Sciweavers

Share
warning: Creating default object from empty value in /var/www/modules/taxonomy/taxonomy.module on line 1416.
AAAI
2012
8 years 3 months ago
Discovering Constraints for Inductive Process Modeling
Scientists use two forms of knowledge in the construction of explanatory models: generalized entities and processes that relate them; and constraints that specify acceptable combi...
Ljupco Todorovski, Will Bridewell, Pat Langley
SDM
2012
SIAM
261views Data Mining» more  SDM 2012»
8 years 3 months ago
Combining Active Learning and Dynamic Dimensionality Reduction
To date, many active learning techniques have been developed for acquiring labels when training data is limited. However, an important aspect of the problem has often been neglect...
Mustafa Bilgic
AAAI
2011
9 years 1 months ago
Coordinated Multi-Agent Reinforcement Learning in Networked Distributed POMDPs
In many multi-agent applications such as distributed sensor nets, a network of agents act collaboratively under uncertainty and local interactions. Networked Distributed POMDP (ND...
Chongjie Zhang, Victor R. Lesser
EDBT
2011
ACM
199views Database» more  EDBT 2011»
9 years 4 months ago
Predicting completion times of batch query workloads using interaction-aware models and simulation
A question that database administrators (DBAs) routinely need to answer is how long a batch query workload will take to complete. This question arises, for example, while planning...
Mumtaz Ahmad, Songyun Duan, Ashraf Aboulnaga, Shiv...
BMCBI
2006
120views more  BMCBI 2006»
10 years 1 months ago
Integrating protein structures and precomputed genealogies in the Magnum database: Examples with cellular retinoid binding prote
Background: When accurate models for the divergent evolution of protein sequences are integrated with complementary biological information, such as folded protein structures, anal...
Michael E. Bradley, Steven A. Benner
ICRA
2009
IEEE
137views Robotics» more  ICRA 2009»
10 years 8 months ago
Unsupervised learning of 3D object models from partial views
— We present an algorithm for learning 3D object models from partial object observations. The input to our algorithm is a sequence of 3D laser range scans. Models learned from th...
Michael Ruhnke, Bastian Steder, Giorgio Grisetti, ...
books