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AICOM
2002
103views more  AICOM 2002»
13 years 9 months ago
The emergent computational potential of evolving artificial living systems
The computational potential of artificial living systems can be studied without knowing the algorithms that govern their behavior. Modeling single organisms by means of socalled c...
Jirí Wiedermann, Jan van Leeuwen
ISVC
2010
Springer
13 years 7 months ago
Attention-Based Target Localization Using Multiple Instance Learning
Abstract. We propose a novel Multiple Instance Learning (MIL) framework to perform target localization from image sequences. The proposed approach consists of a softmax logistic re...
Karthik Sankaranarayanan, James W. Davis
ICML
2010
IEEE
13 years 10 months ago
Learning Efficiently with Approximate Inference via Dual Losses
Many structured prediction tasks involve complex models where inference is computationally intractable, but where it can be well approximated using a linear programming relaxation...
Ofer Meshi, David Sontag, Tommi Jaakkola, Amir Glo...
JMLR
2002
115views more  JMLR 2002»
13 years 9 months ago
PAC-Bayesian Generalisation Error Bounds for Gaussian Process Classification
Approximate Bayesian Gaussian process (GP) classification techniques are powerful nonparametric learning methods, similar in appearance and performance to support vector machines....
Matthias Seeger
ICFEM
2004
Springer
14 years 2 months ago
Learning to Verify Safety Properties
We present a novel approach for verifying safety properties of finite state machines communicating over unbounded FIFO channels that is based on applying machine learning techniqu...
Abhay Vardhan, Koushik Sen, Mahesh Viswanathan, Gu...