos, Georgios Piliouras, Robert D. K...
CORR
2007
Springer
88views Education» more  CORR 2007»
14 years 12 months ago
Decisive Markov Chains
We consider qualitative and quantitative verification problems for infinite-state Markov chains. We call a Markov chain decisive w.r.t. a given set of target states F if it almos...
Parosh Aziz Abdulla, Noomene Ben Henda, Richard Ma...
PODC
2004
ACM
15 years 5 months ago
On the design of distributed protocols from differential equations
We propose a framework to translate certain subclasses of differential equation systems into distributed protocols that are practical. The synthesized protocols are state machine...
Indranil Gupta
NEUROSCIENCE
2001
Springer
15 years 4 months ago
Analysis and Synthesis of Agents That Learn from Distributed Dynamic Data Sources
We propose a theoretical framework for specification and analysis of a class of learning problems that arise in open-ended environments that contain multiple, distributed, dynamic...
Doina Caragea, Adrian Silvescu, Vasant Honavar